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| 1`HB`1138_bus`1138`1138`4054`yes`1138`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`D. Tylavsky`I. Duff, R. Grimes, J. Lewis`1985`power network problem` | |
| 2`HB`494_bus`494`494`1666`yes`494`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`D. Tylavsky`I. Duff, R. Grimes, J. Lewis`1985`power network problem` | |
| 3`HB`662_bus`662`662`2474`yes`662`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`D. Tylavsky`I. Duff, R. Grimes, J. Lewis`1985`power network problem` | |
| 4`HB`685_bus`685`685`3249`yes`685`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`D. Tylavsky`I. Duff, R. Grimes, J. Lewis`1985`power network problem` | |
| 5`HB`abb313`313`176`1557`yes`176`1`2`0`0%`0%`binary`rectangular`no`no`M. Abbas`A. Curtis, I. Duff, J. Reid`1974`least squares problem` | |
| 6`HB`arc130`130`130`1037`yes`130`55`55`245`76%`0%`real`unsymmetric`no`no`A. Curtis`A. Curtis, I. Duff, J. Reid`1974`materials problem` | |
| 7`HB`ash219`219`85`438`yes`85`1`1`0`0%`0%`binary`rectangular`no`no`V. Askenazi`A. Curtis, I. Duff, J. Reid`1974`least squares problem` | |
| 8`HB`ash292`292`292`2208`yes`292`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`V. Askenazi`A. Curtis, I. Duff, J. Reid`1974`least squares problem` | |
| 9`HB`ash331`331`104`662`yes`104`1`1`0`0%`0%`binary`rectangular`no`no`V. Askenazi`A. Curtis, I. Duff, J. Reid`1974`least squares problem` | |
| 10`HB`ash608`608`188`1216`yes`188`1`1`0`0%`0%`binary`rectangular`no`no`V. Askenazi`A. Curtis, I. Duff, J. Reid`1974`least squares problem` | |
| 11`HB`ash85`85`85`523`yes`85`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`V. Askenazi`A. Curtis, I. Duff, J. Reid`1974`least squares problem` | |
| 12`HB`ash958`958`292`1916`yes`292`1`1`0`0%`0%`binary`rectangular`no`no`V. Askenazi`A. Curtis, I. Duff, J. Reid`1974`least squares problem` | |
| 13`HB`bcspwr01`39`39`131`yes`39`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 14`HB`bcspwr02`49`49`167`yes`49`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 15`HB`bcspwr03`118`118`476`yes`118`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 16`HB`bcspwr04`274`274`1612`yes`274`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 17`HB`bcspwr05`443`443`1623`yes`443`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 18`HB`bcspwr06`1454`1454`5300`yes`1454`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 19`HB`bcspwr07`1612`1612`5824`yes`1612`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 20`HB`bcspwr08`1624`1624`6050`yes`1624`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 21`HB`bcspwr09`1723`1723`6511`yes`1723`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 22`HB`bcspwr10`5300`5300`21842`yes`5300`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`B. Dembart, J. Lewis`I. Duff, R. Grimes, J. Lewis`1981`power network problem` | |
| 23`HB`bcsstk01`48`48`400`yes`48`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 24`HB`bcsstk02`66`66`4356`yes`66`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 25`HB`bcsstk03`112`112`640`yes`112`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 26`HB`bcsstk04`132`132`3648`yes`132`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 27`HB`bcsstk05`153`153`2423`yes`153`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 28`HB`bcsstk06`420`420`7860`yes`420`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 29`HB`bcsstk07`420`420`7860`yes`420`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`duplicate structural problem`\nduplicate of HB/bcsstk06\n | |
| 30`HB`bcsstk08`1074`1074`12960`yes`1074`4`4`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 31`HB`bcsstk09`1083`1083`18437`yes`1083`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 32`HB`bcsstk10`1086`1086`22070`yes`1086`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 33`HB`bcsstk11`1473`1473`34241`yes`1473`9`9`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 34`HB`bcsstk12`1473`1473`34241`yes`1473`9`9`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`duplicate structural problem`\nduplicate of HB/bcsstk11\n | |
| 35`HB`bcsstk13`2003`2003`83883`yes`2003`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`computational fluid dynamics problem` | |
| 36`HB`bcsstk14`1806`1806`63454`yes`1806`41`41`0`symmetric`symmetric`real`symmetric`yes`yes`M. Will`I. Duff, R. Grimes, J. Lewis`1985`structural problem` | |
| 37`HB`bcsstk15`3948`3948`117816`yes`3948`7`7`0`symmetric`symmetric`real`symmetric`yes`yes`M. Will`I. Duff, R. Grimes, J. Lewis`1985`structural problem` | |
| 38`HB`bcsstk16`4884`4884`290378`yes`4884`75`75`0`symmetric`symmetric`real`symmetric`yes`yes`M. Will`I. Duff, R. Grimes, J. Lewis`1985`structural problem` | |
| 39`HB`bcsstk17`10974`10974`428650`yes`10974`519`519`0`symmetric`symmetric`real`symmetric`yes`yes`M. Will`I. Duff, R. Grimes, J. Lewis`1985`structural problem` | |
| 40`HB`bcsstk18`11948`11948`149090`yes`11948`792`792`0`symmetric`symmetric`real`symmetric`yes`yes`M. Will`I. Duff, R. Grimes, J. Lewis`1985`structural problem` | |
| 41`HB`bcsstk19`817`817`6853`yes`817`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 42`HB`bcsstk20`485`485`3135`yes`485`4`4`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 43`HB`bcsstk21`3600`3600`26600`yes`3600`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 44`HB`bcsstk22`138`138`696`yes`138`4`4`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 45`HB`bcsstk23`3134`3134`45178`yes`3134`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 46`HB`bcsstk24`3562`3562`159910`yes`3562`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 47`HB`bcsstk25`15439`15439`252241`yes`15439`13`13`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 48`HB`bcsstk26`1922`1922`30336`yes`1922`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Mera, R. Cigel, J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 49`HB`bcsstk27`1224`1224`56126`yes`1224`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Mera, R. Cigel, J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 50`HB`bcsstk28`4410`4410`219024`yes`4410`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Mera, R. Cigel, J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 51`HB`bcsstk29`13992`13992`619488`yes`13992`28`28`0`symmetric`symmetric`binary`symmetric`yes`no`R. Cigel, R. Grimes, J. Lewis, E. Meyer`I. Duff, R. Grimes, J. Lewis`1986`structural problem` | |
| 52`HB`bcsstk30`28924`28924`2043492`yes`28924`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Cigel, R. Grimes, J. Lewis, E. Meyer`I. Duff, R. Grimes, J. Lewis`1986`structural problem` | |
| 53`HB`bcsstk31`35588`35588`1181416`yes`35588`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`R. Cigel, R. Grimes, J. Lewis, E. Meyer`I. Duff, R. Grimes, J. Lewis`1986`structural problem` | |
| 54`HB`bcsstk32`44609`44609`2014701`yes`44609`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Cigel, R. Grimes, J. Lewis, E. Meyer`I. Duff, R. Grimes, J. Lewis`1986`structural problem` | |
| 55`HB`bcsstk33`8738`8738`591904`yes`8738`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Cigel, R. Grimes, J. Lewis, E. Meyer`I. Duff, R. Grimes, J. Lewis`1986`structural problem` | |
| 56`HB`bcsstm01`48`48`24`no`24`26`48`24`symmetric`symmetric`integer`symmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 57`HB`bcsstm02`66`66`66`yes`66`66`66`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 58`HB`bcsstm03`112`112`72`no`72`74`112`40`symmetric`symmetric`real`symmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 59`HB`bcsstm04`132`132`66`no`66`68`132`66`symmetric`symmetric`real`symmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 60`HB`bcsstm05`153`153`153`yes`153`153`153`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 61`HB`bcsstm06`420`420`420`yes`420`420`420`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 62`HB`bcsstm07`420`420`7252`yes`420`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 63`HB`bcsstm08`1074`1074`1074`yes`1074`1074`1074`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 64`HB`bcsstm09`1083`1083`1083`yes`1083`1083`1083`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 65`HB`bcsstm10`1086`1086`22092`yes`1086`2`2`0`symmetric`symmetric`real`symmetric`yes`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 66`HB`bcsstm11`1473`1473`1473`yes`1473`1473`1473`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 67`HB`bcsstm12`1473`1473`19659`yes`1473`10`10`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 68`HB`bcsstm13`2003`2003`21181`no`1241`574`1334`762`symmetric`symmetric`real`symmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1982`computational fluid dynamics problem` | |
| 69`HB`bcsstm19`817`817`817`yes`817`817`817`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 70`HB`bcsstm20`485`485`485`yes`485`485`485`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 71`HB`bcsstm21`3600`3600`3600`yes`3600`3600`3600`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 72`HB`bcsstm22`138`138`138`yes`138`138`138`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 73`HB`bcsstm23`3134`3134`3134`yes`3134`3134`3134`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 74`HB`bcsstm24`3562`3562`3562`yes`3562`3562`3562`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 75`HB`bcsstm25`15439`15439`15439`yes`15439`15439`15439`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 76`HB`bcsstm26`1922`1922`1922`yes`1922`1922`1922`0`symmetric`symmetric`real`symmetric`yes`yes`A. Mera, R. Cigel, J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 77`HB`bcsstm27`1224`1224`56126`yes`1224`1`1`0`symmetric`symmetric`real`symmetric`yes`no`A. Mera, R. Cigel, J. Lewis`I. Duff, R. Grimes, J. Lewis`1984`structural problem` | |
| 78`HB`beacxc`497`506`50409`no`449`10`66`0`0%`0%`real`rectangular`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 79`HB`beaflw`497`507`53403`no`460`13`13`0`0%`0%`real`rectangular`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 80`HB`beause`497`507`44551`no`459`31`8`0`0%`0%`real`rectangular`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 81`HB`blckhole`2132`2132`14872`yes`2132`12`12`0`symmetric`symmetric`binary`symmetric`yes`no`E. Meyer`I. Duff, R. Grimes, J. Lewis`1983`structural problem` | |
| 82`HB`bp_0`822`822`3276`yes`822`822`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`optimization problem sequence`\nnext: HB/bp_200 first: HB/bp_0\n | |
| 83`HB`bp_1000`822`822`4661`yes`822`463`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/bp_1200 first: HB/bp_0\n | |
| 84`HB`bp_1200`822`822`4726`yes`822`447`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/bp_1400 first: HB/bp_0\n | |
| 85`HB`bp_1400`822`822`4790`yes`822`403`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/bp_1600 first: HB/bp_0\n | |
| 86`HB`bp_1600`822`822`4841`yes`822`450`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: - first: HB/bp_0\n | |
| 87`HB`bp_200`822`822`3802`yes`822`673`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/bp_400 first: HB/bp_0\n | |
| 88`HB`bp_400`822`822`4028`yes`822`591`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/bp_600 first: HB/bp_0\n | |
| 89`HB`bp_600`822`822`4172`yes`822`537`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/bp_800 first: HB/bp_0\n | |
| 90`HB`bp_800`822`822`4534`yes`822`492`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/bp_1000 first: HB/bp_0\n | |
| 91`HB`can_1054`1054`1054`12196`yes`1054`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 92`HB`can_1072`1072`1072`12444`yes`1072`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 93`HB`can_144`144`144`1296`yes`144`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 94`HB`can_161`161`161`1377`yes`161`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 95`HB`can_187`187`187`1491`yes`187`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 96`HB`can_229`229`229`1777`yes`229`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 97`HB`can_24`24`24`160`yes`24`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 98`HB`can_256`256`256`2916`yes`256`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 99`HB`can_268`268`268`3082`yes`268`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 100`HB`can_292`292`292`2540`yes`292`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 101`HB`can_445`445`445`3809`yes`445`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 102`HB`can_61`61`61`557`yes`61`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 103`HB`can_62`62`62`218`yes`62`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 104`HB`can_634`634`634`7228`yes`634`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 105`HB`can_715`715`715`6665`yes`715`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 106`HB`can_73`73`73`377`yes`73`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 107`HB`can_838`838`838`10010`yes`838`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 108`HB`can_96`96`96`768`yes`96`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`L. Marro`I. Duff, R. Grimes, J. Lewis`1981`structural problem` | |
| 109`HB`curtis54`54`54`291`yes`54`1`1`0`95%`95%`binary`unsymmetric`no`no`A. Curtis`A. Curtis, I. Duff, J. Reid`1971`2D/3D problem` | |
| 110`HB`dwt_1005`1005`1005`8621`yes`1005`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 111`HB`dwt_1007`1007`1007`8575`yes`1007`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 112`HB`dwt_1242`1242`1242`10426`yes`1242`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 113`HB`dwt_162`162`162`1182`yes`162`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 114`HB`dwt_193`193`193`3493`yes`193`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 115`HB`dwt_198`198`198`1392`yes`198`6`6`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 116`HB`dwt_209`209`209`1743`yes`209`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 117`HB`dwt_221`221`221`1629`yes`221`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 118`HB`dwt_234`234`234`834`yes`234`7`7`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 119`HB`dwt_245`245`245`1461`yes`245`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 120`HB`dwt_2680`2680`2680`25026`yes`2680`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 121`HB`dwt_307`307`307`2523`yes`307`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 122`HB`dwt_310`310`310`2448`yes`310`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 123`HB`dwt_346`346`346`3226`yes`346`4`4`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 124`HB`dwt_361`361`361`2953`yes`361`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 125`HB`dwt_419`419`419`3563`yes`419`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 126`HB`dwt_492`492`492`3156`yes`492`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 127`HB`dwt_503`503`503`6027`yes`503`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 128`HB`dwt_512`512`512`3502`yes`512`32`32`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 129`HB`dwt_59`59`59`267`yes`59`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 130`HB`dwt_592`592`592`5104`yes`592`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 131`HB`dwt_607`607`607`5131`yes`607`4`4`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 132`HB`dwt_66`66`66`320`yes`66`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 133`HB`dwt_72`72`72`222`yes`72`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 134`HB`dwt_758`758`758`5994`yes`758`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 135`HB`dwt_869`869`869`7285`yes`869`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 136`HB`dwt_87`87`87`541`yes`87`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 137`HB`dwt_878`878`878`7448`yes`878`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 138`HB`dwt_918`918`918`7384`yes`918`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 139`HB`dwt_992`992`992`16744`yes`992`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Everstine, D. Taylor`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 140`HB`eris1176`1176`1176`18552`yes`1176`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`A. Erisman`A. Curtis, I. Duff, J. Reid`1973`power network problem` | |
| 141`HB`fs_183_1`183`183`998`yes`183`37`37`71`42%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`2D/3D problem sequence`\nnext: HB/fs_183_3 first: HB/fs_183_1\n | |
| 142`HB`fs_183_3`183`183`1069`yes`183`30`30`0`42%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`subsequent 2D/3D problem`\nnext: HB/fs_183_4 first: HB/fs_183_1\n | |
| 143`HB`fs_183_4`183`183`1069`yes`183`30`30`0`42%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`subsequent 2D/3D problem`\nnext: HB/fs_183_6 first: HB/fs_183_1\n | |
| 144`HB`fs_183_6`183`183`1000`yes`183`37`37`69`42%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`subsequent 2D/3D problem`\nnext: - first: HB/fs_183_1\n | |
| 145`HB`fs_541_1`541`541`4282`yes`541`2`2`3`68%`0%`real`unsymmetric`no`no`A. Curtis`A. Curtis, I. Duff, J. Reid`1978`2D/3D problem sequence`\nnext: HB/fs_541_2 first: HB/fs_541_1\n | |
| 146`HB`fs_541_2`541`541`4282`yes`541`2`2`3`68%`0%`real`unsymmetric`no`no`A. Curtis`A. Curtis, I. Duff, J. Reid`1978`subsequent 2D/3D problem`\nnext: HB/fs_541_3 first: HB/fs_541_1\n | |
| 147`HB`fs_541_3`541`541`4282`yes`541`2`2`3`68%`0%`real`unsymmetric`no`no`A. Curtis`A. Curtis, I. Duff, J. Reid`1978`subsequent 2D/3D problem`\nnext: HB/fs_541_4 first: HB/fs_541_1\n | |
| 148`HB`fs_541_4`541`541`4273`yes`541`2`2`12`68%`0%`real`unsymmetric`no`no`A. Curtis`A. Curtis, I. Duff, J. Reid`1978`subsequent 2D/3D problem`\nnext: - first: HB/fs_541_1\n | |
| 149`HB`fs_680_1`680`680`2184`yes`680`446`446`462`51%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`2D/3D problem sequence`\nnext: HB/fs_680_2 first: HB/fs_680_1\n | |
| 150`HB`fs_680_2`680`680`2424`yes`680`446`446`222`51%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`subsequent 2D/3D problem`\nnext: HB/fs_680_3 first: HB/fs_680_1\n | |
| 151`HB`fs_680_3`680`680`2471`yes`680`446`446`175`51%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`subsequent 2D/3D problem`\nnext: - first: HB/fs_680_1\n | |
| 152`HB`fs_760_1`760`760`5739`yes`760`17`17`237`65%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`2D/3D problem sequence`\nnext: HB/fs_760_2 first: HB/fs_760_1\n | |
| 153`HB`fs_760_2`760`760`5739`yes`760`17`17`237`65%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`subsequent 2D/3D problem`\nnext: HB/fs_760_3 first: HB/fs_760_1\n | |
| 154`HB`fs_760_3`760`760`5816`yes`760`17`17`160`65%`0%`real`unsymmetric`no`no`A. Curtis`I. Duff, R. Grimes, J. Lewis`1983`subsequent 2D/3D problem`\nnext: - first: HB/fs_760_1\n | |
| 155`HB`gemat1`4929`10595`46591`yes`4929`1`1`778`0%`0%`real`rectangular`no`no`R. Burchett`I. Duff, R. Grimes, J. Lewis`1984`power network problem` | |
| 156`HB`gemat11`4929`4929`33108`yes`4929`352`2`77`0%`0%`real`unsymmetric`no`no`R. Burchett`I. Duff, R. Grimes, J. Lewis`1984`power network problem sequence`\nnext: HB/gemat12 first: HB/gemat11\n | |
| 157`HB`gemat12`4929`4929`33044`yes`4929`378`2`67`0%`0%`real`unsymmetric`no`no`R. Burchett`I. Duff, R. Grimes, J. Lewis`1984`subsequent power network problem`\nnext: - first: HB/gemat11\n | |
| 158`HB`gent113`113`113`655`yes`113`18`18`0`6%`6%`binary`unsymmetric`no`no`W. Gentleman`A. Curtis, I. Duff, J. Reid`1973`statistical/mathematical problem` | |
| 159`HB`gr_30_30`900`900`7744`yes`900`1`1`0`symmetric`symmetric`integer`symmetric`yes`yes`R. Grimes`I. Duff, R. Grimes, J. Lewis`1983`2D/3D problem` | |
| 160`HB`gre_1107`1107`1107`5664`unknown`unknown`unknown`1`0`0%`0%`real`unsymmetric`no`no`F. Cachard`I. Duff, R. Grimes, J. Lewis`1981`directed weighted graph` | |
| 161`HB`gre_115`115`115`421`unknown`unknown`unknown`1`0`25%`0%`real`unsymmetric`no`no`F. Cachard`I. Duff, R. Grimes, J. Lewis`1981`directed weighted graph` | |
| 162`HB`gre_185`185`185`975`unknown`unknown`unknown`1`30`41%`0%`real`unsymmetric`no`no`F. Cachard`I. Duff, R. Grimes, J. Lewis`1981`directed weighted graph` | |
| 163`HB`gre_216a`216`216`812`unknown`unknown`unknown`1`64`0%`0%`real`unsymmetric`no`no`F. Cachard`I. Duff, R. Grimes, J. Lewis`1981`directed weighted graph` | |
| 164`HB`gre_216b`216`216`812`unknown`unknown`unknown`1`64`0%`0%`real`unsymmetric`no`no`F. Cachard`I. Duff, R. Grimes, J. Lewis`1981`directed weighted graph` | |
| 165`HB`gre_343`343`343`1310`unknown`unknown`unknown`1`125`0%`0%`real`unsymmetric`no`no`F. Cachard`I. Duff, R. Grimes, J. Lewis`1981`directed weighted graph` | |
| 166`HB`gre_512`512`512`1976`unknown`unknown`unknown`1`216`0%`0%`real`unsymmetric`no`no`F. Cachard`I. Duff, R. Grimes, J. Lewis`1981`directed weighted graph` | |
| 167`HB`hor_131`434`434`4182`unknown`unknown`unknown`1`528`symmetric`37%`real`unsymmetric`no`no`R. Hornby`I. Duff, R. Grimes, J. Lewis`1983`directed weighted graph` | |
| 168`HB`ibm32`32`32`126`unknown`unknown`unknown`1`0`9%`9%`binary`unsymmetric`no`no`IBM`A. Curtis, I. Duff, J. Reid`1971`directed graph` | |
| 169`HB`illc1033`1033`320`4719`yes`320`15`1`13`0%`0%`real`rectangular`no`no`M. Saunders`I. Duff, R. Grimes, J. Lewis`1979`least squares problem` | |
| 170`HB`illc1850`1850`712`8636`yes`712`10`1`122`0%`0%`real`rectangular`no`no`M. Saunders`I. Duff, R. Grimes, J. Lewis`1979`least squares problem` | |
| 171`HB`impcol_a`207`207`572`yes`207`164`4`0`2%`1%`real`unsymmetric`no`no`D. Bogle`I. Duff, R. Grimes, J. Lewis`1982`chemical process simulation problem` | |
| 172`HB`impcol_b`59`59`271`yes`59`19`1`41`9%`0%`real`unsymmetric`no`no`D. Bogle`I. Duff, R. Grimes, J. Lewis`1982`chemical process simulation problem` | |
| 173`HB`impcol_c`137`137`400`yes`137`115`18`11`4%`1%`real`unsymmetric`no`no`D. Bogle`I. Duff, R. Grimes, J. Lewis`1982`chemical process simulation problem` | |
| 174`HB`impcol_d`425`425`1255`yes`425`321`3`84`6%`2%`real`unsymmetric`no`no`D. Bogle`I. Duff, R. Grimes, J. Lewis`1982`chemical process simulation problem` | |
| 175`HB`impcol_e`225`225`1303`yes`225`151`17`5`10%`0%`real`unsymmetric`no`no`D. Bogle`I. Duff, R. Grimes, J. Lewis`1982`chemical process simulation problem` | |
| 176`HB`jagmesh1`936`936`6264`yes`936`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 177`HB`jagmesh2`1009`1009`6865`yes`1009`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 178`HB`jagmesh3`1089`1089`7361`yes`1089`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 179`HB`jagmesh4`1440`1440`9504`yes`1440`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 180`HB`jagmesh5`1180`1180`7750`yes`1180`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 181`HB`jagmesh6`1377`1377`8993`yes`1377`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 182`HB`jagmesh7`1138`1138`7450`yes`1138`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 183`HB`jagmesh8`1141`1141`7465`yes`1141`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 184`HB`jagmesh9`1349`1349`9101`yes`1349`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`2D/3D problem` | |
| 185`HB`jgl009`9`9`50`yes`9`1`1`0`48%`48%`binary`unsymmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1983`counter-example problem` | |
| 186`HB`jgl011`11`11`76`yes`11`1`1`0`52%`52%`binary`unsymmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1983`counter-example problem` | |
| 187`HB`jpwh_991`991`991`6027`yes`991`146`146`0`94%`94%`integer`unsymmetric`no`no`J. Whelan`I. Duff, R. Grimes, J. Lewis`1978`semiconductor device problem` | |
| 188`HB`lns_131`131`131`536`yes`131`65`48`0`70%`2%`real`unsymmetric`no`no`I. Jones`I. Duff, R. Grimes, J. Lewis`1982`computational fluid dynamics problem` | |
| 189`HB`lns_3937`3937`3937`25407`yes`3937`351`290`0`85%`0%`real`unsymmetric`no`no`I. Jones`I. Duff, R. Grimes, J. Lewis`1982`computational fluid dynamics problem` | |
| 190`HB`lns_511`511`511`2796`yes`511`135`98`0`80%`2%`real`unsymmetric`no`no`I. Jones`I. Duff, R. Grimes, J. Lewis`1982`computational fluid dynamics problem` | |
| 191`HB`lnsp3937`3937`3937`25407`yes`3937`351`290`0`85%`0%`real`unsymmetric`no`no`I. Jones`I. Duff, R. Grimes, J. Lewis`1982`computational fluid dynamics problem` | |
| 192`HB`lnsp_131`131`131`536`yes`131`65`48`0`70%`2%`real`unsymmetric`no`no`I. Jones`I. Duff, R. Grimes, J. Lewis`1982`computational fluid dynamics problem` | |
| 193`HB`lnsp_511`511`511`2796`yes`511`135`98`0`80%`2%`real`unsymmetric`no`no`I. Jones`I. Duff, R. Grimes, J. Lewis`1982`computational fluid dynamics problem` | |
| 194`HB`lshp1009`1009`1009`6865`yes`1009`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`duplicate thermal problem`\nduplicate of HB/jagmesh2\n | |
| 195`HB`lshp1270`1270`1270`8668`yes`1270`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 196`HB`lshp1561`1561`1561`10681`yes`1561`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 197`HB`lshp1882`1882`1882`12904`yes`1882`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 198`HB`lshp2233`2233`2233`15337`yes`2233`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 199`HB`lshp2614`2614`2614`17980`yes`2614`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 200`HB`lshp3025`3025`3025`20833`yes`3025`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 201`HB`lshp3466`3466`3466`23896`yes`3466`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 202`HB`lshp_265`265`265`1753`yes`265`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 203`HB`lshp_406`406`406`2716`yes`406`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 204`HB`lshp_577`577`577`3889`yes`577`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 205`HB`lshp_778`778`778`5272`yes`778`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. George`I. Duff, R. Grimes, J. Lewis`1978`thermal problem` | |
| 206`HB`lund_a`147`147`2449`yes`147`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`T. Johansson`A. Curtis, I. Duff, J. Reid`1974`structural problem` | |
| 207`HB`lund_b`147`147`2441`yes`147`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`T. Johansson`A. Curtis, I. Duff, J. Reid`1974`structural problem` | |
| 208`HB`mahindas`1258`1258`7682`yes`1258`670`1`0`2%`0%`real`unsymmetric`no`no`K. Pearson`I. Duff, R. Grimes, J. Lewis`1984`economic problem` | |
| 209`HB`mbeacxc`496`496`49920`no`448`10`54`0`32%`0%`real`unsymmetric`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 210`HB`mbeaflw`496`496`49920`no`448`10`54`0`32%`0%`real`unsymmetric`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 211`HB`mbeause`496`496`41063`no`447`28`66`0`22%`1%`real`unsymmetric`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 212`HB`mcca`180`180`2659`yes`180`6`6`0`64%`0%`real`unsymmetric`no`no`M. Carlsson`I. Duff, R. Grimes, J. Lewis`1985`2D/3D problem` | |
| 213`HB`mcfe`765`765`24382`yes`765`5`5`0`70%`0%`real`unsymmetric`no`no`M. Carlsson`I. Duff, R. Grimes, J. Lewis`1985`2D/3D problem` | |
| 214`HB`nnc1374`1374`1374`8588`yes`1374`57`1`18`82%`59%`real`unsymmetric`no`no`National Nuclear Corp.`I. Duff, R. Grimes, J. Lewis`1982`2D/3D problem` | |
| 215`HB`nnc261`261`261`1500`yes`261`29`1`0`82%`61%`real`unsymmetric`no`no`National Nuclear Corp.`I. Duff, R. Grimes, J. Lewis`1982`2D/3D problem` | |
| 216`HB`nnc666`666`666`4032`yes`666`41`1`12`82%`59%`real`unsymmetric`no`no`National Nuclear Corp.`I. Duff, R. Grimes, J. Lewis`1982`2D/3D problem` | |
| 217`HB`nos1`237`237`1017`yes`237`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`H. Simon`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 218`HB`nos2`957`957`4137`yes`957`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`H. Simon`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 219`HB`nos3`960`960`15844`yes`960`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`H. Simon`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 220`HB`nos4`100`100`594`yes`100`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`H. Simon`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 221`HB`nos5`468`468`5172`yes`468`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`H. Simon`I. Duff, R. Grimes, J. Lewis`1982`structural problem` | |
| 222`HB`nos6`675`675`3255`yes`675`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`H. Simon`I. Duff, R. Grimes, J. Lewis`1982`2D/3D problem` | |
| 223`HB`nos7`729`729`4617`yes`729`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`H. Simon`I. Duff, R. Grimes, J. Lewis`1982`2D/3D problem` | |
| 224`HB`orani678`2529`2529`90158`yes`2529`700`1`0`7%`0%`real`unsymmetric`no`no`K. Pearson`I. Duff, R. Grimes, J. Lewis`1984`economic problem` | |
| 225`HB`orsirr_1`1030`1030`6858`yes`1030`1`1`0`symmetric`41%`real`unsymmetric`no`no`R. Grimes`I. Duff, R. Grimes, J. Lewis`1984`computational fluid dynamics problem` | |
| 226`HB`orsirr_2`886`886`5970`yes`886`1`1`0`symmetric`41%`real`unsymmetric`no`no`R. Grimes`I. Duff, R. Grimes, J. Lewis`1984`computational fluid dynamics problem` | |
| 227`HB`orsreg_1`2205`2205`14133`yes`2205`1`1`0`symmetric`41%`real`unsymmetric`no`no`R. Grimes`I. Duff, R. Grimes, J. Lewis`1984`computational fluid dynamics problem` | |
| 228`HB`plat1919`1919`1919`32399`yes`1919`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1975`2D/3D problem` | |
| 229`HB`plat362`362`362`5786`yes`362`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lewis`I. Duff, R. Grimes, J. Lewis`1975`2D/3D problem` | |
| 230`HB`plsk1919`1919`1919`9662`yes`1919`11`1`0`symmetric`0%`real`skew-symmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1975`2D/3D problem` | |
| 231`HB`plskz362`362`362`1760`yes`362`3`1`0`symmetric`0%`real`skew-symmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1975`2D/3D problem` | |
| 232`HB`pores_1`30`30`180`yes`30`1`1`0`63%`29%`real`unsymmetric`no`no`J. Appleyard`I. Duff, R. Grimes, J. Lewis`1980`computational fluid dynamics problem` | |
| 233`HB`pores_2`1224`1224`9613`yes`1224`1`1`0`61%`39%`real`unsymmetric`no`no`J. Appleyard`I. Duff, R. Grimes, J. Lewis`1980`computational fluid dynamics problem` | |
| 234`HB`pores_3`532`532`3474`yes`532`2`2`0`74%`31%`real`unsymmetric`no`no`J. Appleyard`I. Duff, R. Grimes, J. Lewis`1980`computational fluid dynamics problem` | |
| 235`HB`psmigr_1`3140`3140`543160`yes`3140`1`1`2`48%`1%`integer`unsymmetric`no`no`P. Slater`I. Duff, R. Grimes, J. Lewis`1983`economic problem` | |
| 236`HB`psmigr_2`3140`3140`540022`yes`3140`1`1`0`48%`0%`real`unsymmetric`no`no`P. Slater`I. Duff, R. Grimes, J. Lewis`1983`economic problem` | |
| 237`HB`psmigr_3`3140`3140`543160`yes`3140`1`1`2`48%`0%`real`unsymmetric`no`no`P. Slater`I. Duff, R. Grimes, J. Lewis`1983`economic problem` | |
| 238`HB`rgg010`10`10`76`yes`10`1`1`0`64%`64%`binary`unsymmetric`no`no`J. Lewis`I. Duff, R. Grimes, J. Lewis`1983`counter-example problem` | |
| 239`HB`saylr1`238`238`1128`yes`238`1`1`0`symmetric`65%`real`unsymmetric`no`no`R. Kendall, D. Peaceman, H. Stone, W. Watts`P. Saylor`1984`computational fluid dynamics problem` | |
| 240`HB`saylr3`1000`1000`3750`yes`1000`318`318`0`symmetric`symmetric`real`symmetric`no`no`R. Kendall, D. Peaceman, H. Stone, W. Watts`P. Saylor`1984`computational fluid dynamics problem` | |
| 241`HB`saylr4`3564`3564`22316`yes`3564`1`1`0`symmetric`symmetric`real`symmetric`no`no`R. Kendall, D. Peaceman, H. Stone, W. Watts`P. Saylor`1984`computational fluid dynamics problem` | |
| 242`HB`sherman1`1000`1000`3750`yes`1000`318`318`0`symmetric`symmetric`real`symmetric`no`no`A. Sherman`I. Duff, R. Grimes, J. Lewis`1984`computational fluid dynamics problem` | |
| 243`HB`sherman2`1080`1080`23094`yes`1080`211`211`0`67%`0%`real`unsymmetric`no`no`A. Sherman`I. Duff, R. Grimes, J. Lewis`1984`computational fluid dynamics problem` | |
| 244`HB`sherman3`5005`5005`20033`yes`5005`2111`2111`0`symmetric`45%`real`unsymmetric`no`no`A. Sherman`I. Duff, R. Grimes, J. Lewis`1984`computational fluid dynamics problem` | |
| 245`HB`sherman4`1104`1104`3786`yes`1104`559`559`0`symmetric`0%`real`unsymmetric`no`no`A. Sherman`I. Duff, R. Grimes, J. Lewis`1984`computational fluid dynamics problem` | |
| 246`HB`sherman5`3312`3312`20793`yes`3312`1675`1675`0`74%`15%`real`unsymmetric`no`no`A. Sherman`I. Duff, R. Grimes, J. Lewis`1984`computational fluid dynamics problem` | |
| 247`HB`shl_0`663`663`1687`yes`663`663`4`0`0%`0%`integer`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`optimization problem sequence`\nnext: HB/shl_200 first: HB/shl_0\n | |
| 248`HB`shl_200`663`663`1726`yes`663`663`4`0`0%`0%`integer`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/shl_400 first: HB/shl_0\n | |
| 249`HB`shl_400`663`663`1712`yes`663`663`2`0`0%`0%`integer`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: - first: HB/shl_0\n | |
| 250`HB`sstmodel`3345`3345`22749`yes`3345`616`616`0`symmetric`symmetric`binary`symmetric`yes`no`E. Meyer`I. Duff, R. Grimes, J. Lewis`1983`structural problem` | |
| 251`HB`steam1`240`240`2248`yes`240`1`1`1514`symmetric`27%`real`unsymmetric`no`no`R. Grimes`I. Duff, R. Grimes, J. Lewis`1983`computational fluid dynamics problem` | |
| 252`HB`steam2`600`600`5660`yes`600`151`151`8100`symmetric`19%`real`unsymmetric`no`no`R. Grimes`I. Duff, R. Grimes, J. Lewis`1983`computational fluid dynamics problem` | |
| 253`HB`steam3`80`80`314`yes`80`21`21`614`symmetric`32%`real`unsymmetric`no`no`R. Grimes`I. Duff, R. Grimes, J. Lewis`1983`computational fluid dynamics problem` | |
| 254`HB`str_0`363`363`2454`yes`363`363`2`0`0%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`optimization problem sequence`\nnext: HB/str_200 first: HB/str_0\n | |
| 255`HB`str_200`363`363`3068`yes`363`234`2`0`1%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/str_400 first: HB/str_0\n | |
| 256`HB`str_400`363`363`3157`yes`363`203`2`0`2%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: HB/str_600 first: HB/str_0\n | |
| 257`HB`str_600`363`363`3279`yes`363`142`2`0`2%`0%`real`unsymmetric`no`no`M. Saunders`A. Curtis, I. Duff, J. Reid`1978`subsequent optimization problem`\nnext: - first: HB/str_0\n | |
| 258`HB`watt_1`1856`1856`11360`yes`1856`129`129`0`99%`99%`real`unsymmetric`no`no`J. Somerville`I. Duff, R. Grimes, J. Lewis`1983`computational fluid dynamics problem` | |
| 259`HB`watt_2`1856`1856`11550`yes`1856`65`65`0`98%`97%`real`unsymmetric`no`no`J. Somerville`I. Duff, R. Grimes, J. Lewis`1983`computational fluid dynamics problem` | |
| 260`HB`well1033`1033`320`4732`yes`320`15`1`0`0%`0%`real`rectangular`no`no`M. Saunders`I. Duff, R. Grimes, J. Lewis`1979`least squares problem` | |
| 261`HB`well1850`1850`712`8755`yes`712`10`1`3`0%`0%`real`rectangular`no`no`M. Saunders`I. Duff, R. Grimes, J. Lewis`1979`least squares problem` | |
| 262`HB`west0067`67`67`294`yes`67`2`1`0`3%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 263`HB`west0132`132`132`413`yes`132`56`2`1`2%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 264`HB`west0156`156`156`362`yes`156`134`1`9`0%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 265`HB`west0167`167`167`506`yes`167`91`1`1`2%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 266`HB`west0381`381`381`2134`yes`381`6`1`23`1%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 267`HB`west0479`479`479`1888`yes`479`166`2`22`1%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 268`HB`west0497`497`497`1721`yes`497`294`2`6`1%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 269`HB`west0655`655`655`2808`yes`655`198`2`46`1%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 270`HB`west0989`989`989`3518`yes`989`270`2`19`2%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 271`HB`west1505`1505`1505`5414`yes`1505`405`1`31`0%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 272`HB`west2021`2021`2021`7310`yes`2021`522`1`43`0%`0%`real`unsymmetric`no`no`A. Westerberg`I. Duff, R. Grimes, J. Lewis`1983`chemical process simulation problem` | |
| 273`HB`will199`199`199`701`yes`199`10`1`0`6%`6%`binary`unsymmetric`no`no`R. Willoughby`I. Duff, R. Grimes, J. Lewis`1979`structural problem` | |
| 274`HB`will57`57`57`281`yes`57`1`1`0`87%`87%`binary`unsymmetric`no`no`R. Willoughby`I. Duff, R. Grimes, J. Lewis`1970`semiconductor device problem` | |
| 275`HB`wm1`207`277`2909`yes`207`50`29`0`0%`0%`real`rectangular`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 276`HB`wm2`207`260`2942`yes`207`36`4`0`0%`0%`real`rectangular`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 277`HB`wm3`207`260`2948`yes`207`28`4`0`0%`0%`real`rectangular`no`no`D. Szyld`I. Duff, R. Grimes, J. Lewis`1982`economic problem` | |
| 278`HB`young1c`841`841`4089`yes`841`1`1`0`symmetric`85%`complex`unsymmetric`no`no`D. Young`I. Duff, R. Grimes, J. Lewis`1984`acoustics problem`\nThe YOUNG*C matrices originally appeared in the Harwell/Boeing \ncollection as type CSA (complex symmetric). However, both upper \nand lower triangular parts are present in the original files \n(an invalid specification; only the lower part can be present \nin the file). If the entries in the upper triangular part are \nconsidered as part of the matrix, the matrices become unsymmetric. \nThe matrices have been corrected in the UF Sparse Matrix Collection\nby changing their type to CUA so that the entries in the original \nfiles are not ignored. In addition, the YOUNG3C matrix has a zero \nimaginary part, and thus appears here as a real matrix. \n | |
| 279`HB`young2c`841`841`4089`yes`841`1`1`0`symmetric`85%`complex`unsymmetric`no`no`D. Young`I. Duff, R. Grimes, J. Lewis`1984`duplicate acoustics problem`\nduplicate of HB/young1c\n | |
| 280`HB`young3c`841`841`3988`yes`841`1`1`0`94%`81%`real`unsymmetric`no`no`D. Young`I. Duff, R. Grimes, J. Lewis`1984`acoustics problem`\nThe YOUNG*C matrices originally appeared in the Harwell/Boeing \ncollection as type CSA (complex symmetric). However, both upper \nand lower triangular parts are present in the original files \n(an invalid specification; only the lower part can be present \nin the file). If the entries in the upper triangular part are \nconsidered as part of the matrix, the matrices become unsymmetric. \nThe matrices have been corrected in the UF Sparse Matrix Collection\nby changing their type to CUA so that the entries in the original \nfiles are not ignored. In addition, the YOUNG3C matrix has a zero \nimaginary part, and thus appears here as a real matrix. \n | |
| 281`HB`young4c`841`841`4089`yes`841`1`1`0`symmetric`80%`complex`unsymmetric`no`no`D. Young`I. Duff, R. Grimes, J. Lewis`1984`acoustics problem`\nThe YOUNG*C matrices originally appeared in the Harwell/Boeing \ncollection as type CSA (complex symmetric). However, both upper \nand lower triangular parts are present in the original files \n(an invalid specification; only the lower part can be present \nin the file). If the entries in the upper triangular part are \nconsidered as part of the matrix, the matrices become unsymmetric. \nThe matrices have been corrected in the UF Sparse Matrix Collection\nby changing their type to CUA so that the entries in the original \nfiles are not ignored. In addition, the YOUNG3C matrix has a zero \nimaginary part, and thus appears here as a real matrix. \n | |
| 282`HB`zenios`2873`2873`1314`no`266`84`2650`25877`symmetric`symmetric`real`symmetric`no`no`S. Zenios`I. Duff, R. Grimes, J. Lewis`1985`optimization problem` | |
| 283`ATandT`onetone1`36057`36057`335552`yes`36057`3843`203`5536`7%`4%`real`unsymmetric`no`no`R. Melville, D. Long`T. Davis`2001`frequency-domain circuit simulation problem` | |
| 284`ATandT`onetone2`36057`36057`222596`yes`36057`3843`203`5032`11%`7%`real`unsymmetric`no`no`R. Melville, D. Long`T. Davis`2001`frequency-domain circuit simulation problem` | |
| 285`ATandT`pre2`659033`659033`5834044`yes`659033`29282`391`125238`33%`7%`real`unsymmetric`no`no`R. Melville, D. Long`T. Davis`2001`frequency-domain circuit simulation problem` | |
| 286`ATandT`twotone`120750`120750`1206265`yes`120750`13135`5`17959`24%`11%`real`unsymmetric`no`no`R. Melville, D. Long`T. Davis`2001`frequency-domain circuit simulation problem` | |
| 287`Averous`epb0`1794`1794`7764`yes`1794`1`1`0`50%`0%`real`unsymmetric`no`no`D. Averous`T. Davis`1998`thermal problem` | |
| 288`Averous`epb1`14734`14734`95053`yes`14734`1`1`0`73%`0%`real`unsymmetric`no`no`D. Averous`T. Davis`1998`thermal problem` | |
| 289`Averous`epb2`25228`25228`175027`yes`25228`1`1`0`67%`0%`real`unsymmetric`no`no`D. Averous`T. Davis`1998`thermal problem` | |
| 290`Averous`epb3`84617`84617`463625`yes`84617`1`1`0`67%`3%`real`unsymmetric`no`no`D. Averous`T. Davis`1998`thermal problem` | |
| 291`Bai`af23560`23560`23560`460598`yes`23560`1`1`23658`100%`0%`real`unsymmetric`no`no`A. Mahajan`Z. Bai, D. Day, J. Demmel, J. Dongarra`1991`computational fluid dynamics problem` | |
| 292`Bai`bfwa398`398`398`3678`yes`398`2`2`0`99%`94%`real`unsymmetric`no`no`B. Schultz, S. Gedney`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 293`Bai`bfwa62`62`62`450`yes`62`2`2`0`97%`81%`real`unsymmetric`no`no`B. Schultz, S. Gedney`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 294`Bai`bfwa782`782`782`7514`yes`782`2`2`0`99%`96%`real`unsymmetric`no`no`B. Schultz, S. Gedney`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 295`Bai`bfwb398`398`398`2910`yes`398`2`2`0`symmetric`symmetric`real`symmetric`no`no`B. Schultz, S. Gedney`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 296`Bai`bfwb62`62`62`342`yes`62`2`2`0`symmetric`symmetric`real`symmetric`no`no`B. Schultz, S. Gedney`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 297`Bai`bfwb782`782`782`5982`yes`782`2`2`0`symmetric`symmetric`real`symmetric`no`no`B. Schultz, S. Gedney`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 298`Bai`bwm200`200`200`796`yes`200`1`1`0`symmetric`66%`real`unsymmetric`no`no`Y. Saad`Z. Bai, D. Day, J. Demmel, J. Dongarra`1992`chemical process simulation problem` | |
| 299`Bai`bwm2000`2000`2000`7996`yes`2000`1`1`0`symmetric`67%`real`unsymmetric`no`no`Y. Saad`Z. Bai, D. Day, J. Demmel, J. Dongarra`1992`chemical process simulation problem` | |
| 300`Bai`cdde1`961`961`4681`yes`961`1`1`0`symmetric`0%`real`unsymmetric`no`no`author unknown`Z. Bai, D. Day, J. Demmel, J. Dongarra`1992`computational fluid dynamics problem sequence`\nnext: Bai/cdde2 first: Bai/cdde1\n | |
| 301`Bai`cdde2`961`961`4681`yes`961`1`1`0`symmetric`0%`real`unsymmetric`no`no`author unknown`Z. Bai, D. Day, J. Demmel, J. Dongarra`1992`subsequent computational fluid dynamics problem`\nnext: Bai/cdde3 first: Bai/cdde1\n | |
| 302`Bai`cdde3`961`961`4681`yes`961`1`1`0`symmetric`0%`real`unsymmetric`no`no`author unknown`Z. Bai, D. Day, J. Demmel, J. Dongarra`1992`subsequent computational fluid dynamics problem`\nnext: Bai/cdde4 first: Bai/cdde1\n | |
| 303`Bai`cdde4`961`961`4681`yes`961`1`1`0`symmetric`0%`real`unsymmetric`no`no`author unknown`Z. Bai, D. Day, J. Demmel, J. Dongarra`1992`subsequent computational fluid dynamics problem`\nnext: Bai/cdde5 first: Bai/cdde1\n | |
| 304`Bai`cdde5`961`961`4681`yes`961`1`1`0`symmetric`0%`real`unsymmetric`no`no`author unknown`Z. Bai, D. Day, J. Demmel, J. Dongarra`1992`subsequent computational fluid dynamics problem`\nnext: Bai/cdde6 first: Bai/cdde1\n | |
| 305`Bai`cdde6`961`961`4681`yes`961`1`1`0`symmetric`0%`real`unsymmetric`no`no`author unknown`Z. Bai, D. Day, J. Demmel, J. Dongarra`1992`subsequent computational fluid dynamics problem`\nnext: - first: Bai/cdde1\n | |
| 306`Bai`ck104`104`104`992`yes`104`2`2`0`symmetric`0%`real`unsymmetric`no`no`J. Cullum`Z. Bai, D. Day, J. Demmel, J. Dongarra`1986`2D/3D problem` | |
| 307`Bai`ck400`400`400`2860`yes`400`2`2`0`99%`0%`real`unsymmetric`no`no`J. Cullum`Z. Bai, D. Day, J. Demmel, J. Dongarra`1986`2D/3D problem` | |
| 308`Bai`ck656`656`656`3884`yes`656`2`2`0`99%`0%`real`unsymmetric`no`no`J. Cullum`Z. Bai, D. Day, J. Demmel, J. Dongarra`1986`2D/3D problem` | |
| 309`Bai`dw1024`2048`2048`10114`yes`2048`1`1`0`98%`95%`real`unsymmetric`no`no`H. Dong`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`electromagnetics problem` | |
| 310`Bai`dw256A`512`512`2480`yes`512`1`1`0`98%`91%`real`unsymmetric`no`no`H. Dong`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`electromagnetics problem` | |
| 311`Bai`dw256B`512`512`2500`yes`512`1`1`0`97%`88%`real`unsymmetric`no`no`H. Dong`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`electromagnetics problem` | |
| 312`Bai`dw4096`8192`8192`41746`yes`8192`1`1`0`96%`92%`real`unsymmetric`no`no`H. Dong`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`electromagnetics problem` | |
| 313`Bai`lop163`163`163`935`yes`163`1`1`0`45%`0%`real`unsymmetric`no`no`W. Stewart`Z. Bai, D. Day, J. Demmel, J. Dongarra`1978`statistical/mathematical problem` | |
| 314`Bai`mhda416`416`416`8562`yes`416`8`8`0`77%`27%`real`unsymmetric`no`no`A. Booten, M. Kooper, H. van der Vorst, S. Poedts, J. Goedbloed`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 315`Bai`mhdb416`416`416`2312`yes`416`14`14`0`symmetric`symmetric`real`symmetric`yes`yes`A. Booten, M. Kooper, H. van der Vorst, S. Poedts, J. Goedbloed`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 316`Bai`odepa400`400`400`1201`yes`400`1`1`0`100%`99%`real`unsymmetric`no`no`G. Stewart`Z. Bai, D. Day, J. Demmel, J. Dongarra`1978`2D/3D problem` | |
| 317`Bai`odepb400`400`400`399`no`399`401`400`0`symmetric`symmetric`real`symmetric`no`no`G. Stewart`Z. Bai, D. Day, J. Demmel, J. Dongarra`1978`2D/3D problem` | |
| 318`Bai`olm100`100`100`396`yes`100`1`1`0`67%`33%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 319`Bai`olm1000`1000`1000`3996`yes`1000`1`1`0`67%`33%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 320`Bai`olm2000`2000`2000`7996`yes`2000`1`1`0`67%`33%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 321`Bai`olm500`500`500`1996`yes`500`1`1`0`67%`33%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 322`Bai`olm5000`5000`5000`19996`yes`5000`1`1`0`67%`33%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 323`Bai`pde225`225`225`1065`yes`225`1`1`0`symmetric`50%`real`unsymmetric`no`no`H. Elman`Z. Bai, D. Day, J. Demmel, J. Dongarra`1982`2D/3D problem` | |
| 324`Bai`pde2961`2961`2961`14585`yes`2961`1`1`0`symmetric`50%`real`unsymmetric`no`no`H. Elman`Z. Bai, D. Day, J. Demmel, J. Dongarra`1982`2D/3D problem` | |
| 325`Bai`pde900`900`900`4380`yes`900`1`1`0`symmetric`50%`real`unsymmetric`no`no`H. Elman`Z. Bai, D. Day, J. Demmel, J. Dongarra`1982`2D/3D problem` | |
| 326`Bai`qc2534`2534`2534`463360`yes`2534`1`1`0`symmetric`0%`complex`symmetric`no`no`S. Chu`Z. Bai, D. Day, J. Demmel, J. Dongarra`1991`electromagnetics problem` | |
| 327`Bai`qc324`324`324`26730`yes`324`1`1`0`symmetric`0%`complex`symmetric`no`no`S. Chu`Z. Bai, D. Day, J. Demmel, J. Dongarra`1991`electromagnetics problem` | |
| 328`Bai`qh882`882`882`3354`yes`882`43`1`0`93%`0%`real`unsymmetric`no`no`D. Ndereyimana`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`power network problem` | |
| 329`Bai`rbsa480`480`480`17088`yes`480`1`1`0`7%`0%`integer`unsymmetric`no`no`H. Ren`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`robotics problem` | |
| 330`Bai`rbsb480`480`480`17088`yes`480`1`1`0`8%`0%`integer`unsymmetric`no`no`H. Ren`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`robotics problem` | |
| 331`Bai`rdb2048`2048`2048`12032`yes`2048`1`1`0`symmetric`79%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem`\nThis matrix (Bai/rdb2048) is the same as the original NEP RDB2048L\nmatrix (as of Nov 2006). Either the name changed since 1996 and \nthe L was added in the NEP collection, or the L was dropped when \nthe matrix as added to the UF Sparse Matrix Collection in 1996. \nThe name cannot be corrected here without disrupting the UF Sparse\nMatrix Collection. To make matters worse, there is now a matrix \nin the NEP collection with the name RDB2048, as of Nov 2006. The \nNEP RDB2048 matrix was added to this collection in Nov 2006, as \nBai/rdb2038_noL matrix. \n | |
| 332`Bai`rdb5000`5000`5000`29600`yes`5000`1`1`0`symmetric`80%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 333`Bai`rdb968`968`968`5632`yes`968`1`1`0`symmetric`79%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 334`Bai`rw136`136`136`479`yes`136`6`1`0`44%`3%`real`unsymmetric`no`no`G. Stewart`Z. Bai, D. Day, J. Demmel, J. Dongarra`1978`statistical/mathematical problem` | |
| 335`Bai`rw496`496`496`1859`yes`496`6`1`0`47%`0%`real`unsymmetric`no`no`G. Stewart`Z. Bai, D. Day, J. Demmel, J. Dongarra`1978`statistical/mathematical problem` | |
| 336`Bai`rw5151`5151`5151`20199`yes`5151`6`1`0`49%`0%`real`unsymmetric`no`no`G. Stewart`Z. Bai, D. Day, J. Demmel, J. Dongarra`1978`statistical/mathematical problem` | |
| 337`Bai`tub100`100`100`396`yes`100`1`1`0`symmetric`0%`real`unsymmetric`no`no`K. Meerbergen, D. Roose`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 338`Bai`tub1000`1000`1000`3996`yes`1000`1`1`0`symmetric`0%`real`unsymmetric`no`no`K. Meerbergen, D. Roose`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 339`Boeing`bcsstk34`588`588`21418`yes`588`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 340`Boeing`bcsstk35`30237`30237`1450163`yes`30237`1`1`0`symmetric`symmetric`real`symmetric`yes`no`R. Grimes`T. Davis`1995`structural problem` | |
| 341`Boeing`bcsstk36`23052`23052`1143140`yes`23052`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 342`Boeing`bcsstk37`25503`25503`1140977`yes`25503`1`1`0`symmetric`symmetric`real`symmetric`yes`no`R. Grimes`T. Davis`1995`structural problem` | |
| 343`Boeing`bcsstk38`8032`8032`355460`yes`8032`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 344`Boeing`bcsstm34`588`588`24270`yes`588`1`1`0`symmetric`symmetric`real`symmetric`no`no`R. Grimes`T. Davis`1995`structural problem` | |
| 345`Boeing`bcsstm35`30237`30237`20619`no`15803`14796`29228`0`symmetric`symmetric`real`symmetric`no`no`R. Grimes`T. Davis`1995`structural problem` | |
| 346`Boeing`bcsstm36`23052`23052`320606`no`12172`3`10881`0`symmetric`symmetric`real`symmetric`no`no`R. Grimes`T. Davis`1995`structural problem` | |
| 347`Boeing`bcsstm37`25503`25503`15525`no`14005`13572`25068`0`symmetric`symmetric`real`symmetric`no`no`R. Grimes`T. Davis`1995`structural problem` | |
| 348`Boeing`bcsstm38`8032`8032`10485`no`5199`3825`6656`0`symmetric`symmetric`real`symmetric`no`no`R. Grimes`T. Davis`1995`structural problem` | |
| 349`Boeing`bcsstm39`46772`46772`46772`yes`46772`46772`46772`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 350`Boeing`crystk01`4875`4875`315891`yes`4875`1`1`0`symmetric`symmetric`real`symmetric`yes`no`R. Grimes`T. Davis`1995`materials problem` | |
| 351`Boeing`crystk02`13965`13965`968583`yes`13965`1`1`0`symmetric`symmetric`real`symmetric`yes`no`R. Grimes`T. Davis`1995`materials problem` | |
| 352`Boeing`crystk03`24696`24696`1751178`yes`24696`1`1`0`symmetric`symmetric`real`symmetric`yes`no`R. Grimes`T. Davis`1995`materials problem` | |
| 353`Boeing`crystm01`4875`4875`105339`yes`4875`3`3`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`materials problem` | |
| 354`Boeing`crystm02`13965`13965`322905`yes`13965`3`3`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`materials problem` | |
| 355`Boeing`crystm03`24696`24696`583770`yes`24696`3`3`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`materials problem` | |
| 356`Boeing`ct20stif`52329`52329`2600295`yes`52329`1`1`98168`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 357`Boeing`msc00726`726`726`34518`yes`726`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 358`Boeing`msc01050`1050`1050`26198`yes`1050`1`1`2958`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 359`Boeing`msc01440`1440`1440`44998`yes`1440`1`1`1272`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 360`Boeing`msc04515`4515`4515`97707`yes`4515`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 361`Boeing`msc10848`10848`10848`1229776`yes`10848`1`1`2`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 362`Boeing`msc23052`23052`23052`1142686`yes`23052`1`1`12128`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 363`Boeing`nasa1824`1824`1824`39208`yes`1824`1`1`0`symmetric`symmetric`real`symmetric`yes`no`R. Grimes`T. Davis`1995`duplicate structural problem`\nLet A1=Nasa/nasa1824 and A2=Boeing/nasa1824. A1 and A2 have the same \nnonzero pattern. A1 and A2 differ in value in only 386 entries out of\n39208, and only in 21 columns of the lower triangular part; \ntril(A(196:321196:216)) and the same rows of the upper triangular \npart. The magnitudes of the entries in A2 in this region of the \nmatrix are all tiny, and have only 9 digits if printed in base-10 \n(unlike the other entries, which have full precision). I suspect A2 \n(Boeing/nasa1824) is a corrupted version of A1 (Nasa/nasa1824). \n | |
| 364`Boeing`nasa2910`2910`2910`174296`yes`2910`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Grimes`T. Davis`1995`duplicate structural problem`\nBoeing/nasa2910 is the nonzero pattern of Nasa/nasa2910.\n | |
| 365`Boeing`nasa4704`4704`4704`104756`yes`4704`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Grimes`T. Davis`1995`duplicate structural problem`\nBoeing/nasa4704 is the nonzero pattern of Nasa/nasa4704.\n | |
| 366`Boeing`pcrystk02`13965`13965`968583`yes`13965`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Grimes`T. Davis`1995`duplicate materials problem`\nThis matrix is the nonzero pattern of Boeing/crystk02\n | |
| 367`Boeing`pcrystk03`24696`24696`1751178`yes`24696`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Grimes`T. Davis`1995`duplicate materials problem`\nThis matrix is the nonzero pattern of Boeing/crystk03\n | |
| 368`Boeing`pct20stif`52329`52329`2698463`yes`52329`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Grimes`T. Davis`1995`structural problem` | |
| 369`Boeing`pwtk`217918`217918`11524432`yes`217918`1`1`109992`symmetric`symmetric`real`symmetric`yes`yes`R. Grimes`T. Davis`1995`structural problem` | |
| 370`Bomhof`circuit_1`2624`2624`35823`yes`2624`60`6`0`100%`21%`real`unsymmetric`no`no`W. Bomhof`T. Davis`2000`circuit simulation problem` | |
| 371`Bomhof`circuit_2`4510`4510`21199`yes`4510`3249`3231`0`81%`42%`real`unsymmetric`no`no`W. Bomhof`T. Davis`2000`circuit simulation problem` | |
| 372`Bomhof`circuit_3`12127`12127`48137`yes`12127`4521`4399`0`77%`30%`real`unsymmetric`no`no`W. Bomhof`T. Davis`2000`circuit simulation problem` | |
| 373`Bomhof`circuit_4`80209`80209`307604`yes`80209`28005`27923`0`83%`36%`real`unsymmetric`no`no`W. Bomhof`T. Davis`2000`circuit simulation problem` | |
| 374`Bova`rma10`46835`46835`2329092`yes`46835`8`8`44909`symmetric`24%`real`unsymmetric`no`no`S. Bova`T. Davis`1997`computational fluid dynamics problem` | |
| 375`Brethour`coater1`1348`1348`19457`no`1331`85`262`0`59%`40%`real`unsymmetric`no`no`J. Brethour`T. Davis`1997`computational fluid dynamics problem` | |
| 376`Brethour`coater2`9540`9540`207308`no`9434`207`382`0`59%`13%`real`unsymmetric`no`no`J. Brethour`T. Davis`1997`computational fluid dynamics problem` | |
| 377`Brunetiere`thermal`3456`3456`66528`yes`3456`1`1`0`symmetric`7%`real`unsymmetric`no`no`N. Brunetiere`T. Davis`2000`thermal problem` | |
| 378`Cote`mplate`5962`5962`142190`yes`5962`1`1`0`symmetric`5%`complex`symmetric`no`no`A. Cote`T. Davis`1997`acoustics problem` | |
| 379`Cote`vibrobox`12328`12328`301700`yes`12328`1`1`41128`symmetric`symmetric`real`symmetric`yes`no`A. Cote`T. Davis`1997`acoustics problem` | |
| 380`DRIVCAV`cavity01`317`317`7280`yes`317`82`82`47`80%`52%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`computational fluid dynamics problem sequence`\nnext: DRIVCAV/cavity02 first: DRIVCAV/cavity01\n | |
| 381`DRIVCAV`cavity02`317`317`5923`yes`317`82`82`1404`80%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity03 first: DRIVCAV/cavity01 \npattern is the same as the transpose of DRIVCAV/cavity01\n | |
| 382`DRIVCAV`cavity03`317`317`7311`yes`317`82`82`16`80%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity04 first: DRIVCAV/cavity01\npattern is the same as DRIVCAV/cavity01 \n | |
| 383`DRIVCAV`cavity04`317`317`5923`yes`317`82`82`1404`80%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: - first: DRIVCAV/cavity01 \npattern is the same as the transpose of DRIVCAV/cavity01\n | |
| 384`DRIVCAV`cavity05`1182`1182`32632`yes`1182`162`162`115`90%`61%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`computational fluid dynamics problem sequence`\nnext: DRIVCAV/cavity06 first: DRIVCAV/cavity05\n | |
| 385`DRIVCAV`cavity06`1182`1182`29675`yes`1182`162`162`3072`90%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity07 first: DRIVCAV/cavity05 \npattern is the same as the transpose of DRIVCAV/cavity05\n | |
| 386`DRIVCAV`cavity07`1182`1182`32702`yes`1182`162`162`45`90%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity08 first: DRIVCAV/cavity05\npattern is the same as DRIVCAV/cavity05 \n | |
| 387`DRIVCAV`cavity08`1182`1182`29675`yes`1182`162`162`3072`90%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity09 first: DRIVCAV/cavity05 \npattern is the same as the transpose of DRIVCAV/cavity05\n | |
| 388`DRIVCAV`cavity09`1182`1182`32702`yes`1182`162`162`45`90%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: - first: DRIVCAV/cavity05 \npattern is the same as DRIVCAV/cavity05\n | |
| 389`DRIVCAV`cavity10`2597`2597`76171`yes`2597`242`242`196`94%`64%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`computational fluid dynamics problem sequence`\nnext: DRIVCAV/cavity11 first: DRIVCAV/cavity10\n | |
| 390`DRIVCAV`cavity11`2597`2597`71601`yes`2597`242`242`4766`94%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity12 first: DRIVCAV/cavity10 \npattern is the same as the transpose of DRIVCAV/cavity10\n | |
| 391`DRIVCAV`cavity12`2597`2597`76258`yes`2597`242`242`109`94%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity13 first: DRIVCAV/cavity10\npattern is the same as DRIVCAV/cavity10 \n | |
| 392`DRIVCAV`cavity13`2597`2597`71601`yes`2597`242`242`4766`94%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity14 first: DRIVCAV/cavity10 \npattern is the same as the transpose of DRIVCAV/cavity10\n | |
| 393`DRIVCAV`cavity14`2597`2597`76258`yes`2597`242`242`109`94%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity15 first: DRIVCAV/cavity10\npattern is the same as DRIVCAV/cavity10 \n | |
| 394`DRIVCAV`cavity15`2597`2597`71601`yes`2597`242`242`4766`94%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: - first: DRIVCAV/cavity10 \npattern is the same as the transpose of DRIVCAV/cavity10\n | |
| 395`DRIVCAV`cavity16`4562`4562`137887`yes`4562`322`322`300`95%`65%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`computational fluid dynamics problem sequence`\nnext: DRIVCAV/cavity17 first: DRIVCAV/cavity16\n | |
| 396`DRIVCAV`cavity17`4562`4562`131735`yes`4562`322`322`6452`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity18 first: DRIVCAV/cavity16 \npattern is the same as the transpose of DRIVCAV/cavity16\n | |
| 397`DRIVCAV`cavity18`4562`4562`138040`yes`4562`322`322`147`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity19 first: DRIVCAV/cavity16\npattern is the same as DRIVCAV/cavity16 \n | |
| 398`DRIVCAV`cavity19`4562`4562`131735`yes`4562`322`322`6452`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity20 first: DRIVCAV/cavity16 \npattern is the same as the transpose of DRIVCAV/cavity16\n | |
| 399`DRIVCAV`cavity20`4562`4562`138040`yes`4562`322`322`147`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity21 first: DRIVCAV/cavity16\npattern is the same as DRIVCAV/cavity16 \n | |
| 400`DRIVCAV`cavity21`4562`4562`131735`yes`4562`322`322`6452`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity22 first: DRIVCAV/cavity16 \npattern is the same as the transpose of DRIVCAV/cavity16\n | |
| 401`DRIVCAV`cavity22`4562`4562`138040`yes`4562`322`322`147`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity23 first: DRIVCAV/cavity16\npattern is the same as DRIVCAV/cavity16 \n | |
| 402`DRIVCAV`cavity23`4562`4562`131735`yes`4562`322`322`6452`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity24 first: DRIVCAV/cavity16 \npattern is the same as the transpose of DRIVCAV/cavity16\n | |
| 403`DRIVCAV`cavity24`4562`4562`138040`yes`4562`322`322`147`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity25 first: DRIVCAV/cavity16\npattern is the same as DRIVCAV/cavity16 \n | |
| 404`DRIVCAV`cavity25`4562`4562`131735`yes`4562`322`322`6452`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: DRIVCAV/cavity26 first: DRIVCAV/cavity16 \npattern is the same as the transpose of DRIVCAV/cavity16\n | |
| 405`DRIVCAV`cavity26`4562`4562`138040`yes`4562`322`322`147`95%`0%`real`unsymmetric`no`no`A. Chapman`A. Baggag, Y. Saad`1996`subsequent computational fluid dynamics problem`\nnext: - first: DRIVCAV/cavity16 \npattern is the same as DRIVCAV/cavity16\n | |
| 406`FIDAP`ex1`216`216`4317`yes`216`1`1`35`symmetric`100%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 407`FIDAP`ex10`2410`2410`54840`yes`2410`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 408`FIDAP`ex10hs`2548`2548`57308`yes`2548`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 409`FIDAP`ex11`16614`16614`1096948`yes`16614`1`1`0`symmetric`100%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 410`FIDAP`ex12`3973`3973`79077`yes`3973`1`1`1134`symmetric`symmetric`real`symmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 411`FIDAP`ex13`2568`2568`75628`yes`2568`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 412`FIDAP`ex14`3251`3251`65875`yes`3251`1`1`900`symmetric`symmetric`real`symmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 413`FIDAP`ex15`6867`6867`98671`yes`6867`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 414`FIDAP`ex18`5773`5773`71701`yes`5773`212`212`104`symmetric`50%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 415`FIDAP`ex19`12005`12005`259577`yes`12005`607`607`302`symmetric`43%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 416`FIDAP`ex2`441`441`26839`yes`441`1`1`0`symmetric`symmetric`real`symmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 417`FIDAP`ex20`2203`2203`67830`yes`2203`1`1`2151`symmetric`97%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 418`FIDAP`ex21`656`656`18964`yes`656`1`1`180`symmetric`94%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 419`FIDAP`ex22`839`839`22460`yes`839`1`1`255`symmetric`89%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 420`FIDAP`ex23`1409`1409`42760`yes`1409`1`1`943`symmetric`94%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 421`FIDAP`ex24`2283`2283`47901`yes`2283`1`1`836`symmetric`86%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 422`FIDAP`ex25`848`848`24369`yes`848`1`1`243`symmetric`98%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 423`FIDAP`ex26`2163`2163`74464`yes`2163`2`2`19569`symmetric`73%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 424`FIDAP`ex27`974`974`37652`yes`974`2`1`3130`symmetric`53%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 425`FIDAP`ex28`2603`2603`77031`yes`2603`1`1`750`symmetric`99%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 426`FIDAP`ex29`2870`2870`23754`yes`2870`180`180`0`symmetric`100%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 427`FIDAP`ex3`1821`1821`52685`yes`1821`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 428`FIDAP`ex31`3909`3909`91223`yes`3909`2`2`24134`symmetric`73%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 429`FIDAP`ex32`1159`1159`11047`yes`1159`2`2`296`symmetric`symmetric`real`symmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 430`FIDAP`ex33`1733`1733`22189`yes`1733`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 431`FIDAP`ex35`19716`19716`227872`yes`19716`342`342`336`symmetric`46%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 432`FIDAP`ex36`3079`3079`53099`yes`3079`3`3`744`symmetric`100%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 433`FIDAP`ex37`3565`3565`67591`yes`3565`1652`1652`0`symmetric`95%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 434`FIDAP`ex4`1601`1601`31849`yes`1601`1`1`450`symmetric`symmetric`real`symmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 435`FIDAP`ex40`7740`7740`456188`yes`7740`1`1`1824`symmetric`77%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 436`FIDAP`ex5`27`27`279`yes`27`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 437`FIDAP`ex6`1651`1651`49062`yes`1651`13`1`471`symmetric`98%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 438`FIDAP`ex7`1633`1633`46626`yes`1633`2`2`7917`symmetric`82%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 439`FIDAP`ex8`3096`3096`90841`yes`3096`2`2`15503`symmetric`43%`real`unsymmetric`no`no`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 440`FIDAP`ex9`3363`3363`99471`yes`3363`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Baggag, Y. Saad`A. Baggag, Y. Saad`1994`computational fluid dynamics problem` | |
| 441`Gaertner`big`13209`13209`91465`unknown`unknown`unknown`1`0`symmetric`100%`integer`unsymmetric`no`no`K. Gaertner`F. Grund`2001`directed weighted graph` | |
| 442`Gaertner`nopoly`10774`10774`70842`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`yes`no`K. Gaertner`F. Grund`2001`undirected weighted graph` | |
| 443`Gaertner`pesa`11738`11738`79566`unknown`unknown`unknown`1`0`symmetric`100%`integer`unsymmetric`no`no`K. Gaertner`F. Grund`2001`directed weighted graph` | |
| 444`Garon`garon1`3175`3175`84723`yes`3175`1`1`4204`symmetric`67%`real`unsymmetric`no`no`A. Garon`T. Davis`1996`computational fluid dynamics problem` | |
| 445`Garon`garon2`13535`13535`373235`yes`13535`1`1`17372`symmetric`67%`real`unsymmetric`no`no`A. Garon`T. Davis`1996`computational fluid dynamics problem` | |
| 446`Goodwin`goodwin`7320`7320`324772`yes`7320`2`2`12`64%`0%`real`unsymmetric`no`no`R. Goodwin`T. Davis`1995`computational fluid dynamics problem` | |
| 447`Goodwin`rim`22560`22560`1014951`yes`22560`2`2`0`64%`0%`real`unsymmetric`no`no`R. Goodwin`T. Davis`1995`computational fluid dynamics problem` | |
| 448`Graham`graham1`9035`9035`335472`yes`9035`478`474`32`72%`0%`real`unsymmetric`no`no`D. Graham`T. Davis`1998`computational fluid dynamics problem` | |
| 449`Grund`b1_ss`7`7`15`yes`7`1`1`0`0%`0%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`chemical process simulation problem` | |
| 450`Grund`b2_ss`1089`1089`3895`yes`1089`249`1`333`1%`0%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`chemical process simulation problem` | |
| 451`Grund`b_dyn`1089`1089`4144`yes`1089`164`1`120`1%`0%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`chemical process simulation problem` | |
| 452`Grund`bayer01`57735`57735`275094`yes`57735`9133`1`2680`0%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 453`Grund`bayer02`13935`13935`63307`yes`13935`2226`1`372`0%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 454`Grund`bayer03`6747`6747`29195`yes`6747`2419`1`27001`0%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 455`Grund`bayer04`20545`20545`85537`yes`20545`8168`6`73545`0%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 456`Grund`bayer05`3268`3268`20712`yes`3268`3037`1`7124`1%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 457`Grund`bayer06`3008`3008`20715`yes`3008`1273`1`6861`1%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 458`Grund`bayer07`3268`3268`20963`yes`3268`3037`1`6873`1%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 459`Grund`bayer08`3008`3008`20698`yes`3008`1273`1`6878`1%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 460`Grund`bayer09`3083`3083`11767`yes`3083`1872`2`9449`2%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 461`Grund`bayer10`13436`13436`71594`yes`13436`2545`1`23332`0%`0%`real`unsymmetric`no`no`Bayer`F. Grund`1997`chemical process simulation problem` | |
| 462`Grund`d_dyn`87`87`230`yes`87`19`1`8`8%`2%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`chemical process simulation problem` | |
| 463`Grund`d_dyn1`87`87`232`yes`87`17`1`6`8%`2%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`chemical process simulation problem` | |
| 464`Grund`d_ss`53`53`144`yes`53`1`1`5`4%`0%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`chemical process simulation problem` | |
| 465`Grund`meg1`2904`2904`58142`yes`2904`929`1`0`0%`0%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`circuit simulation problem` | |
| 466`Grund`meg4`5860`5860`25258`yes`5860`1412`1318`21584`symmetric`symmetric`real`symmetric`no`no`F. Grund`F. Grund`1997`circuit simulation problem` | |
| 467`Grund`poli`4008`4008`8188`yes`4008`3943`3943`0`3%`0%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`economic problem` | |
| 468`Grund`poli_large`15575`15575`33033`yes`15575`15466`15466`41`0%`0%`real`unsymmetric`no`no`F. Grund`F. Grund`1997`economic problem` | |
| 469`Gset`G1`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 470`Gset`G10`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 471`Gset`G11`800`800`3200`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 472`Gset`G12`800`800`3200`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 473`Gset`G13`800`800`3200`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 474`Gset`G14`800`800`9388`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G18\n | |
| 475`Gset`G15`800`800`9322`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G19\n | |
| 476`Gset`G16`800`800`9344`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G20\n | |
| 477`Gset`G17`800`800`9334`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G21\n | |
| 478`Gset`G18`800`800`9388`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 479`Gset`G19`800`800`9322`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 480`Gset`G2`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 481`Gset`G20`800`800`9344`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 482`Gset`G21`800`800`9334`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 483`Gset`G22`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 484`Gset`G23`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 485`Gset`G24`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 486`Gset`G25`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 487`Gset`G26`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 488`Gset`G27`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 489`Gset`G28`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 490`Gset`G29`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 491`Gset`G3`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 492`Gset`G30`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 493`Gset`G31`2000`2000`39980`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 494`Gset`G32`2000`2000`8000`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 495`Gset`G33`2000`2000`8000`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 496`Gset`G34`2000`2000`8000`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 497`Gset`G35`2000`2000`23556`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G39\n | |
| 498`Gset`G36`2000`2000`23532`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G40\n | |
| 499`Gset`G37`2000`2000`23570`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G41\n | |
| 500`Gset`G38`2000`2000`23558`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G42\n | |
| 501`Gset`G39`2000`2000`23556`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 502`Gset`G4`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 503`Gset`G40`2000`2000`23532`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 504`Gset`G41`2000`2000`23570`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 505`Gset`G42`2000`2000`23558`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 506`Gset`G43`1000`1000`19980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 507`Gset`G44`1000`1000`19980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 508`Gset`G45`1000`1000`19980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 509`Gset`G46`1000`1000`19980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 510`Gset`G47`1000`1000`19980`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 511`Gset`G48`3000`3000`12000`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 512`Gset`G49`3000`3000`12000`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 513`Gset`G5`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 514`Gset`G50`3000`3000`12000`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 515`Gset`G51`1000`1000`11818`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 516`Gset`G52`1000`1000`11832`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 517`Gset`G53`1000`1000`11828`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 518`Gset`G54`1000`1000`11832`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected random graph` | |
| 519`Gset`G55`5000`5000`24996`unknown`unknown`unknown`32`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G56\n | |
| 520`Gset`G56`5000`5000`24996`unknown`unknown`unknown`32`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 521`Gset`G57`5000`5000`20000`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 522`Gset`G58`5000`5000`59140`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G59\n | |
| 523`Gset`G59`5000`5000`59140`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 524`Gset`G6`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 525`Gset`G60`7000`7000`34296`unknown`unknown`unknown`45`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G61\n | |
| 526`Gset`G61`7000`7000`34296`unknown`unknown`unknown`45`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 527`Gset`G62`7000`7000`28000`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 528`Gset`G63`7000`7000`82918`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`C. Helmberg`Y. Ye`1996`duplicate undirected random graph`\nThis matrix is the nonzero pattern of Gset/G64\n | |
| 529`Gset`G64`7000`7000`82918`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 530`Gset`G65`8000`8000`32000`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 531`Gset`G66`9000`9000`36000`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 532`Gset`G67`10000`10000`40000`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 533`Gset`G7`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 534`Gset`G8`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 535`Gset`G9`800`800`38352`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`C. Helmberg`Y. Ye`1996`undirected weighted random graph` | |
| 536`Gupta`gupta1`31802`31802`2164210`yes`31802`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Gupta`T. Davis`1996`optimization problem` | |
| 537`Gupta`gupta2`62064`62064`4248286`yes`62064`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Gupta`T. Davis`1996`optimization problem` | |
| 538`Gupta`gupta3`16783`16783`9323427`yes`16783`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Gupta`T. Davis`1996`optimization problem` | |
| 539`Hamm`add20`2395`2395`13151`yes`2395`1`1`4168`symmetric`53%`real`unsymmetric`no`no`S. Hamm`T. Davis`1991`circuit simulation problem` | |
| 540`Hamm`add32`4960`4960`19848`yes`4960`1`1`4036`symmetric`31%`real`unsymmetric`no`no`S. Hamm`T. Davis`1991`circuit simulation problem` | |
| 541`Hamm`bcircuit`68902`68902`375558`yes`68902`1`1`0`symmetric`91%`real`unsymmetric`no`no`S. Hamm`T. Davis`2001`circuit simulation problem` | |
| 542`Hamm`hcircuit`105676`105676`513072`yes`105676`1420`1359`0`100%`20%`real`unsymmetric`no`no`S. Hamm`T. Davis`2001`circuit simulation problem` | |
| 543`Hamm`memplus`17758`17758`99147`yes`17758`23`23`27003`symmetric`50%`real`unsymmetric`no`no`S. Hamm`T. Davis`1991`circuit simulation problem` | |
| 544`Hamm`scircuit`170998`170998`958936`yes`170998`153`48`0`100%`80%`real`unsymmetric`no`no`S. Hamm`T. Davis`2001`circuit simulation problem` | |
| 545`Hollinger`g7jac010`2880`2880`18229`yes`2880`177`107`1406`7%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 546`Hollinger`g7jac010sc`2880`2880`18229`yes`2880`177`107`1406`7%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 547`Hollinger`g7jac020`5850`5850`42568`yes`5850`317`177`2897`6%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 548`Hollinger`g7jac020sc`5850`5850`42568`yes`5850`317`177`2897`6%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 549`Hollinger`g7jac040`11790`11790`107383`yes`11790`597`317`7288`5%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 550`Hollinger`g7jac040sc`11790`11790`107383`yes`11790`597`317`7288`5%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 551`Hollinger`g7jac050sc`14760`14760`145157`yes`14760`737`387`12833`4%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 552`Hollinger`g7jac060`17730`17730`183325`yes`17730`877`457`19991`4%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 553`Hollinger`g7jac060sc`17730`17730`183325`yes`17730`877`457`19991`4%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 554`Hollinger`g7jac080`23670`23670`259648`yes`23670`1157`597`34328`4%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 555`Hollinger`g7jac080sc`23670`23670`259648`yes`23670`1157`597`34328`4%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 556`Hollinger`g7jac100`29610`29610`335972`yes`29610`1437`737`48664`4%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 557`Hollinger`g7jac100sc`29610`29610`335972`yes`29610`1437`737`48664`4%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 558`Hollinger`g7jac120`35550`35550`412306`yes`35550`1717`877`62990`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 559`Hollinger`g7jac120sc`35550`35550`412306`yes`35550`1717`877`62990`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 560`Hollinger`g7jac140`41490`41490`488633`yes`41490`1997`1017`77323`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 561`Hollinger`g7jac140sc`41490`41490`488633`yes`41490`1997`1017`77323`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 562`Hollinger`g7jac160`47430`47430`564952`yes`47430`2277`1157`91664`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 563`Hollinger`g7jac160sc`47430`47430`564952`yes`47430`2277`1157`91664`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 564`Hollinger`g7jac180`53370`53370`641290`yes`53370`2557`1297`105986`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 565`Hollinger`g7jac180sc`53370`53370`641290`yes`53370`2557`1297`105986`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 566`Hollinger`g7jac200`59310`59310`717620`yes`59310`2837`1437`120316`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 567`Hollinger`g7jac200sc`59310`59310`717620`yes`59310`2837`1437`120316`3%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 568`Hollinger`jan99jac020`6774`6774`33744`yes`6774`1311`1291`4948`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 569`Hollinger`jan99jac020sc`6774`6774`33744`yes`6774`1311`1291`4948`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 570`Hollinger`jan99jac040`13694`13694`72734`yes`13694`1934`1914`10108`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 571`Hollinger`jan99jac040sc`13694`13694`72734`yes`13694`1934`1914`10108`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 572`Hollinger`jan99jac060`20614`20614`111903`yes`20614`2774`2754`15279`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 573`Hollinger`jan99jac060sc`20614`20614`111903`yes`20614`2774`2754`15279`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 574`Hollinger`jan99jac080`27534`27534`151063`yes`27534`3614`3594`20459`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 575`Hollinger`jan99jac080sc`27534`27534`151063`yes`27534`3614`3594`20459`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 576`Hollinger`jan99jac100`34454`34454`190224`yes`34454`4450`4430`25638`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 577`Hollinger`jan99jac100sc`34454`34454`190224`yes`34454`4450`4430`25638`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 578`Hollinger`jan99jac120`41374`41374`229385`yes`41374`5292`5272`30817`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 579`Hollinger`jan99jac120sc`41374`41374`229385`yes`41374`5292`5272`30817`0%`0%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 580`Hollinger`mark3jac020`9129`9129`52883`yes`9129`321`321`3292`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 581`Hollinger`mark3jac020sc`9129`9129`52883`yes`9129`321`321`3292`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 582`Hollinger`mark3jac040`18289`18289`106803`yes`18289`641`641`6632`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 583`Hollinger`mark3jac040sc`18289`18289`106803`yes`18289`641`641`6632`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 584`Hollinger`mark3jac060`27449`27449`160723`yes`27449`961`961`9972`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 585`Hollinger`mark3jac060sc`27449`27449`160723`yes`27449`961`961`9972`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 586`Hollinger`mark3jac080`36609`36609`214643`yes`36609`1281`1281`13312`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 587`Hollinger`mark3jac080sc`36609`36609`214643`yes`36609`1281`1281`13312`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 588`Hollinger`mark3jac100`45769`45769`268563`yes`45769`1601`1601`16652`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 589`Hollinger`mark3jac100sc`45769`45769`268563`yes`45769`1601`1601`16652`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 590`Hollinger`mark3jac120`54929`54929`322483`yes`54929`1921`1921`19992`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 591`Hollinger`mark3jac120sc`54929`54929`322483`yes`54929`1921`1921`19992`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 592`Hollinger`mark3jac140`64089`64089`376395`yes`64089`2241`2241`23340`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 593`Hollinger`mark3jac140sc`64089`64089`376395`yes`64089`2241`2241`23340`7%`1%`real`unsymmetric`no`no`P. Hollinger`T. Davis`2001`economic problem` | |
| 594`LPnetlib`lp_25fv47`821`1876`10705`no`820`29`3`0`0%`0%`real`rectangular`no`no`J. Reid`D. Gay`1978`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \n------------------------------------------------------------------------------\nThis LP problem is the source of nine sparse matrices in the Harwell/Boeing \nsparse matrix collection: BP_0, BP_200, BP_400, BP_600, BP_800, BP_1000, \nBP_1200, BP_1400, and BP_1600. Those nine matrices are square, nonsingular \nbasis matrices that occured during the solution of 25FV47 (also called BP \nor BP1). \n------------------------------------------------------------------------------\n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \n25FV47 822 1571 11127 70477 5.5018458883E+03 \n \nFrom John Reid. Problem 25FV47 is sometimes called BP or BP1. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \n25FV47 5.5018467791E+03 \n \n | |
| 595`LPnetlib`lp_80bau3b`2262`12061`23264`yes`2262`26`154`0`0%`0%`real`rectangular`no`no`W. Kurator, H. Greenberg`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \n80BAU3B 2263 9799 29063 298952 B 9.8723216072E+05 \n \n BOUND-TYPE TABLE \n80BAU3B UP LO FX \n \nSupplied by Bob Fourer. \n \nWhen included in Netlib: Extra free rows omitted. \n \nSource: W. Kurator and Harvey Greenberg, Energy Information \nAdministration (Greenberg is now at the Univ. of Colorado - Denver). \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \n80BAU3B 9.8722419241E+05 9.8722952818E+05 \n | |
| 596`LPnetlib`lp_adlittle`56`138`424`yes`56`2`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nADLITTLE 57 97 465 3690 2.2549496316E+05 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 2. ADLITTLE 57 97 465 2.2549496E+05 123 1.3 98 1.1 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 597`LPnetlib`lp_afiro`27`51`102`yes`27`1`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nAFIRO 28 32 88 794 -4.6475314286E+02 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 1. AFIRO 28 32 88 -4.6475314E+02 6 0.5 6 0.5 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 598`LPnetlib`lp_agg`488`615`2862`yes`488`1`1`0`0%`0%`real`rectangular`no`no`R. Leachman`M. Resende`1988`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nAGG 489 163 2541 21865 -3.5991767287E+07 \n \nProvided by Mauricio Resende. Formulated by R. C. Leachman. \nAdded to Netlib on 6 May 1988 \n \n | |
| 599`LPnetlib`lp_agg2`516`758`4740`yes`516`1`1`0`0%`0%`real`rectangular`no`no`R. Leachman`M. Resende`1988`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nAGG2 517 302 4515 32552 -2.0239252356E+07 \n \nProvided by Mauricio Resende. Formulated by R. C. Leachman. \nAdded to Netlib on 6 May 1988 \n | |
| 600`LPnetlib`lp_agg3`516`758`4756`yes`516`1`1`0`0%`0%`real`rectangular`no`no`R. Leachman`M. Resende`1988`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nAGG3 517 302 4531 32570 1.0312115935E+07 \n \nProvided by Mauricio Resende. Formulated by R. C. Leachman. \nAdded to Netlib on 6 May 1988 \n | |
| 601`LPnetlib`lp_bandm`305`472`2494`yes`305`48`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nBANDM 306 472 2659 19460 -1.5862801845E+02 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 10. BANDM 306 472 2659 -1.5862802E+02 362 7.6 534 10.0 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 602`LPnetlib`lp_beaconfd`173`295`3408`yes`173`34`6`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nBEACONFD 174 262 3476 17475 3.3592485807E+04 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\nWhen included in Netlib: Extra right-hand side vectors omitted. \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 5. BEACONFD 174 262 3476 3.3592486E+04 38 1.9 39 1.8 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 603`LPnetlib`lp_blend`74`114`522`yes`74`1`1`0`0%`0%`real`rectangular`no`no`N. Gould`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nBLEND 75 83 521 3227 -3.0812149846E+01 \n \nNick Gould supplied BLEND from the Harwell collection of LP test problems. \n \nConcerning the problems he supplied, Nick Gould says that BLEND \"is \na variant of the [oil refinery] problem in Murtagh's book (the \ncoefficients are different) which I understand John Reid obtained \nfrom the people at NPL (Gill and Murray?); they were also the original \nsources for the SC problems\" \n \nAdded to Netlib on 6 April 1989 \n \n | |
| 604`LPnetlib`lp_bnl1`643`1586`5532`no`642`12`12`0`0%`0%`real`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nBNL1 644 1175 6129 42473 1.9776292856E+03 \n \nFrom John Tomlin. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nBNL1 1.9776295615E+03 1.9776293385E+03 \n \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n BNL1 1614 169 10.47 \n \nAdded to Netlib on 30 Oct. 1989 \n \n | |
| 605`LPnetlib`lp_bnl2`2324`4486`14996`yes`2324`60`104`0`0%`0%`real`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nBNL2 2325 3489 16124 127145 1.8112365404E+03 \n \nFrom John Tomlin. \n \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n BNL2 4914 906 18.44 \n \nAdded to Netlib on 30 Oct. 1989 \n | |
| 606`LPnetlib`lp_bore3d`233`334`1448`no`232`42`21`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nBORE3D 234 315 1525 13160 B 1.3730803942E+03 \n \n BOUND-TYPE TABLE \nBORE3D UP LO FX \n \nSupplied by Bob Fourer. \nSource: consulting. \nEmpty RHS section. \n \nWhen included in Netlib: Extra free rows omitted. \n \n | |
| 607`LPnetlib`lp_brandy`220`303`2202`no`193`58`40`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nBRANDY 221 249 2150 14028 1.5185098965E+03 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\nWhen included in Netlib: Extra right-hand side vectors omitted. \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 7. BRANDY 221 249 2150 1.5185099E+03 292 4.9 377 5.9 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 608`LPnetlib`lp_capri`271`482`1896`yes`271`17`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nCAPRI 272 353 1786 15267 B 2.6900129138E+03 \n \n BOUND-TYPE TABLE \nCAPRI UP FX FR \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 9. CAPRI 272 353 1786 2.6900129E+03 273 4.4 235 3.9 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 609`LPnetlib`lp_cre_a`3516`7248`18168`no`3428`8`89`0`0%`0%`real`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nCRE-A 3517 4067 19054 0 152726 659682 2.3595407e+07\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 610`LPnetlib`lp_cre_b`9648`77137`260785`no`7240`6`2409`0`0%`0%`real`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nCRE-B 9649 72447 328542 0 2119719 10478735 2.3129640e+07\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 611`LPnetlib`lp_cre_c`3068`6411`15977`no`2986`17`83`0`0%`0%`real`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nCRE-C 3069 3678 16922 0 135315 587817 2.5275116e+07\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 612`LPnetlib`lp_cre_d`8926`73948`246614`no`6476`22`2451`0`0%`0%`real`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\n \nCRE-A 3517 4067 19054 0 152726 659682 2.3595407e+07\nCRE-B 9649 72447 328542 0 2119719 10478735 2.3129640e+07\nCRE-C 3069 3678 16922 0 135315 587817 2.5275116e+07\nCRE-D 8927 69980 312626 0 2022105 9964196 2.4454970e+07\nKEN-07 2427 3602 11981 7204 150525 718748 -6.7952044e+08\nKEN-11 14695 21349 70354 42698 928171 4167698 -6.9723823e+09\nKEN-13 28633 42659 139834 85318 1836457 8254122 -1.0257395e+10\nKEN-18 105128 154699 512719 309398 7138893 29855000 -5.2217025e+10\nOSA-07 1119 23949 167643 0 1059475 5388666 5.3572252e+05\nOSA-14 2338 52460 367220 0 2359656 11800249 1.1064628e+06\nOSA-30 4351 100024 700160 0 4470876 22495351 2.1421399e+06\nOSA-60 10281 232966 1630758 0 10377094 52402461 4.0440725e+06\nPDS-02 2954 7535 21252 2134 197821 801690 2.8857862e+10\nPDS-06 9882 28655 82269 9240 769564 3124272 2.7761038e+10\nPDS-10 16559 48763 140063 16148 1313834 5331274 2.6727095e+10\nPDS-20 33875 105728 304153 34888 2856653 11550890 2.3821659e+10\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 613`LPnetlib`lp_cycle`1903`3371`21234`no`1875`98`29`0`0%`0%`real`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nCYCLE 1904 2857 21322 166648 B -5.2263930249E+00 \n \n BOUND-TYPE TABLE \nCYCLE UP FR \n \nEmpty RHS section. \n \nFrom John Tomlin. \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n CYCLE 3156 1485 47.05 \n \nAdded to Netlib on 27 June 1989 \n | |
| 614`LPnetlib`lp_czprob`929`3562`10708`yes`929`193`5`0`0%`0%`real`rectangular`no`no`J. Reid`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nCZPROB 930 3523 14173 92202 B 2.1851966989E+06 \n \n BOUND-TYPE TABLE \nCZPROB FX \n \nFrom John Reid. Previously named \"GUB\". \n | |
| 615`LPnetlib`lp_d2q06c`2171`5831`33081`yes`2171`11`1`0`0%`0%`real`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nD2Q06C 2172 5167 35674 258038 1.2278423615E+05 \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nD2Q06C 1.2278423521E+05 \n \nFrom John Tomlin. \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n D2Q06C 42417 4223 9.96 \n \nAdded to Netlib on 30 Oct. 1989 \n | |
| 616`LPnetlib`lp_d6cube`415`6184`37704`no`404`3`12`0`0%`0%`integer`rectangular`no`no`R. Hughes`D. Gay`1993`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nD6CUBE 416 6184 43888 167633 B 3.1549166667E+02 \n \n BOUND-TYPE TABLE \nD6CUBE LO \n \nSupplied by Robert Hughes. \n \nOf D6CUBE, Robert Hughes says, \"Mike Anderson and I are working on the \nproblem of finding the minimum cardinality of triangulations of the \n6-dimensional cube. The optimal objective value of the problem I sent \nyou provides a lower bound for the cardinalities of all triangulations \nwhich contain a certain simplex of volume 8/6! and which contains the \ncentroid of the 6-cube in its interior. The linear programming \nproblem is not easily described.\" \n \nAdded to Netlib on 26 March 1993 \n | |
| 617`LPnetlib`lp_degen2`444`757`4201`yes`444`1`1`0`0%`0%`integer`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nDEGEN2 445 534 4449 24657 -1.4351780000E+03 \n \nFrom John Tomlin. \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n DEGEN2 1075 610 56.74 \n \nWhen included in Netlib: Cost coefficients negated. \n \nAdded to Netlib on 30 Oct. 1989 \n | |
| 618`LPnetlib`lp_degen3`1503`2604`25432`yes`1503`1`1`0`0%`0%`integer`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nDEGEN3 1504 1818 26230 130252 -9.8729400000E+02 \n \nFrom John Tomlin. \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n DEGEN3 6283 3299 52.51 \n \nWhen included in Netlib: Cost coefficients negated. \n \nAdded to Netlib on 30 Oct. 1989 \n | |
| 619`LPnetlib`lp_dfl001`6071`12230`35632`yes`6071`1`1`0`0%`0%`real`rectangular`no`no`M. Meketon`D. Gay`1990`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nDFL001 6072 12230 41873 353192 B 1.12664E+07 ** \n \n BOUND-TYPE TABLE \nDFL001 UP \n \nSubmitted by Marc Meketon. \n \nDFL001, says Marc Meketon, \"is a 'real-world' airline schedule planning \n(fleet assignment) problem. This LP was preprocessed by a modified \nversion of the KORBX(r) System preprocessor. The problem reduced in \nsize (rows, columns, non-zeros) significantly. The row and columns were \nrandomly sorted and renamed, and a fixed adjustment to the objective \nfunction was eliminated. The name of the problem is derived from the \ninitials of the person who created it.\" \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nDFL001 1.1266396047E+07 ** \n \nDavid Gay reports: \n** On an IEEE-arithmetic machine (an SGI 4D/380S), I (dmg) succeeded in \ngetting MINOS 5.3 to report optimal objective values, 1.1261702419E+07 \nand 1.1249281428E+07, for DFL001 only by starting with LOAD files \nderived from the solution obtained on the same machine by Bob \nVanderbei's ALPO (an interior-point code); starting from one of the \nresulting \"optimal\" bases, MINOS ran 23914 iterations on a VAX before \nreporting an optimal value of 1.1253287141E+07. When started from the \nsame LOAD file used on the SGI machine, MINOS on the VAX reported an \noptimal value of 1.1255107696E+07. Changing the FEASIBILITY TOLERANCE \nto 1.E-10 (from its default of 1.E-6) led MINOS on the SGI machine to \nreport \"optimal\" values of 1.1266408461E+07 and 1.1266402835E+07. This \nclearly is a problem where the FEASIBILITY TOLERANCE, initial basis, and \nfloating-point arithmetic strongly affect the \"optimal\" solution that \nMINOS reports. On the SGI machine, ALPO with SPLIT 3 found \n primal: obj value = 1.126639607e+07 FEASIBLE ( 2.79e-09 ) \n dual: obj value = 1.126639604e+07 FEASIBLE ( 1.39e-16 ) \n \nBob Bixby reports the following about his experience solving DFL001 \nwith CPLEX: \n First, the value for the objective function that I get running \n defaults is 1.1266396047e+07, with the following residuals: \n \n Max. unscaled (scaled) bound infeas.: 4.61853e-14 (2.30926e-14) \n Max. unscaled (scaled) reduced-cost infeas.: 6.40748e-08 (6.40748e-08) \n Max. unscaled (scaled) Ax-b resid.: 4.28546e-14 (4.28546e-14) \n Max. unscaled (scaled) c_B-B'pi resid.: 8.00937e-08 (8.00937e-08) \n \n The L_infinity condition number of the (scaled) optimal basis is \n 213737. I got exactly the same objective value solving the problem in \n several different ways. I played a bit trying to get a better \n reduced-cost infeasibility, but that seems hopeless (if not pointless) \n given the c-Bpi residuals. \n \n Just as an aside, this problem exhibits very interesting behavior when \n solved using a simplex method. I ran reduced-cost pricing on it in \n phase I, with the result that it took 465810 iterations to get \n feasible. Running the default CPLEX pricing scheme, the entire \n problem solved in 94337 iterations (33059 in phase I) on a \n Sparcstation. Steepest-edge pricing (and a different scaling) took \n 25803 iterations. This is a nasty problem. \n \n \nAdded to Netlib on 11 Oct. 1990 \n9 Jan. 1991: Bixby's remarks about DFL001 added to lp/data/readme. \n \n | |
| 620`LPnetlib`lp_e226`223`472`2768`yes`223`4`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nE226 224 282 2767 17749 -1.8751929066E+01 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\nWhen included in Netlib: Extra free rows omitted. \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 8. E226 226 282 3038 -1.8751929E+01 570 9.4 471 7.5 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 621`LPnetlib`lp_etamacro`400`816`2537`yes`400`1`2`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nETAMACRO 401 688 2489 21915 B -7.5571521774E+02 \n \n BOUND-TYPE TABLE \nETAMACRO UP LO FX \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\nWhen included in Netlib: Cost coefficients negated. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nETAMACRO -7.5571523337E+02 -7.5571522100E+02 \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 12. ETAMACRO 401 689 2489 7.5571521E+02 MAX 904 15.0 927 17.6 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 622`LPnetlib`lp_fffff800`524`1028`6401`yes`524`38`1`0`0%`0%`real`rectangular`no`no`J. Reid`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nFFFFF800 525 854 6235 39637 5.5567961165E+05 \n \nFrom John Reid. \nWhen included in Netlib: Extra right-hand side vectors omitted; \nextra bound sets omitted. \nFFFFF800 is sometimes called POWELL. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nFFFFF800 5.5567956482E+05 5.5567958085E+05 \n | |
| 623`LPnetlib`lp_finnis`497`1064`2760`yes`497`1`1`0`0%`0%`real`rectangular`no`no`N. Gould`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nFINNIS 498 614 2714 23847 B 1.7279096547E+05 \n \n BOUND-TYPE TABLE \nFINNIS UP LO FX \n \nWhen included in Netlib: Extra free rows omitted. \n \nNick Gould supplied FINNIS from the Harwell collection of LP test problems. \nConcerning the problems he supplied, Nick Gould says that FINNIS \n\"is from Mike Finnis at Harwell, a model for the selection of \nalternative fuel types.\" \n \nAdded to Netlib on 6 April 1989 \n \n | |
| 624`LPnetlib`lp_fit1d`24`1049`13427`yes`24`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1990`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nFIT1D 25 1026 14430 51734 B -9.1463780924E+03 \n \n BOUND-TYPE TABLE \nFIT1D UP \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Cost coefficients negated. \n \nConcerning FIT1D, FIT1P, FIT2D, FIT2P, Bob Fourer says \n The pairs FIT1P/FIT1D and FIT2P/FIT2D are primal and \n dual versions of the same two problems [except that we \n have negated the cost coefficients of the dual problems \n so all are minimization problems]. They originate from \n a model for fitting linear inequalities to data, by \n minimization of a sum of piecewise-linear penalties. \n The FIT1 problems are based on 627 data points and 2-3 \n pieces per primal pl penalty term. The FIT2 problems \n are based on 3000 data points (from a different sample \n altogether) and 4-5 pieces per pl term. \n \nAdded to Netlib on 31 Jan. 1990 \n \n | |
| 625`LPnetlib`lp_fit1p`627`1677`9868`yes`627`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1990`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nFIT1P 628 1677 10894 65116 B 9.1463780924E+03 \n \n BOUND-TYPE TABLE \nFIT1P UP \n \nSupplied by Bob Fourer. \n \nConcerning FIT1D, FIT1P, FIT2D, FIT2P, Bob Fourer says \n The pairs FIT1P/FIT1D and FIT2P/FIT2D are primal and \n dual versions of the same two problems [except that we \n have negated the cost coefficients of the dual problems \n so all are minimization problems]. They originate from \n a model for fitting linear inequalities to data, by \n minimization of a sum of piecewise-linear penalties. \n The FIT1 problems are based on 627 data points and 2-3 \n pieces per primal pl penalty term. The FIT2 problems \n are based on 3000 data points (from a different sample \n altogether) and 4-5 pieces per pl term. \n \nAdded to Netlib on 31 Jan. 1990 \n \n | |
| 626`LPnetlib`lp_fit2d`25`10524`129042`yes`25`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1990`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nFIT2D 26 10500 138018 482330 B -6.8464293294E+04 \n \n BOUND-TYPE TABLE \nFIT2D UP \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Cost coefficients negated. \n \nConcerning FIT1D, FIT1P, FIT2D, FIT2P, Bob Fourer says \n The pairs FIT1P/FIT1D and FIT2P/FIT2D are primal and \n dual versions of the same two problems [except that we \n have negated the cost coefficients of the dual problems \n so all are minimization problems]. They originate from \n a model for fitting linear inequalities to data, by \n minimization of a sum of piecewise-linear penalties. \n The FIT1 problems are based on 627 data points and 2-3 \n pieces per primal pl penalty term. The FIT2 problems \n are based on 3000 data points (from a different sample \n altogether) and 4-5 pieces per pl term. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nFIT2D -6.8464293232E+04 \n \nAdded to Netlib on 31 Jan. 1990 \n | |
| 627`LPnetlib`lp_fit2p`3000`13525`50284`yes`3000`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1990`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nFIT2P 3001 13525 60784 439794 B 6.8464293232E+04 \n \n BOUND-TYPE TABLE \nFIT2P UP \n \nSupplied by Bob Fourer. \n \nConcerning FIT1D, FIT1P, FIT2D, FIT2P, Bob Fourer says \n The pairs FIT1P/FIT1D and FIT2P/FIT2D are primal and \n dual versions of the same two problems [except that we \n have negated the cost coefficients of the dual problems \n so all are minimization problems]. They originate from \n a model for fitting linear inequalities to data, by \n minimization of a sum of piecewise-linear penalties. \n The FIT1 problems are based on 627 data points and 2-3 \n pieces per primal pl penalty term. The FIT2 problems \n are based on 3000 data points (from a different sample \n altogether) and 4-5 pieces per pl term. \n \nAdded to Netlib on 31 Jan. 1990 \n \n | |
| 628`LPnetlib`lp_ganges`1309`1706`6937`yes`1309`185`1`0`0%`0%`real`rectangular`no`no`L. Schrage`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nGANGES 1310 1681 7021 60191 B -1.0958636356E+05 \n \n BOUND-TYPE TABLE \nGANGES UP LO \n \nSubmitted by Linus Schrage. \nWhen included in Netlib: Extra free rows omitted; \nCost coefficients negated. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nGANGES -1.0958573613E+05 -1.0958577038E+05 \n | |
| 629`LPnetlib`lp_gfrd_pnc`616`1160`2445`yes`616`27`1`0`0%`0%`real`rectangular`no`no`R. Helgason, J. Kennington, P. Wong`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nGFRD-PNC 617 1092 3467 24476 B 6.9022359995E+06 \n \n BOUND-TYPE TABLE \nGFRD-PNC UP LO \n \nSupplied by Bob Fourer. \n \nSource: GFRD-PNC, SIERRA: R. Helgason, J. Kennington, and P. Wong, \n\"An Application of Network Programming for National Forest Planning\", \nTechnical Report OR 81006, Dept. of Operations Research, Southern \nMethodist University. \n \n | |
| 630`LPnetlib`lp_greenbea`2392`5598`31070`no`2389`75`9`0`0%`0%`real`rectangular`no`no`K. Palmer`R. Fourer`1984`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nGREENBEA 2393 5405 31499 235711 B -7.2462405908E+07 \n \n BOUND-TYPE TABLE \nGREENBEA UP LO FX \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra bound sets omitted; Extra free rows \nomitted. \nEmpty RHS section. \nProblems GREENBEA and GREENBEB differ only in their BOUNDS sections. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nGREENBEA -7.2555248130E+07 \n \nSource: GREENBEA, GREENBEB: a large refinery model; see the book \n\"A Model-Management Framework for Mathematical Programming\" by Kenneth \nH. Palmer et al. (John Wiley & Sons, New York, 1984). \n \nAdded to Netlib on 6 May 1988 \n \n | |
| 631`LPnetlib`lp_greenbeb`2392`5598`31070`no`2389`75`9`0`0%`0%`real`rectangular`no`no`K. Palmer`R. Fourer`1984`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nGREENBEB 2393 5405 31499 235739 B -4.3021476065E+06 \n \n BOUND-TYPE TABLE \nGREENBEB UP LO FX FR \n \nSupplied by Bob Fourer. \nEmpty RHS section. \nWhen included in Netlib: Extra bound sets omitted, extra free \nrows omitted. \nProblems GREENBEA and GREENBEB differ only in their BOUNDS sections. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nGREENBEB -4.3022602612E+06 -4.3021537702E+06 \n \nSource: GREENBEA, GREENBEB: a large refinery model; see the book \n\"A Model-Management Framework for Mathematical Programming\" by Kenneth \nH. Palmer et al. (John Wiley & Sons, New York, 1984). \n \nAdded to Netlib on 6 May 1988 \n | |
| 632`LPnetlib`lp_grow15`300`645`5620`yes`300`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1983`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nGROW15 301 645 5665 35041 B -1.0687094129E+08 \n \n BOUND-TYPE TABLE \nGROW15 UP \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra bound sets omitted; explicit zeros \nomitted; Cost coefficients negated. \n \nSource: GROW15, GROW22, GROW7: R. Fourer, \"Solving Staircase Linear \nPrograms by the Simplex Method, 2: Pricing\", Math. Prog. 25 (1983), \npp. 251-292. \n \n | |
| 633`LPnetlib`lp_grow22`440`946`8252`yes`440`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1983`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nGROW22 441 946 8318 50789 B -1.6083433648E+08 \n \n BOUND-TYPE TABLE \nGROW22 UP \n \nFrom Bob Fourer. \nWhen included in Netlib: Extra bound sets omitted; explicit zeros \nomitted; cost coefficients negated. \n \nSource: GROW15, GROW22, GROW7: R. Fourer, \"Solving Staircase Linear \nPrograms by the Simplex Method, 2: Pricing\", Math. Prog. 25 (1983), \npp. 251-292. \n \n | |
| 634`LPnetlib`lp_grow7`140`301`2612`yes`140`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1983`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nGROW7 141 301 2633 17043 B -4.7787811815E+07 \n \n BOUND-TYPE TABLE \nGROW7 UP \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra bound sets omitted; explicit zeros \nomitted; cost coefficients negated. \n \nSource: GROW15, GROW22, GROW7: R. Fourer, \"Solving Staircase Linear \nPrograms by the Simplex Method, 2: Pricing\", Math. Prog. 25 (1983), \npp. 251-292. \n | |
| 635`LPnetlib`lp_israel`174`316`2443`yes`174`1`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nISRAEL 175 142 2358 12109 -8.9664482186E+05 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\nWhen included in Netlib: Extra right-hand side vectors omitted. \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 6. ISRAEL 175 142 2358 -8.9664482E+05 345 5.0 231 3.7 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 636`LPnetlib`lp_kb2`43`68`313`yes`43`1`1`0`0%`0%`real`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nKB2 44 41 291 2526 B -1.7499001299E+03 \n \n BOUND-TYPE TABLE \nKB2 UP \n \nEmpty RHS section. \n \nFrom John Tomlin. \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n KB2 82 29 35.37 \n \nAdded to Netlib on 27 June 1989 \n | |
| 637`LPnetlib`lp_ken_07`2426`3602`8404`yes`2426`990`1`0`0%`0%`integer`rectangular`no`no`J. Kennington`D. Gay`1991`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nKEN-07 2427 3602 11981 7204 150525 718748 -6.7952044e+08\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 638`LPnetlib`lp_ken_11`14694`21349`49058`yes`14694`4610`1`0`0%`0%`integer`rectangular`no`no`J. Kennington`D. Gay`1991`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nKEN-11 14695 21349 70354 42698 928171 4167698 -6.9723823e+09\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 639`LPnetlib`lp_ken_13`28632`42659`97246`yes`28632`6099`1`0`0%`0%`integer`rectangular`no`no`J. Kennington`D. Gay`1991`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nKEN-13 28633 42659 139834 85318 1836457 8254122 -1.0257395e+10\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 640`LPnetlib`lp_ken_18`105127`154699`358171`yes`105127`26266`1`0`0%`0%`integer`rectangular`no`no`J. Kennington`D. Gay`1991`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nKEN-18 105128 154699 512719 309398 7138893 29855000 -5.2217025e+10\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 641`LPnetlib`lp_lotfi`153`366`1136`yes`153`9`1`0`0%`0%`real`rectangular`no`no`V. Lofti`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nLOTFI 154 308 1086 6718 -2.5264706062E+01 \n \nFrom Vahid Lotfi. \nWhen included in Netlib: cost coefficients negated. \n \nLOTFI, says Vahid Lotfi, \"involves audit staff scheduling. This problem \nis semi real world and we have used it in a study, the results of which \nare to appear in Decision Sciences (Fall 1990). The detailed \ndescription of the problem is also in the paper. The problem is \nactually an MOLP with seven objectives, the first is maximization and \nthe other six are minimization. The version that I am sending has the \naggregated objective (i.e., z1-z2-z3-z4-z5-z6-z7).\" \n \nAdded to Netlib on 27 June 1989 \n | |
| 642`LPnetlib`lp_maros`846`1966`10137`yes`846`3`3`0`0%`0%`real`rectangular`no`no`I. Maros`D. Gay`1990`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nMAROS 847 1443 10006 65906 B -5.8063743701E+04 \n \nFrom Istvan Maros. \nWhen included in Netlib: extra free rows omitted; \ncost coefficients negated. \n \nConcerning the problems he submitted, Istvan Maros says that MAROS is \nan industrial production/allocation model about which \"the customer does \nnot want to reveal the exact meaning\". \n \nAdded to Netlib on 15 June 1990 \n | |
| 643`LPnetlib`lp_maros_r7`3136`9408`144848`yes`3136`1`1`0`0%`0%`real`rectangular`no`no`I. Maros`D. Gay`1994`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nMAROS-R7 3137 9408 151120 4812587 1.4971851665E+06 \n \nFrom Istvan Maros. \n \nConcerning the problems he submitted, Istvan Maros says that \nMAROS-R7 is \"an interesting \nreal-life LP problem which appeared hard to some solvers.\" It \"is an \nimage restoration problem done via a goal programming approach. It is \nstructured, namely, its first section is a band matrix with the \ndominating number of nonzeros, while the second section is also a band \nmatrix with bandwidth equals 2 and coefficients +1, -1. The problem is \na representative of a family of problems in which the number of rows and \nthe bandwidth of the first section can vary. This one is a medium size \nproblem from the family. MAROS-R7 became available in cooperation with \nRoni Levkovitz and Carison Tong.\" \n \nAdded to Netlib on 17 Jan. 1994 \n \n | |
| 644`LPnetlib`lp_modszk1`687`1620`3168`no`686`3`3`0`0%`0%`real`rectangular`no`no`I. Maros`D. Gay`1994`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nMODSZK1 688 1620 4158 40908 B 3.2061972906E+02 \n \n BOUND-TYPE TABLE \nMODSZK1 FR \n \nFrom Istvan Maros. \nConcerning the problems he submitted, Istvan Maros says that \nMODSZK1 is a \"real-life problem\" that \nis \"very degenerate\" and on which a dual simplex algorithm \"may require \nup to 10 times\" fewer iterations than a primal simplex algorithm. It \n\"is a multi-sector economic planning model (a kind of an input/output \nmodel in economy)\" and \"is an old problem of mine and it is not easy to \nrecall more.\" \n \nAdded to Netlib on 17 Jan. 1994 \n \n | |
| 645`LPnetlib`lp_osa_07`1118`25067`144812`yes`1118`1`1`0`0%`0%`real`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nOSA-07 1119 23949 167643 0 1059475 5388666 5.3572252e+05\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 646`LPnetlib`lp_osa_14`2337`54797`317097`yes`2337`1`1`0`0%`0%`real`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nOSA-14 2338 52460 367220 0 2359656 11800249 1.1064628e+06\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 647`LPnetlib`lp_osa_30`4350`104374`604488`yes`4350`1`1`0`0%`0%`real`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nOSA-30 4351 100024 700160 0 4470876 22495351 2.1421399e+06\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 648`LPnetlib`lp_osa_60`10280`243246`1408073`yes`10280`1`1`0`0%`0%`real`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nOSA-60 10281 232966 1630758 0 10377094 52402461 4.0440725e+06\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 649`LPnetlib`lp_pds_02`2953`7716`16571`yes`2953`300`1`0`0%`0%`integer`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nPDS-02 2954 7535 21252 2134 197821 801690 2.8857862e+10\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 650`LPnetlib`lp_pds_06`9881`29351`63220`yes`9881`516`1`0`0%`0%`integer`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nPDS-06 9882 28655 82269 9240 769564 3124272 2.7761038e+10\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 651`LPnetlib`lp_pds_10`16558`49932`107605`yes`16558`581`1`0`0%`0%`integer`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nPDS-10 16559 48763 140063 16148 1313834 5331274 2.6727095e+10\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 652`LPnetlib`lp_pds_20`33874`108175`232647`no`33798`853`77`0`0%`0%`integer`rectangular`no`no`J. Kennington`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data/kennington. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/data/kennington \n \nThe following are relevant excerpts from lp/data/kennington/readme: \n \nThe \"Kennington\" problems: sixteen problems described in \"An Empirical \nEvaluation of the KORBX Algorithms for Military Airlift Applications\" \nby W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. \nWichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). \n \nThe following table gives some statistics for the \"Kennington\" \nproblems. The number of columns excludes slacks and surpluses. \nThe bounds column tells how many entries appear in the BOUNDS \nsection of the MPS file. The mpc column shows the bytes in \nthe problem after \"uncompress\" and before \"emps\"; MPS shows \nthe bytes after \"emps\". The optimal values were computed by \nVanderbei's ALPO, running on an SGI computer (with binary IEEE \narithmetic). \n \nName rows columns nonzeros bounds mpc MPS optimal value\nPDS-20 33875 105728 304153 34888 2856653 11550890 2.3821659e+10\n \nSubmitted to Netlib by Irv Lustig. \n \n | |
| 653`LPnetlib`lp_perold`625`1506`6148`yes`625`3`1`0`0%`0%`real`rectangular`no`no`N. Gould`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nPEROLD 626 1376 6026 47486 B -9.3807580773E+03 \n \n BOUND-TYPE TABLE \nPEROLD UP LO FX FR \n \nNick Gould supplied PEROLD, from the Harwell collection of LP test problems. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nPEROLD -9.3807552782E+03 -9.3807553661E+03 \n \nConcerning the problems he supplied, Nick Gould says that PEROLD \"is \nanother Pilot model (Pilot1)\". \n \nAdded to Netlib on 6 April 1989 \n \n | |
| 654`LPnetlib`lp_pilot`1441`4860`44375`yes`1441`2`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nPILOT 1442 3652 43220 278593 B -5.5740430007E+02 \n \n BOUND-TYPE TABLE \nPILOT UP LO FX \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\nWhen included in Netlib: Extra bound sets omitted; \ncost coefficients negated. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nPILOT -5.5748972928E+02 -5.5741215293E+02 \n \nConcerning PILOT87, Irv Lustig says, \"PILOT87 is considered (by John \nStone, at least) to be harder than PILOT because of the bad scaling in \nthe numerics.\" \n \nModified on Oct. 1991 (minor cleanup): removed 8 duplicate right-hand \nside values for row BTRB01. \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 13. PILOT 1460 3652 43645 5.5742994E+02 MAX ? ? 20000* 2hrs* \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n* PILOT is a linearized form of a quadratic program. The first 45 \n objective elements are the optimal gradients of the quadratic \n terms in the objective of the QP. PILOT is normally solved \n from an advanced basis, with scaling. The Itns and Time shown \n above are estimates. \n \n | |
| 655`LPnetlib`lp_pilot4`410`1123`5264`yes`410`9`1`0`0%`0%`real`rectangular`no`no`Stanford`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nPILOT4 411 1000 5145 40936 B -2.5811392641E+03 \n \n BOUND-TYPE TABLE \nPILOT4 UP FX FR PL \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Cost coefficients unchanged (PILOT4 appeared \nto be a minimization problem already). \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nPILOT4 -2.5811392589E+03 -2.5811392624E+03 \n \nSource for PILOT.JA, PILOT.WE, PILOT4, PILOTNOV: Systems Optimization \nLaboratory, Stanford University. \n | |
| 656`LPnetlib`lp_pilot87`2030`6680`74949`yes`2030`2`2`0`0%`0%`real`rectangular`no`no`J. Stone`I. Lustig`1990`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nPILOT87 2031 4883 73804 514192 B 3.0171072827E+02 \n \nSupplied by Irv Lustig, which he obtained from John Stone. \nWhen included in Netlib: Extra free rows omitted. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nPILOT87 3.0171074161E+02 \n \nAdded to Netlib on 15 June 1990. \nModified, in Netlib, on 21 Oct. 1991 (minor cleanups): removed lower bound\nof 49.5 on U[OG]ST0[12], which are subsequently fixed at 99 (UOST[12]) or \n65.4. \n \n | |
| 657`LPnetlib`lp_pilot_ja`940`2267`14977`yes`940`3`1`0`0%`0%`real`rectangular`no`no`Stanford`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nPILOT.JA 941 1988 14706 97258 B -6.1131344111E+03 \n \n BOUND-TYPE TABLE \nPILOT.JA UP LO FX FR \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Cost coefficients negated. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nPILOT.JA -6.1131364656E+03 -6.1131349867E+03 \n \nSource for PILOT.JA, PILOT.WE, PILOT4, PILOTNOV: Systems Optimization \nLaboratory, Stanford University. \n \n | |
| 658`LPnetlib`lp_pilot_we`722`2928`9265`yes`722`1`1`0`0%`0%`real`rectangular`no`no`Stanford`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nPILOT.WE 723 2789 9218 79972 B -2.7201027439E+06 \n \n BOUND-TYPE TABLE \nPILOT.WE UP LO FX FR \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Cost coefficients negated. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nPILOT.WE -2.7201075328E+06 -2.7201042967E+06 \n \nSource for PILOT.JA, PILOT.WE, PILOT4, PILOTNOV: Systems Optimization \nLaboratory, Stanford University. \n | |
| 659`LPnetlib`lp_pilotnov`975`2446`13331`yes`975`3`1`0`0%`0%`real`rectangular`no`no`Stanford`R. Fourer`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nPILOTNOV 976 2172 13129 89779 B -4.4972761882E+03 \n \n BOUND-TYPE TABLE \nPILOTNOV UP FX \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Cost coefficients negated. \nPrior to 29 April 1987, the lp/data/readme file gave the optimal value \nfrom maximizing rather than minimizing PILOTNOV. \n \nSource for PILOT.JA, PILOT.WE, PILOT4, PILOTNOV: Systems Optimization \nLaboratory, Stanford University. \n \n | |
| 660`LPnetlib`lp_qap12`3192`8856`38304`yes`3192`1`1`0`0%`0%`integer`rectangular`no`no`T. Johnson`R. Bixby, M. Saltzman, T. Johnson`1999`linear programming problem`\nA Netlib LP problem, in lp/generators/qap. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/generators/qap \n \nThis copy of QAP12 was created by the QAP generator program, \non an Sun UltraSparc, on May 15, 1997. \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nQAP12 3193 8856 44244 (see NOTES) 5.2289435056E+02 \n \nProblems QAP8, QAP12, and QAP15 are from a generator by Terri \nJohnson (communicated by a combination of Bob Bixby, Matt Saltzman, and \nTerri Johnson). \n \nSource for Terri Johnson's generator and input data \nfor producing MPS files for QAP8, QAP12, and QAP15 appear in directory \nlp/generators/qap. \n \nAdded to Netlib on 12 April 1996. \n \nThe following are relevant excerpts from lp/generators/qap/readme \n(by Terri Johnson): \n \n The Quadratic Assignment Problem (Problem QAP) is a specially- \nstructured zero-one quadratic programming problem. While having \nreceived considerable attention since its introduction into the \nliterature over 30 years ago, and while many applications exist in \nvarious disciplines, this problem has resisted exact solution \nprocedures. Only for smaller-size problems can optimal solutions be \nobtained and verified. The solution strategies for Problem QAP \ndeveloped by Johnson (Ph.D. dissertation, Clemson University, 1992) \nand Adams and Johnson (Improved Linear Programming-based Lower Bounds \nfor the Quadratic Assignment Problem, DIMACS: Quadratic Assignment \nand Related Problems, Vol. 16 (1994), 43-75) are based on a new, \nequivalent, mixed- integer linear reformulation, Problem LP. \n The traditional , nonlinear formulation of Problem QAP has a \nquadratic objective function, 2m constraints and m^2 binary variables. \nThe linearized version of concern, Problem LP, on the other hand, has \n2m^2(m-1) + m^2(m-1)^2/2 + 2m constraints, in addition to non- \nnegativity restrictions on all the variables, and m^2 binary variables \nand m^2(m-1)^2 continuous variables. The continuous relaxation of \nProblem LP, obtained by omitting the x binary restrictions, possesses \na special block diagonal structure which readily lends itself to \ndecomposition techniques. However, the inherent degeneracy makes this \na formidable program for problems as small in size as m=15 to 20. A \nsmaller reformulation, which reduces the number of constraints and \nvariables each by m^2(m-1)^2/2, can be obtained via an appropriate \nsubstitution of variables, but such a substitution forfeits the \nproblem structure. It has been amply demonstrated that this \nformulation serves as a unifying and dominating entity with respect to \nthe different linear reformulations of Problem QAP, as well as with \nrespect to a variety of bounding procedures. Consequently, the \nability to quickly solve this linear formulation holds the promise of \nbeing able to solve larger-sized QAP's. \n Provided here is Fortran source, newlp.f, for a program that \ngenerates MPS files for the linearized QAP with the substitution of \nvariables. Under the assumption that the test problem is symmetric, \nthe generator reads the problem size, m, and an mxm matrix with the \noriginal distances in the upper half of the matrix and the original \nflows in the lower half of the matrix. All diagonal entries are 0. \nUsing this input, the generator program computes the objective \nfunction coefficients for the quadratic terms, and automatically \ncomputes the constraints. The objective function is assumed to \ncontain no linear terms since such values can be easily incorporated \ninto the quadratic terms. \n Input files qap8.dat, qap12.dat, and qap15.dat cause the \ngenerator program to emit MPS files for well-known test problems of \nNugent, C.E., T.E. Vollmann, and J. Ruml, An Experimental Comparison \nof Techniques for the Assignment of Facilities to Locations, \nOperations Research, Vol. 16, No. 1 (1968), 150-173, of sizes m=8, 12, \nand 15 for the linearization. \n \n \nPROBLEM: M = 12 No. of Variables No. of Constraints \n \n QAP 144 24 \n LP (with substitution) 8856 3192 \n Optimal value: 5.2289435056e+2 \n \nFor more information, please contact Terri Johnson at: \n johnsont@numen.elon.edu \n | |
| 661`LPnetlib`lp_qap15`6330`22275`94950`yes`6330`1`1`0`0%`0%`integer`rectangular`no`no`T. Johnson`R. Bixby, M. Saltzman, T. Johnson`1999`linear programming problem`\nA Netlib LP problem, in lp/generators/qap. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/generators/qap \n \nThis copy of QAP15 was created by the QAP generator program, \non an Sun UltraSparc, on May 15, 1997. \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nQAP15 6331 22275 110700 (see NOTES) 1.0409940410E+03 \n \nProblems QAP8, QAP12, and QAP15 are from a generator by Terri \nJohnson (communicated by a combination of Bob Bixby, Matt Saltzman, and \nTerri Johnson). \n \nSource for Terri Johnson's generator and input data \nfor producing MPS files for QAP8, QAP12, and QAP15 appear in directory \nlp/generators/qap. \n \nAdded to Netlib on 12 April 1996. \n \nThe following are relevant excerpts from lp/generators/qap/readme \n(by Terri Johnson): \n \n The Quadratic Assignment Problem (Problem QAP) is a specially- \nstructured zero-one quadratic programming problem. While having \nreceived considerable attention since its introduction into the \nliterature over 30 years ago, and while many applications exist in \nvarious disciplines, this problem has resisted exact solution \nprocedures. Only for smaller-size problems can optimal solutions be \nobtained and verified. The solution strategies for Problem QAP \ndeveloped by Johnson (Ph.D. dissertation, Clemson University, 1992) \nand Adams and Johnson (Improved Linear Programming-based Lower Bounds \nfor the Quadratic Assignment Problem, DIMACS: Quadratic Assignment \nand Related Problems, Vol. 16 (1994), 43-75) are based on a new, \nequivalent, mixed- integer linear reformulation, Problem LP. \n The traditional , nonlinear formulation of Problem QAP has a \nquadratic objective function, 2m constraints and m^2 binary variables. \nThe linearized version of concern, Problem LP, on the other hand, has \n2m^2(m-1) + m^2(m-1)^2/2 + 2m constraints, in addition to non- \nnegativity restrictions on all the variables, and m^2 binary variables \nand m^2(m-1)^2 continuous variables. The continuous relaxation of \nProblem LP, obtained by omitting the x binary restrictions, possesses \na special block diagonal structure which readily lends itself to \ndecomposition techniques. However, the inherent degeneracy makes this \na formidable program for problems as small in size as m=15 to 20. A \nsmaller reformulation, which reduces the number of constraints and \nvariables each by m^2(m-1)^2/2, can be obtained via an appropriate \nsubstitution of variables, but such a substitution forfeits the \nproblem structure. It has been amply demonstrated that this \nformulation serves as a unifying and dominating entity with respect to \nthe different linear reformulations of Problem QAP, as well as with \nrespect to a variety of bounding procedures. Consequently, the \nability to quickly solve this linear formulation holds the promise of \nbeing able to solve larger-sized QAP's. \n Provided here is Fortran source, newlp.f, for a program that \ngenerates MPS files for the linearized QAP with the substitution of \nvariables. Under the assumption that the test problem is symmetric, \nthe generator reads the problem size, m, and an mxm matrix with the \noriginal distances in the upper half of the matrix and the original \nflows in the lower half of the matrix. All diagonal entries are 0. \nUsing this input, the generator program computes the objective \nfunction coefficients for the quadratic terms, and automatically \ncomputes the constraints. The objective function is assumed to \ncontain no linear terms since such values can be easily incorporated \ninto the quadratic terms. \n Input files qap8.dat, qap12.dat, and qap15.dat cause the \ngenerator program to emit MPS files for well-known test problems of \nNugent, C.E., T.E. Vollmann, and J. Ruml, An Experimental Comparison \nof Techniques for the Assignment of Facilities to Locations, \nOperations Research, Vol. 16, No. 1 (1968), 150-173, of sizes m=8, 12, \nand 15 for the linearization. \n \n \nPROBLEM: M = 15 No. of Variables No. of Constraints \n \n QAP 225 30 \n LP (with substitution) 22275 6330 \n Optimal value: 1.0409940410e+3 \n \nFor more information, please contact Terri Johnson at: \n johnsont@numen.elon.edu \n | |
| 662`LPnetlib`lp_qap8`912`1632`7296`yes`912`1`1`0`0%`0%`integer`rectangular`no`no`T. Johnson`R. Bixby, M. Saltzman, T. Johnson`1999`linear programming problem`\nA Netlib LP problem, in lp/generators/qap. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/generators/qap \n \nThis copy of QAP8 was created by the QAP generator program, \non an Sun UltraSparc, on May 15, 1997. \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nQAP8 913 1632 8304 (see NOTES) 2.0350000000E+02 \n \nProblems QAP8, QAP12, and QAP15 are from a generator by Terri \nJohnson (communicated by a combination of Bob Bixby, Matt Saltzman, and \nTerri Johnson). \n \nSource for Terri Johnson's generator and input data \nfor producing MPS files for QAP8, QAP12, and QAP15 appear in directory \nlp/generators/qap. \n \nAdded to Netlib on 12 April 1996. \n \nThe following are relevant excerpts from lp/generators/qap/readme \n(by Terri Johnson): \n \n The Quadratic Assignment Problem (Problem QAP) is a specially- \nstructured zero-one quadratic programming problem. While having \nreceived considerable attention since its introduction into the \nliterature over 30 years ago, and while many applications exist in \nvarious disciplines, this problem has resisted exact solution \nprocedures. Only for smaller-size problems can optimal solutions be \nobtained and verified. The solution strategies for Problem QAP \ndeveloped by Johnson (Ph.D. dissertation, Clemson University, 1992) \nand Adams and Johnson (Improved Linear Programming-based Lower Bounds \nfor the Quadratic Assignment Problem, DIMACS: Quadratic Assignment \nand Related Problems, Vol. 16 (1994), 43-75) are based on a new, \nequivalent, mixed- integer linear reformulation, Problem LP. \n The traditional , nonlinear formulation of Problem QAP has a \nquadratic objective function, 2m constraints and m^2 binary variables. \nThe linearized version of concern, Problem LP, on the other hand, has \n2m^2(m-1) + m^2(m-1)^2/2 + 2m constraints, in addition to non- \nnegativity restrictions on all the variables, and m^2 binary variables \nand m^2(m-1)^2 continuous variables. The continuous relaxation of \nProblem LP, obtained by omitting the x binary restrictions, possesses \na special block diagonal structure which readily lends itself to \ndecomposition techniques. However, the inherent degeneracy makes this \na formidable program for problems as small in size as m=15 to 20. A \nsmaller reformulation, which reduces the number of constraints and \nvariables each by m^2(m-1)^2/2, can be obtained via an appropriate \nsubstitution of variables, but such a substitution forfeits the \nproblem structure. It has been amply demonstrated that this \nformulation serves as a unifying and dominating entity with respect to \nthe different linear reformulations of Problem QAP, as well as with \nrespect to a variety of bounding procedures. Consequently, the \nability to quickly solve this linear formulation holds the promise of \nbeing able to solve larger-sized QAP's. \n Provided here is Fortran source, newlp.f, for a program that \ngenerates MPS files for the linearized QAP with the substitution of \nvariables. Under the assumption that the test problem is symmetric, \nthe generator reads the problem size, m, and an mxm matrix with the \noriginal distances in the upper half of the matrix and the original \nflows in the lower half of the matrix. All diagonal entries are 0. \nUsing this input, the generator program computes the objective \nfunction coefficients for the quadratic terms, and automatically \ncomputes the constraints. The objective function is assumed to \ncontain no linear terms since such values can be easily incorporated \ninto the quadratic terms. \n Input files qap8.dat, qap12.dat, and qap15.dat cause the \ngenerator program to emit MPS files for well-known test problems of \nNugent, C.E., T.E. Vollmann, and J. Ruml, An Experimental Comparison \nof Techniques for the Assignment of Facilities to Locations, \nOperations Research, Vol. 16, No. 1 (1968), 150-173, of sizes m=8, 12, \nand 15 for the linearization. \n \n \nPROBLEM: M = 8 No. of Variables No. of Constraints \n \n QAP 64 16 \n LP (with substitution) 1632 912 \n Optimal value: 2.035e+2 \n \n \nFor more information, please contact Terri Johnson at: \n johnsont@numen.elon.edu \n | |
| 663`LPnetlib`lp_recipe`91`204`687`yes`91`1`12`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nRECIPE 92 180 752 6210 B -2.6661600000E+02 \n \n BOUND-TYPE TABLE \nRECIPE UP LO FX \n \nEmpty RHS section. \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra bound sets omitted; \nextra free rows omitted. \n \nSource: consulting. \n \n | |
| 664`LPnetlib`lp_sc105`105`163`340`yes`105`2`2`0`0%`0%`real`rectangular`no`no`N. Gould`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSC105 106 103 281 3307 -5.2202061212E+01 \n \nNick Gould supplied SC105 from the Harwell collection of LP test problems.\nWhen included in Netlib: Cost coefficients negated. \n \nAdded to Netlib on 6 April 1989 \n | |
| 665`LPnetlib`lp_sc205`205`317`665`yes`205`3`3`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSC205 206 203 552 6380 -5.2202061212E+01 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n | |
| 666`LPnetlib`lp_sc50a`50`78`160`yes`50`2`2`0`0%`0%`real`rectangular`no`no`N. Gould`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSC50A 51 48 131 1615 -6.4575077059E+01 \n \nNick Gould supplied SC50A from the Harwell collection of LP test problems.\nWhen included in Netlib: Cost coefficients negated. \n \nAdded to Netlib on 6 April 1989 \n | |
| 667`LPnetlib`lp_sc50b`50`78`148`yes`50`3`3`0`0%`0%`real`rectangular`no`no`N. Gould`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSC50B 51 48 119 1567 -7.0000000000E+01 \n \nNick Gould supplied SC50A from the Harwell collection of LP test problems.\nWhen included in Netlib: Cost coefficients negated. \n \nAdded to Netlib on 6 April 1989 \n | |
| 668`LPnetlib`lp_scagr25`471`671`1725`yes`471`2`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCAGR25 472 500 2029 17406 -1.4753433061E+07 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n | |
| 669`LPnetlib`lp_scagr7`129`185`465`yes`129`2`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCAGR7 130 140 553 4953 -2.3313892548E+06 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nSCAGR7 -2.3313898243E+06 -2.3313897524E+06 \n \n | |
| 670`LPnetlib`lp_scfxm1`330`600`2732`yes`330`9`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCFXM1 331 457 2612 19078 1.8416759028E+04 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n | |
| 671`LPnetlib`lp_scfxm2`660`1200`5469`yes`660`17`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCFXM2 661 914 5229 37079 3.6660261565E+04 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \n | |
| 672`LPnetlib`lp_scfxm3`990`1800`8206`yes`990`25`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCFXM3 991 1371 7846 53828 5.4901254550E+04 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \n | |
| 673`LPnetlib`lp_scorpion`388`466`1534`yes`388`110`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCORPION 389 358 1708 12186 1.8781248227E+03 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \n \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \n | |
| 674`LPnetlib`lp_scrs8`490`1275`3288`yes`490`26`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCRS8 491 1169 4029 36760 9.0429998619E+02 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \n \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nSCRS8 9.0429695380E+02 9.0429695380E+02 \n \n | |
| 675`LPnetlib`lp_scsd1`77`760`2388`yes`77`1`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCSD1 78 760 3148 17852 8.6666666743E+00 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \n | |
| 676`LPnetlib`lp_scsd6`147`1350`4316`yes`147`1`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCSD6 148 1350 5666 32161 5.0500000078E+01 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nSCSD6 5.0500000077E+01 \n \n | |
| 677`LPnetlib`lp_scsd8`397`2750`8584`yes`397`1`1`0`0%`0%`real`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCSD8 398 2750 11334 65888 9.0499999993E+02 \n \nSupplied by Bob Fourer. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \n | |
| 678`LPnetlib`lp_sctap1`300`660`1872`yes`300`1`1`0`0%`0%`integer`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCTAP1 301 480 2052 14970 1.4122500000E+03 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \n | |
| 679`LPnetlib`lp_sctap2`1090`2500`7334`yes`1090`1`1`0`0%`0%`integer`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCTAP2 1091 1880 8124 57479 1.7248071429E+03 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \n | |
| 680`LPnetlib`lp_sctap3`1480`3340`9734`yes`1480`1`1`0`0%`0%`integer`rectangular`no`no`J. Ho, E. Loute`R. Fourer`1981`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSCTAP3 1481 2480 10734 78688 1.4240000000E+03 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: J.K. Ho and E. Loute, \"A Set of Staircase Linear Programming \nTest Problems\", Math. Prog. 20 (1981), pp. 245-250. \n \n | |
| 681`LPnetlib`lp_share1b`117`253`1179`yes`117`6`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHARE1B 118 225 1182 8380 -7.6589318579E+04 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\n \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 4. SHARE1B 118 225 1182 -7.6589319E+04 296 3.4 260 2.8 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 682`LPnetlib`lp_share2b`96`162`777`yes`96`1`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHARE2B 97 79 730 4795 -4.1573224074E+02 \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\nWhen included in Netlib: Extra free rows omitted. \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 3. SHARE2B 99 79 802 -4.1573224E+02 91 1.3 121 1.4 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 683`LPnetlib`lp_shell`536`1777`3558`yes`536`1`1`0`0%`0%`integer`rectangular`no`no`J. Reid`D. Gay`1978`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \n------------------------------------------------------------------------------\nThis LP problem is the source of three sparse matrices in the Harwell/Boeing \nsparse matrix collection: SHL_0, SHL_200, and SHL_400. Those three matrices \nare square, nonsingular basis matrices that occured during the solution of \nSHELL. \n------------------------------------------------------------------------------\n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHELL 537 1775 4900 38049 B 1.2088253460E+09 \n \n BOUND-TYPE TABLE \nSHELL UP LO FX \n \nFrom John Reid. \n \n | |
| 684`LPnetlib`lp_ship04l`402`2166`6380`no`360`6`43`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHIP04L 403 2118 8450 57203 1.7933245380E+06 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: consulting. \n \n | |
| 685`LPnetlib`lp_ship04s`402`1506`4400`no`360`94`43`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHIP04S 403 1458 5810 41257 1.7987147004E+06 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: consulting. \n \n | |
| 686`LPnetlib`lp_ship08l`778`4363`12882`no`712`26`67`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHIP08L 779 4283 17085 117083 1.9090552114E+06 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: consulting. \n \n | |
| 687`LPnetlib`lp_ship08s`778`2467`7194`no`712`298`67`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHIP08S 779 2387 9501 70093 1.9200982105E+06 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: consulting. \n \n | |
| 688`LPnetlib`lp_ship12l`1151`5533`16276`no`1042`206`110`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHIP12L 1152 5427 21597 146753 1.4701879193E+06 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: consulting. \n \n | |
| 689`LPnetlib`lp_ship12s`1151`2869`8284`no`1042`578`110`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSHIP12S 1152 2763 10941 82527 1.4892361344E+06 \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra free rows omitted. \nSource: consulting. \n \n | |
| 690`LPnetlib`lp_sierra`1227`2735`8001`yes`1227`1`1`0`0%`0%`integer`rectangular`no`no`R. Helgason, J. Kennington, P. Wong`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSIERRA 1228 2036 9252 76627 B 1.5394362184E+07 \n \n BOUND-TYPE TABLE \nSIERRA UP \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Explicit zeros omitted. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nSIERRA 1.5394364186E+07 \n \nSource: GFRD-PNC, SIERRA: R. Helgason, J. Kennington, and P. Wong, \n\"An Application of Network Programming for National Forest Planning\", \nTechnical Report OR 81006, Dept. of Operations Research, Southern \nMethodist University. \n \n | |
| 691`LPnetlib`lp_stair`356`614`4003`yes`356`1`1`0`0%`0%`real`rectangular`no`no`M. Saunders`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send minos from lp/data \n \n------------------------------------------------------------------------------\nThis LP problem is the source of four sparse matrices in the Harwell/Boeing \nsparse matrix collection: STR_0, STR_200, STR_400, and STR_600. Those four \nmatrices are square, nonsingular basis matrices that occured during the \nsolution of STAIR. \n------------------------------------------------------------------------------\n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSTAIR 357 467 3857 27405 B -2.5126695119E+02 \n \n BOUND-TYPE TABLE \nSTAIR UP FX FR \n \nFrom Michael Saunders, Systems Optimization Laboratory at Stanford University.\nWhen included in Netlib: Explicit zeros omitted; \ncost coefficients negated. \n \nThe following are relevant excerts from lp/data/minos (by Michael Saunders), \nregarding experience with MINOS 5.0 on the problems he provided: \n \n (unscaled) (scaled) \nFile Name Rows Cols Elems Optimal Objective Itns Time Itns Time \n---- -------- ---- ---- ----- ----------------- ---- ---- ---- ---- \n 11. STAIR 357 467 3867 2.5126695E+02 MAX 519 15.7 389 13.1 \n \n* Objective is the first row of type N. It is minimized except as shown. \n \n* Itns is the number of iterations required to solve the problem \n by the primal simplex method, as implemented in the Fortran \n code MINOS 5.0 (May 1985), using default values for all \n parameters. (The initial basis is triangular.) \n \n* Time is the processor time required on an IBM 3081K. The MINOS \n source code was compiled with the IBM Fortran 77 compiler \n VS FORTRAN, using the options NOSDUMP, NOSYM and OPT(3). \n \n | |
| 692`LPnetlib`lp_standata`359`1274`3230`yes`359`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSTANDATA 360 1075 3038 26135 B 1.2576995000E+03 \n \n BOUND-TYPE TABLE \nSTANDATA UP FX \n \nSupplied by Bob Fourer. \n \nSTANDGUB includes GUB markers; with these lines removed (lines in \nthe expanded MPS file that contain primes, i.e., that mention the rows \n'EGROUP' and 'ENDX'), STANDGUB becomes the same as problem STANDATA; \nMINOS does not understand the GUB markers, so we cannot report an \noptimal value from MINOS for STANDGUB. STANDMPS amounts to STANDGUB \nwith the GUB constraints as explicit constraints. \n \nSource: consulting. \n \n | |
| 693`LPnetlib`lp_standgub`361`1383`3338`no`360`2`4`1`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSTANDGUB 362 1184 3147 27836 B (see NOTES) \n \n BOUND-TYPE TABLE \nSTANDGUB UP FX \n \nSupplied by Bob Fourer. \n \nSTANDGUB includes GUB markers; with these lines removed (lines in \nthe expanded MPS file that contain primes, i.e., that mention the rows \n'EGROUP' and 'ENDX'), STANDGUB becomes the same as problem STANDATA; \nMINOS does not understand the GUB markers, so we cannot report an \noptimal value from MINOS for STANDGUB. STANDMPS amounts to STANDGUB \nwith the GUB constraints as explicit constraints. \n \nSource: consulting. \n | |
| 694`LPnetlib`lp_standmps`467`1274`3878`yes`467`1`1`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSTANDMPS 468 1075 3686 29839 B 1.4060175000E+03 \n \n BOUND-TYPE TABLE \nSTANDMPS UP FX \n \nSupplied by Bob Fourer. \n \nSTANDGUB includes GUB markers; with these lines removed (lines in \nthe expanded MPS file that contain primes, i.e., that mention the rows \n'EGROUP' and 'ENDX'), STANDGUB becomes the same as problem STANDATA; \nMINOS does not understand the GUB markers, so we cannot report an \noptimal value from MINOS for STANDGUB. STANDMPS amounts to STANDGUB \nwith the GUB constraints as explicit constraints. \n \nSource: consulting. \n \n | |
| 695`LPnetlib`lp_stocfor1`117`165`501`yes`117`12`1`0`0%`0%`real`rectangular`no`no`G. Gassmann`D. Gay`1988`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSTOCFOR1 118 111 474 4247 -4.1131976219E+04 \n \nSTOCFOR12,3 are stochastic forestry problems from Gus Gassmann. To \nquote Gus, \"All of them are seven-period descriptions of a forestry \nproblem with a random occurrence of forest fires, and the size varies \naccording to the number of realizations you use in each period.\" \nSTOCFOR1 \"is the deterministic version, STOCFOR2 has 2 realizations \neach in periods 2 to 7, and the monster STOCFOR3 has 44,42,2, and 2 \nrealizations, respectively.\" The compressed form of STOCFOR3 would be \n652846 bytes long, so requesting STOCFOR3 will instead get you a bundle \nof about 174 kilobytes that includes source for Gus's program, the \ndata files for generating STOCFOR3 and a summary of \"A Standard \nInput Format for Multistage Stochastic Linear Programs\" by J.R. Birge, \nM.A.H. Dempster, H.I. Gassmann, E.A. Gunn, A.J. King, and S.W. Wallace \n[COAL Newsletter No. 17 (Dec. 1987), pp. 1-19]. Data files are also \nincluded for generating versions of STOCFOR12 that have more decimal \nplaces than the versions in lp/data. \n \nAdded to Netlib on 25 June 1988 \n \n | |
| 696`LPnetlib`lp_stocfor2`2157`3045`9357`yes`2157`17`1`0`0%`0%`real`rectangular`no`no`G. Gassmann`D. Gay`1988`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSTOCFOR2 2158 2031 9492 79845 -3.9024408538E+04 \n \nSTOCFOR12,3 are stochastic forestry problems from Gus Gassmann. To \nquote Gus, \"All of them are seven-period descriptions of a forestry \nproblem with a random occurrence of forest fires, and the size varies \naccording to the number of realizations you use in each period.\" \nSTOCFOR1 \"is the deterministic version, STOCFOR2 has 2 realizations \neach in periods 2 to 7, and the monster STOCFOR3 has 44,42,2, and 2 \nrealizations, respectively.\" The compressed form of STOCFOR3 would be \n652846 bytes long, so requesting STOCFOR3 will instead get you a bundle \nof about 174 kilobytes that includes source for Gus's program, the \ndata files for generating STOCFOR3 and a summary of \"A Standard \nInput Format for Multistage Stochastic Linear Programs\" by J.R. Birge, \nM.A.H. Dempster, H.I. Gassmann, E.A. Gunn, A.J. King, and S.W. Wallace \n[COAL Newsletter No. 17 (Dec. 1987), pp. 1-19]. Data files are also \nincluded for generating versions of STOCFOR12 that have more decimal \nplaces than the versions in lp/data. \n \nAdded to Netlib on 25 June 1988 \n \n | |
| 697`LPnetlib`lp_stocfor3`16675`23541`72721`yes`16675`33`1`3752`0%`0%`real`rectangular`no`no`G. Gassmann`D. Gay`1989`linear programming problem`\nA Netlib LP problem, from a generator in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThis copy of STOCFOR3 was created by the STOCFOR generator program, \non an Sun UltraSparc, on May 15, 1997. \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nSTOCFOR3 16676 15695 74004 (see NOTES) -3.9976661576E+04 \n \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nSTOCFOR3 -3.9976785944E+04 -3.9976776417E+04 \n \nSTOCFOR12,3 are stochastic forestry problems from Gus Gassmann. To \nquote Gus, \"All of them are seven-period descriptions of a forestry \nproblem with a random occurrence of forest fires, and the size varies \naccording to the number of realizations you use in each period.\" \nSTOCFOR1 \"is the deterministic version, STOCFOR2 has 2 realizations \neach in periods 2 to 7, and the monster STOCFOR3 has 44,42,2, and 2 \nrealizations, respectively.\" The compressed form of STOCFOR3 would be \n652846 bytes long, so requesting STOCFOR3 will instead get you a bundle \nof about 174 kilobytes that includes source for Gus's program, the \ndata files for generating STOCFOR3 and a summary of \"A Standard \nInput Format for Multistage Stochastic Linear Programs\" by J.R. Birge, \nM.A.H. Dempster, H.I. Gassmann, E.A. Gunn, A.J. King, and S.W. Wallace \n[COAL Newsletter No. 17 (Dec. 1987), pp. 1-19]. Data files are also \nincluded for generating versions of STOCFOR12 that have more decimal \nplaces than the versions in lp/data. \n \nAdded to Netlib on 16 Jan. 1989; bound and range information added to \nindex file; MINOS 5.3 optimal values inserted. \n \nUpdated, in Netlib, on 4 Feb. 1993. STOCFOR3 and the other problems \nyou can generate with the data in the stocfor3 bundle are the same \nnumerically as before (but with different row and column labels). \nThe update (courtesy of Gus Gassmann) fixes some bugs in other uses \nof the generator and expands your options in using the generator. \n \n | |
| 698`LPnetlib`lp_truss`1000`8806`27836`yes`1000`1`1`0`0%`0%`real`rectangular`no`no`M. Ferris`D. Gay`1990`linear programming problem`\nA Netlib LP problem, from a generator in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThis copy of TRUSS was created by the TRUSS generator program, \non an Sun UltraSparc, on May 15, 1997. \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay): \n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nTRUSS 1001 8806 36642 (see NOTES) 4.5881584719E+05 \n \nSource: At the request of Olvi Mangasarian, Rudy Setiono supplied the \ngenerator and description (both written by Michael Ferris) and data for TRUSS.\n \nRequesting TRUSS will get you a bundle of Fortran source and data for \ngenerating an MPS file for TRUSS, a problem of minimizing the weight \nof a certain structure. The bundle also includes a description of the \nproblem. \n \nAdded to Netlib on 26 Feb. 1990 \n \n | |
| 699`LPnetlib`lp_tuff`333`628`4561`no`302`12`41`0`0%`0%`real`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nTUFF 334 587 4523 29439 B 2.9214776509E-01 \n \n BOUND-TYPE TABLE \nTUFF UP LO FX FR \n \nEmpty RHS section. \n \nFrom John Tomlin. \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n TUFF 745 345 46.31 \n \nAdded to Netlib on 27 June 1989. \n | |
| 700`LPnetlib`lp_vtp_base`198`346`1051`yes`198`3`3`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nVTP.BASE 199 203 914 8175 B 1.2983146246E+05 \n \n BOUND-TYPE TABLE \nVTP.BASE UP LO FX FR \n \nSupplied by Bob Fourer. \nSource: consulting. \n \n | |
| 701`LPnetlib`lp_wood1p`244`2595`70216`yes`244`1`1`0`0%`0%`real`rectangular`no`no`J. Tomlin`D. Gay`1989`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nWOOD1P 245 2594 70216 328905 1.4429024116E+00 \n \nFrom John Tomlin. \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n WOOD1P 1059 471 44.48 \n \nAdded to Netlib on 27 June 1989 \n \n | |
| 702`LPnetlib`lp_woodw`1098`8418`37487`yes`1098`1`1`0`0%`0%`real`rectangular`no`no`J. Tomlin`D. Gay`1999`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nWOODW 1099 8405 37478 240063 1.3044763331E+00 \n \nFrom John Tomlin. \nOn the problems supplied by John Tomlin, MINOS 5.3 reports that about \n10% to 57% of its steps are degenerate: \n Name Steps Degen Percent \n WOODW 4147 1604 38.68 \n \nAdded to Netlib on 27 June 1989 \n \n | |
| 703`LPnetlib`lpi_bgdbg1`348`629`1662`yes`348`1`5`0`0%`0%`real`rectangular`no`no`L. Schrage`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nBGDBG1 is a medium problem that was originally an integer program for a \nplant operation model. Infeasibility is original. \nContributor: Linus Schrage, University of Chicago and LINDO Systems Inc. \n \nName Rows Cols Nonzeros Bounds Notes \nbgdbg1 349 407 1485 B \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 704`LPnetlib`lpi_bgetam`400`816`2537`yes`400`1`2`0`0%`0%`real`rectangular`no`no`L. Schrage`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nBGETAM is a medium model that is a version of the ETAMACRO test problem \n(in lp/data) in which one right hand side has been altered to make it \ninfeasible. \nContributor: Linus Schrage, University of Chicago and LINDO Systems Inc. \n \nName Rows Cols Nonzeros Bounds Notes \nbgetam 401 688 2489 B \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 705`LPnetlib`lpi_bgindy`2671`10880`66266`yes`2671`15`1`0`0%`0%`real`rectangular`no`no`L. Schrage`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nBGINDY is a large problem that was originally an integer program of unknown \norigin. Infeasibility is original. \nContributor: Linus Schrage, University of Chicago and LINDO Systems Inc. \n \nName Rows Cols Nonzeros Bounds Notes \nbgindy 2672 10116 75019 \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 706`LPnetlib`lpi_bgprtr`20`40`70`yes`20`1`1`0`0%`0%`integer`rectangular`no`no`L. Schrage`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nBGPRTR is a small model for a multiproduct, multiperiod production \nscheduling model. One right hand side has been altered to make it \ninfeasible. \nContributor: Linus Schrage, University of Chicago and LINDO Systems Inc. \n \nName Rows Cols Nonzeros Bounds Notes \nbgprtr 21 34 90 \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 707`LPnetlib`lpi_box1`231`261`651`yes`231`1`1`0`0%`0%`integer`rectangular`no`no`Z. You`J. Chinneck`1992`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nBOX1, EX72A, EX73A: medium problems derived from research on using the \ninfeasibility version of viability analysis [Chinneck 1992] to analyze \npetri net models. All three problems are volatile, showing IISs of \nwidely differing size depending on the algorithm applied. Contributor: \nZhengping You, Carleton University. \n \nName Rows Cols Nonzeros Bounds Notes \nbox1 232 261 912 B all cols are LO bounded \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1992). \"Viability Analysis: A Formulation Aid for All \nClasses of Network Models\", Naval Research Logistics, Vol. 39, pp. \n531-543. \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 708`LPnetlib`lpi_ceria3d`3576`4400`21178`yes`3576`1`1`0`0%`0%`integer`rectangular`no`no`E. Klotz`J. Chinneck`1999`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nCERIA3D: large problem which has some peculiarities. There are no \ncolumn bounds, and it is highly degenerate. Contributor: Ed Klotz, \nCPLEX Optimization Inc. \n \nName Rows Cols Nonzeros Bounds Notes \nceria3d 3577 824 17604 B FR dense col (> 967) \n \n | |
| 709`LPnetlib`lpi_chemcom`288`744`1590`yes`288`1`1`0`0%`0%`real`rectangular`no`no`T. Baker`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nCHEMCOM, QUAL, REFINERY, REACTOR, VOL1: medium size problems derived \nfrom a petrochemical plant model. Doctored to generate infeasibility \ndue to inability to meet volume or quality restrictions. With the \nexception of REACTOR, these are highly volatile problems, yielding IISs \nof varying sizes when different IIS isolation algorithms are applied. \nSee Chinneck [1993] for further discussion. Contributor: Tom Baker, \nChesapeake Decision Sciences. \n \nName Rows Cols Nonzeros Bounds Notes \nchemcom 289 720 2190 B \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1993). \"Finding the Most Useful Subset of Constraints \nfor Analysis in an Infeasible Linear Program\", technical report \nSCE-93-07, Systems and Computer Engineering, Carleton University, \nOttawa, Canada. \n \n | |
| 710`LPnetlib`lpi_cplex1`3005`5224`10947`yes`3005`1`1`0`0%`0%`real`rectangular`no`no`E. Klotz`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nCPLEX1, CPLEX2: medium and large problems respectively. CPLEX1 \nreferred to as CPLEX problem in Chinneck [1993], and is remarkably \nnon-volatile, showing a single small IIS regardless of the IIS algorithm \napplied. CPLEX2 is an almost-feasible problem. Contributor: Ed Klotz, \nCPLEX Optimization Inc. \n \nName Rows Cols Nonzeros Bounds Notes \ncplex1 3006 3221 10664 B dense col (> 1500) \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1993). \"Finding the Most Useful Subset of Constraints \nfor Analysis in an Infeasible Linear Program\", technical report \nSCE-93-07, Systems and Computer Engineering, Carleton University, \nOttawa, Canada. \n \n | |
| 711`LPnetlib`lpi_cplex2`224`378`1215`yes`224`1`1`0`0%`0%`real`rectangular`no`no`E. Klotz`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nCPLEX1, CPLEX2: medium and large problems respectively. CPLEX1 \nreferred to as CPLEX problem in Chinneck [1993], and is remarkably \nnon-volatile, showing a single small IIS regardless of the IIS algorithm \napplied. CPLEX2 is an almost-feasible problem. Contributor: Ed Klotz, \nCPLEX Optimization Inc. \n \nName Rows Cols Nonzeros Bounds Notes \ncplex2 225 221 1059 B \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1993). \"Finding the Most Useful Subset of Constraints \nfor Analysis in an Infeasible Linear Program\", technical report \nSCE-93-07, Systems and Computer Engineering, Carleton University, \nOttawa, Canada. \n \n | |
| 712`LPnetlib`lpi_ex72a`197`215`467`yes`197`1`1`0`0%`0%`integer`rectangular`no`no`Z. You`J. Chinneck`1992`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nBOX1, EX72A, EX73A: medium problems derived from research on using the \ninfeasibility version of viability analysis [Chinneck 1992] to analyze \npetri net models. All three problems are volatile, showing IISs of \nwidely differing size depending on the algorithm applied. Contributor: \nZhengping You, Carleton University. \n \nName Rows Cols Nonzeros Bounds Notes \nex72a 198 215 682 B all cols are LO bounded \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1992). \"Viability Analysis: A Formulation Aid for All \nClasses of Network Models\", Naval Research Logistics, Vol. 39, pp. \n531-543. \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 713`LPnetlib`lpi_ex73a`193`211`457`yes`193`1`1`0`0%`0%`integer`rectangular`no`no`Z. You`J. Chinneck`1992`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nBOX1, EX72A, EX73A: medium problems derived from research on using the \ninfeasibility version of viability analysis [Chinneck 1992] to analyze \npetri net models. All three problems are volatile, showing IISs of \nwidely differing size depending on the algorithm applied. Contributor: \nZhengping You, Carleton University. \n \nName Rows Cols Nonzeros Bounds Notes \nex73a 194 211 668 B all cols are LO bounded \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1992). \"Viability Analysis: A Formulation Aid for All \nClasses of Network Models\", Naval Research Logistics, Vol. 39, pp. \n531-543. \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 714`LPnetlib`lpi_forest6`66`131`246`yes`66`1`1`0`0%`0%`real`rectangular`no`no`H. Greenberg`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nFOREST6, WOODINFE: very small problems derived from network-based \nforestry models. The IIS in FOREST6 includes most of the rows. \nWOODINFE is the example problem discussed in detail in Greenberg [1993], \nand has a very small IIS. Contributor: H.J. Greenberg, University of \nColorado at Denver. \n \nName Rows Cols Nonzeros Bounds Notes \nforest6 67 95 270 B \n \n \nREFERENCES \n---------- \n \nH.J. Greenberg (1993). \"A Computer-Assisted Analysis System for \nMathematical Programming Models and Solutions: A User's Guide for \nANALYZE\", Kluwer Academic Publishers, Boston. \n \n | |
| 715`LPnetlib`lpi_galenet`8`14`22`yes`8`1`1`0`0%`0%`integer`rectangular`no`no`H. Greenberg`J. Chinneck`1999`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nGALENET: a very small network problem. Contributor: H.J. Greenberg, \nUniversity of Colorado at Denver. \n \nName Rows Cols Nonzeros Bounds Notes \ngalenet 9 8 16 B \n \n | |
| 716`LPnetlib`lpi_gosh`3792`13455`99953`no`3790`130`105`0`0%`0%`real`rectangular`no`no`R. Main`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nGOSH, GRAN, PANG: these very large, large, and medium size models, \nrespectively, problems arose from British Petroleum operations models. \nContributor: Roger Main, BP Oil. \n \nName Rows Cols Nonzeros Bounds Notes \ngosh 3793 10733 97257 B FR 242 free cols \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 717`LPnetlib`lpi_gran`2658`2525`20111`no`2311`1267`1243`0`0%`0%`real`rectangular`no`no`R. Main`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nGOSH, GRAN, PANG: these very large, large, and medium size models, \nrespectively, problems arose from British Petroleum operations models. \nContributor: Roger Main, BP Oil. \n \nName Rows Cols Nonzeros Bounds Notes \ngran 2569 2520 20151 B FX \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 718`LPnetlib`lpi_greenbea`2393`5596`31074`no`2390`75`9`0`0%`0%`real`rectangular`no`no`R. Fourer`R. Fourer`1988`linear programming problem`\nA Netlib LP problem, in lp/data. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n \nThe following are relevant excerpts from lp/data/readme (by David M. Gay):\n \nThe column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude \nslack and surplus columns and the right-hand side vector, but include \nthe cost row. We have omitted other free rows and all but the first \nright-hand side vector, as noted below. The byte count is for the \nMPS compressed file; it includes a newline character at the end of each \nline. These files start with a blank initial line intended to prevent \nmail programs from discarding any of the data. The BR column indicates \nwhether a problem has bounds or ranges: B stands for \"has bounds\", R \nfor \"has ranges\". The BOUND-TYPE TABLE below shows the bound types \npresent in those problems that have bounds. \n \nThe optimal value is from MINOS version 5.3 (of Sept. 1988) \nrunning on a VAX with default options. \n \n PROBLEM SUMMARY TABLE \n \nName Rows Cols Nonzeros Bytes BR Optimal Value \nGREENBEA 2393 5405 31499 235711 B -7.2462405908E+07 \n \n BOUND-TYPE TABLE \nGREENBEA UP LO FX \n \nSupplied by Bob Fourer. \nWhen included in Netlib: Extra bound sets omitted; Extra free rows \nomitted. \nEmpty RHS section. \nProblems GREENBEA and GREENBEB differ only in their BOUNDS sections. \n \nBob Bixby reports that the CPLEX solver (running on a Sparc station) \nfinds slightly different optimal values for some of the problems. \nOn a MIPS processor, MINOS version 5.3 (with crash and scaling of \nDecember 1989) also finds different optimal values for some of the \nproblems. The following table shows the values that differ from those \nshown above. (Whether CPLEX finds different values on the recently \nadded problems remains to be seen.) \n \nProblem CPLEX(Sparc) MINOS(MIPS) \nGREENBEA -7.2555248130E+07 \n \nSource: GREENBEA, GREENBEB: a large refinery model; see the book \n\"A Model-Management Framework for Mathematical Programming\" by Kenneth \nH. Palmer et al. (John Wiley & Sons, New York, 1984). \n \nAdded to Netlib on 6 May 1988 \n \n | |
| 719`LPnetlib`lpi_itest2`9`13`26`yes`9`1`1`0`0%`0%`real`rectangular`no`no`J. Chinneck, E. Dravnieks`J. Chinneck`1991`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nITEST6, ITEST2: very small problems having numerous clustered IISs. \nThese match problems 1 and 2, respectively, in Chinneck and Dravnieks \n[1991]. Contributors: J.W. Chinneck and E.W. Dravnieks, Carleton \nUniversity. \n \nName Rows Cols Nonzeros Bounds Notes \nitest2 10 4 17 \n \nREFERENCES \n---------- \n \nJ.W. Chinneck and E.W. Dravnieks (1991). \"Locating Minimal Infeasible \nConstraint Sets in Linear Programs\", ORSA Journal on Computing, Volume \n3, No. 2. \n \n | |
| 720`LPnetlib`lpi_itest6`11`17`29`yes`11`1`3`0`0%`0%`real`rectangular`no`no`J. Chinneck, E. Dravnieks`J. Chinneck`1991`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nITEST6, ITEST2: very small problems having numerous clustered IISs. \nThese match problems 1 and 2, respectively, in Chinneck and Dravnieks \n[1991]. Contributors: J.W. Chinneck and E.W. Dravnieks, Carleton \nUniversity. \n \nName Rows Cols Nonzeros Bounds Notes \nitest6 12 8 23 \n \nREFERENCES \n---------- \n \nJ.W. Chinneck and E.W. Dravnieks (1991). \"Locating Minimal Infeasible \nConstraint Sets in Linear Programs\", ORSA Journal on Computing, Volume \n3, No. 2. \n \n | |
| 721`LPnetlib`lpi_klein1`54`108`750`yes`54`1`1`0`0%`0%`integer`rectangular`no`no`E. Klotz`J. Chinneck`1999`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nKLEIN1, KLEIN2, KLEIN3: related small and medium size problems. \nContributor: Ed Klotz, CPLEX Optimization Inc. \n \nName Rows Cols Nonzeros Bounds Notes \nklein1 55 54 696 \n \n | |
| 722`LPnetlib`lpi_klein2`477`531`5062`yes`477`1`1`0`0%`0%`integer`rectangular`no`no`E. Klotz`J. Chinneck`1999`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nKLEIN1, KLEIN2, KLEIN3: related small and medium size problems. \nContributor: Ed Klotz, CPLEX Optimization Inc. \n \nName Rows Cols Nonzeros Bounds Notes \nklein2 478 54 4585 \n \n | |
| 723`LPnetlib`lpi_klein3`994`1082`13101`yes`994`1`1`0`0%`0%`integer`rectangular`no`no`E. Klotz`J. Chinneck`1999`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nKLEIN1, KLEIN2, KLEIN3: related small and medium size problems. \nContributor: Ed Klotz, CPLEX Optimization Inc. \n \nName Rows Cols Nonzeros Bounds Notes \nklein3 995 88 12107 \n \n | |
| 724`LPnetlib`lpi_mondou2`312`604`1208`yes`312`10`1`0`0%`0%`integer`rectangular`no`no`J. Mondou`J. Chinneck`1999`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nMONDOU2: medium size problem generated as a subproblem to a larger \nfacility sizing algorithm used by Hydro-Quebec. The diagnosis of the \ninfeasibility in the subproblem is useful to the larger algorithm. \nContributor: J.-F. Mondou, Hydro-Quebec. \n \nName Rows Cols Nonzeros Bounds Notes \nmondou2 313 604 1623 B \n \n | |
| 725`LPnetlib`lpi_pang`361`741`2933`yes`361`5`6`0`0%`0%`real`rectangular`no`no`R. Main`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nPROBLEM DESCRIPTION \n------------------- \n \nGOSH, GRAN, PANG: these very large, large, and medium size models, \nrespectively, problems arose from British Petroleum operations models. \nContributor: Roger Main, BP Oil. \n \nName Rows Cols Nonzeros Bounds Notes \npang 362 460 2666 B FR FX \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 726`LPnetlib`lpi_pilot4i`410`1123`5264`yes`410`9`1`0`0%`0%`real`rectangular`no`no`J. Stone`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/data \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nPILOT4I: medium size problem generated by doctoring the original NETLIB \nPILOT4 model. Contributor: John Stone, Ketron Management Science. \n \nName Rows Cols Nonzeros Bounds Notes \npilot4i 411 1000 5145 B FR FX \n \nAdded to Netlib on Sept. 19, 1993 \n \n | |
| 727`LPnetlib`lpi_qual`323`464`1646`yes`323`13`1`0`0%`0%`real`rectangular`no`no`T. Baker`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nCHEMCOM, QUAL, REFINERY, REACTOR, VOL1: medium size problems derived \nfrom a petrochemical plant model. Doctored to generate infeasibility \ndue to inability to meet volume or quality restrictions. With the \nexception of REACTOR, these are highly volatile problems, yielding IISs \nof varying sizes when different IIS isolation algorithms are applied. \nSee Chinneck [1993] for further discussion. Contributor: Tom Baker, \nChesapeake Decision Sciences. \n \nName Rows Cols Nonzeros Bounds Notes \nqual 324 464 1714 B FX \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1993). \"Finding the Most Useful Subset of Constraints \nfor Analysis in an Infeasible Linear Program\", technical report \nSCE-93-07, Systems and Computer Engineering, Carleton University, \nOttawa, Canada. \n \n | |
| 728`LPnetlib`lpi_reactor`318`808`2591`yes`318`1`1`0`0%`0%`real`rectangular`no`no`T. Baker`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nCHEMCOM, QUAL, REFINERY, REACTOR, VOL1: medium size problems derived \nfrom a petrochemical plant model. Doctored to generate infeasibility \ndue to inability to meet volume or quality restrictions. With the \nexception of REACTOR, these are highly volatile problems, yielding IISs \nof varying sizes when different IIS isolation algorithms are applied. \nSee Chinneck [1993] for further discussion. Contributor: Tom Baker, \nChesapeake Decision Sciences. \n \nName Rows Cols Nonzeros Bounds Notes \nreactor 319 637 2995 B FX \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1993). \"Finding the Most Useful Subset of Constraints \nfor Analysis in an Infeasible Linear Program\", technical report \nSCE-93-07, Systems and Computer Engineering, Carleton University, \nOttawa, Canada. \n \n | |
| 729`LPnetlib`lpi_refinery`323`464`1626`yes`323`13`2`0`0%`0%`real`rectangular`no`no`T. Baker`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nCHEMCOM, QUAL, REFINERY, REACTOR, VOL1: medium size problems derived \nfrom a petrochemical plant model. Doctored to generate infeasibility \ndue to inability to meet volume or quality restrictions. With the \nexception of REACTOR, these are highly volatile problems, yielding IISs \nof varying sizes when different IIS isolation algorithms are applied. \nSee Chinneck [1993] for further discussion. Contributor: Tom Baker, \nChesapeake Decision Sciences. \n \nName Rows Cols Nonzeros Bounds Notes \nrefinery 324 464 1694 B FX \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1993). \"Finding the Most Useful Subset of Constraints \nfor Analysis in an Infeasible Linear Program\", technical report \nSCE-93-07, Systems and Computer Engineering, Carleton University, \nOttawa, Canada. \n \n | |
| 730`LPnetlib`lpi_vol1`323`464`1646`yes`323`13`1`0`0%`0%`real`rectangular`no`no`T. Baker`J. Chinneck`1993`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nCHEMCOM, QUAL, REFINERY, REACTOR, VOL1: medium size problems derived \nfrom a petrochemical plant model. Doctored to generate infeasibility \ndue to inability to meet volume or quality restrictions. With the \nexception of REACTOR, these are highly volatile problems, yielding IISs \nof varying sizes when different IIS isolation algorithms are applied. \nSee Chinneck [1993] for further discussion. Contributor: Tom Baker, \nChesapeake Decision Sciences. \n \nName Rows Cols Nonzeros Bounds Notes \nvol1 324 464 1714 B FX \n \n \nREFERENCES \n---------- \n \nJ.W. Chinneck (1993). \"Finding the Most Useful Subset of Constraints \nfor Analysis in an Infeasible Linear Program\", technical report \nSCE-93-07, Systems and Computer Engineering, Carleton University, \nOttawa, Canada. \n \n | |
| 731`LPnetlib`lpi_woodinfe`35`89`140`yes`35`3`6`0`0%`0%`integer`rectangular`no`no`H. Greenberg`J. Chinneck`1989`linear programming problem`\nAn infeasible Netlib LP problem, in lp/infeas. For more information \nsend email to netlib@ornl.gov with the message: \n \n send index from lp \n send readme from lp/infeas \n \nThe lp/infeas directory contains infeasible linear programming test problems\ncollected by John W. Chinneck, Carleton Univ, Ontario Canada. The following\nare relevant excerpts from lp/infeas/readme (by John W. Chinneck): \n \nIn the following, IIS stands for Irreducible Infeasible Subsystem, a set \nof constraints which is itself infeasible, but becomes feasible when any \none member is removed. Isolating an IIS from within the larger set of \nconstraints defining the model is one analysis approach. \n \nPROBLEM DESCRIPTION \n------------------- \n \nFOREST6, WOODINFE: very small problems derived from network-based \nforestry models. The IIS in FOREST6 includes most of the rows. \nWOODINFE is the example problem discussed in detail in Greenberg [1993], \nand has a very small IIS. Contributor: H.J. Greenberg, University of \nColorado at Denver. \n \nName Rows Cols Nonzeros Bounds Notes \nwoodinfe 36 89 209 B \n \n \nREFERENCES \n---------- \n \nH.J. Greenberg (1993). \"A Computer-Assisted Analysis System for \nMathematical Programming Models and Solutions: A User's Guide for \nANALYZE\", Kluwer Academic Publishers, Boston. \n \n | |
| 732`Li`li`22695`22695`1215181`yes`22695`4`4`135128`symmetric`87%`real`unsymmetric`no`no`B. Li`T. Davis`1999`electromagnetics problem` | |
| 733`Li`pli`22695`22695`1350309`yes`22695`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`B. Li`T. Davis`1999`duplicate electromagnetics problem`\nnonzero pattern of Li/li\n | |
| 734`Mallya`lhr01`1477`1477`18427`yes`1477`298`21`165`1%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 735`Mallya`lhr02`2954`2954`36875`yes`2954`596`42`331`1%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 736`Mallya`lhr04`4101`4101`81057`yes`4101`443`31`1625`2%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 737`Mallya`lhr04c`4101`4101`82682`yes`4101`439`31`0`2%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1997`chemical process simulation problem` | |
| 738`Mallya`lhr07`7337`7337`154660`yes`7337`676`31`1848`2%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 739`Mallya`lhr07c`7337`7337`156508`yes`7337`672`31`0`2%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1997`chemical process simulation problem` | |
| 740`Mallya`lhr10`10672`10672`228395`yes`10672`912`31`4238`1%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 741`Mallya`lhr10c`10672`10672`232633`yes`10672`908`31`0`1%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1997`chemical process simulation problem` | |
| 742`Mallya`lhr11`10964`10964`231806`yes`10964`1200`31`1935`1%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 743`Mallya`lhr11c`10964`10964`233741`yes`10964`1192`31`0`1%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1997`chemical process simulation problem` | |
| 744`Mallya`lhr14`14270`14270`305750`yes`14270`1564`31`2108`1%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 745`Mallya`lhr14c`14270`14270`307858`yes`14270`1556`31`0`1%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1997`chemical process simulation problem` | |
| 746`Mallya`lhr17`17576`17576`379761`yes`17576`1807`31`2214`0%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 747`Mallya`lhr17c`17576`17576`381975`yes`17576`1798`31`0`0%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1997`chemical process simulation problem` | |
| 748`Mallya`lhr34`35152`35152`746972`yes`35152`7985`61`17042`0%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 749`Mallya`lhr34c`35152`35152`764014`yes`35152`3533`61`0`0%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1997`chemical process simulation problem` | |
| 750`Mallya`lhr71`70304`70304`1494006`yes`70304`15970`121`34086`0%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1994`chemical process simulation problem` | |
| 751`Mallya`lhr71c`70304`70304`1528092`yes`70304`7066`121`0`0%`0%`real`unsymmetric`no`no`J. Mallya`T. Davis`1997`chemical process simulation problem` | |
| 752`Mulvey`finan512`74752`74752`596992`yes`74752`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Berger, J. Mulvey, E. Rothberg, R. Vanderbei`E. Rothberg`1997`economic problem` | |
| 753`Mulvey`pfinan512`74752`74752`596992`yes`74752`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Berger, J. Mulvey, E. Rothberg, R. Vanderbei`E. Rothberg`1997`duplicate economic problem`\nThis matrix is the nonzero pattern of Mulvey/finan512\n | |
| 754`Nasa`barth`6691`6691`26439`yes`6691`981`981`0`0%`0%`binary`unsymmetric`no`no`NASA`G. Kumfert, A. Pothen`1995`duplicate structural problem`\nLet A=Nasa/barth, then Pothen/barth = spones(A+A') with xyz coord.\n | |
| 755`Nasa`barth4`6019`6019`23492`yes`6019`33`33`0`0%`0%`binary`unsymmetric`no`no`NASA`G. Kumfert, A. Pothen`1995`duplicate structural problem`\nLet A=Nasa/barth4, then Pothen/barth4 = spones(A+A') with xyz coord.\n | |
| 756`Nasa`barth5`15606`15606`61484`yes`15606`1155`1155`0`0%`0%`binary`unsymmetric`no`no`NASA`G. Kumfert, A. Pothen`1995`duplicate structural problem`\nLet A=Nasa/barth5, then Pothen/barth5 = spones(A+A') with xyz coord.\n | |
| 757`Nasa`nasa1824`1824`1824`39208`yes`1824`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`1995`structural problem` | |
| 758`Nasa`nasa2146`2146`2146`72250`yes`2146`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`1995`structural problem` | |
| 759`Nasa`nasa2910`2910`2910`174296`yes`2910`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`1995`structural problem` | |
| 760`Nasa`nasa4704`4704`4704`104756`yes`4704`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`1995`structural problem` | |
| 761`Nasa`nasasrb`54870`54870`2677324`yes`54870`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`1995`structural problem` | |
| 762`Nasa`pwt`36519`36519`326107`yes`36519`57`57`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`1995`duplicate structural problem`\nNasa/pwt, GHS_psdef/pwt and Pothen/pwt are identical; Pothen/ has xyz coord.\n | |
| 763`Nasa`shuttle_eddy`10429`10429`103599`yes`10429`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`1995`duplicate structural problem`\nIdentical to Pothen/shuttle_eddy; the latter has xyz coordinates.\n | |
| 764`Nasa`skirt`12598`12598`196520`yes`12598`7`7`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`1995`duplicate structural problem`\nIdentical to Pothen/skirt; the latter has xyz coordinates.\n | |
| 765`Nemeth`nemeth01`9506`9506`725054`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`theoretical/quantum chemistry problem sequence`\nnext: Nemeth/nemeth02 first: Nemeth/nemeth01\n | |
| 766`Nemeth`nemeth02`9506`9506`394808`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth03 first: Nemeth/nemeth01\n | |
| 767`Nemeth`nemeth03`9506`9506`394808`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth04 first: Nemeth/nemeth01\n | |
| 768`Nemeth`nemeth04`9506`9506`394808`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth05 first: Nemeth/nemeth01\n | |
| 769`Nemeth`nemeth05`9506`9506`394808`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth06 first: Nemeth/nemeth01\n | |
| 770`Nemeth`nemeth06`9506`9506`394808`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth07 first: Nemeth/nemeth01\n | |
| 771`Nemeth`nemeth07`9506`9506`394812`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth08 first: Nemeth/nemeth01\n | |
| 772`Nemeth`nemeth08`9506`9506`394816`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth09 first: Nemeth/nemeth01\n | |
| 773`Nemeth`nemeth09`9506`9506`395506`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth10 first: Nemeth/nemeth01\n | |
| 774`Nemeth`nemeth10`9506`9506`401448`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth11 first: Nemeth/nemeth01\n | |
| 775`Nemeth`nemeth11`9506`9506`408264`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth12 first: Nemeth/nemeth01\n | |
| 776`Nemeth`nemeth12`9506`9506`446818`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth13 first: Nemeth/nemeth01\n | |
| 777`Nemeth`nemeth13`9506`9506`474472`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth14 first: Nemeth/nemeth01\n | |
| 778`Nemeth`nemeth14`9506`9506`496144`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth15 first: Nemeth/nemeth01\n | |
| 779`Nemeth`nemeth15`9506`9506`539802`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth16 first: Nemeth/nemeth01\n | |
| 780`Nemeth`nemeth16`9506`9506`587012`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth17 first: Nemeth/nemeth01\n | |
| 781`Nemeth`nemeth17`9506`9506`629620`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth18 first: Nemeth/nemeth01\n | |
| 782`Nemeth`nemeth18`9506`9506`695234`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth19 first: Nemeth/nemeth01\n | |
| 783`Nemeth`nemeth19`9506`9506`818302`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth20 first: Nemeth/nemeth01\n | |
| 784`Nemeth`nemeth20`9506`9506`971870`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth21 first: Nemeth/nemeth01\n | |
| 785`Nemeth`nemeth21`9506`9506`1173746`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth22 first: Nemeth/nemeth01\n | |
| 786`Nemeth`nemeth22`9506`9506`1358832`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth23 first: Nemeth/nemeth01\n | |
| 787`Nemeth`nemeth23`9506`9506`1506810`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth24 first: Nemeth/nemeth01\n | |
| 788`Nemeth`nemeth24`9506`9506`1506550`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth25 first: Nemeth/nemeth01\n | |
| 789`Nemeth`nemeth25`9506`9506`1511758`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: Nemeth/nemeth26 first: Nemeth/nemeth01\n | |
| 790`Nemeth`nemeth26`9506`9506`1511760`yes`9506`1`1`0`symmetric`symmetric`real`symmetric`no`no`K. Nemeth`T. Davis`1999`subsequent theoretical/quantum chemistry problem`\nnext: - first: Nemeth/nemeth01\n | |
| 791`Okunbor`aft01`8205`8205`125567`yes`8205`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`W. Eversman, D. Okunbor`T. Davis`2001`acoustics problem` | |
| 792`Okunbor`aft02`8184`8184`127762`yes`8184`1`1`0`symmetric`100%`complex`unsymmetric`no`no`W. Eversman, D. Okunbor`T. Davis`2001`acoustics problem` | |
| 793`Qaplib`lp_nug05`210`225`1050`yes`210`1`1`0`0%`0%`integer`rectangular`no`no`M. Resende`M. Resende`1995`linear programming problem` | |
| 794`Qaplib`lp_nug06`372`486`2232`yes`372`1`1`0`0%`0%`integer`rectangular`no`no`M. Resende`M. Resende`1995`linear programming problem` | |
| 795`Qaplib`lp_nug07`602`931`4214`yes`602`1`1`0`0%`0%`integer`rectangular`no`no`M. Resende`M. Resende`1995`linear programming problem` | |
| 796`Qaplib`lp_nug08`912`1632`7296`yes`912`1`1`0`0%`0%`integer`rectangular`no`no`M. Resende`M. Resende`1995`linear programming problem` | |
| 797`Qaplib`lp_nug12`3192`8856`38304`yes`3192`1`1`0`0%`0%`integer`rectangular`no`no`M. Resende`M. Resende`1995`linear programming problem` | |
| 798`Qaplib`lp_nug15`6330`22275`94950`yes`6330`1`1`0`0%`0%`integer`rectangular`no`no`M. Resende`M. Resende`1995`linear programming problem` | |
| 799`Qaplib`lp_nug20`15240`72600`304800`yes`15240`1`1`0`0%`0%`integer`rectangular`no`no`M. Resende`M. Resende`1995`linear programming problem` | |
| 800`Qaplib`lp_nug30`52260`379350`1567800`yes`52260`1`1`0`0%`0%`integer`rectangular`no`no`M. Resende`M. Resende`1995`linear programming problem` | |
| 801`Ronis`xenon1`48600`48600`1181120`yes`48600`31`31`0`symmetric`78%`real`unsymmetric`no`no`D. Ronis`T. Davis`2001`materials problem` | |
| 802`Ronis`xenon2`157464`157464`3866688`yes`157464`55`55`0`symmetric`78%`real`unsymmetric`no`no`D. Ronis`T. Davis`2001`materials problem` | |
| 803`Rothberg`3dtube`45330`45330`3213618`yes`45330`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`E. Rothberg`T. Davis`1997`computational fluid dynamics problem` | |
| 804`Rothberg`cfd1`70656`70656`1825580`yes`70656`1`1`2784`symmetric`symmetric`real`symmetric`yes`yes`E. Rothberg`T. Davis`1997`computational fluid dynamics problem` | |
| 805`Rothberg`cfd2`123440`123440`3085406`yes`123440`1`1`2492`symmetric`symmetric`real`symmetric`yes`yes`E. Rothberg`T. Davis`1997`computational fluid dynamics problem` | |
| 806`Rothberg`gearbox`153746`153746`9080404`yes`153746`6`6`0`symmetric`symmetric`binary`symmetric`yes`no`E. Rothberg`T. Davis`1997`structural problem` | |
| 807`Rothberg`struct3`53570`53570`1173694`yes`53570`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`E. Rothberg`T. Davis`1997`structural problem` | |
| 808`Rothberg`struct4`4350`4350`237798`yes`4350`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`E. Rothberg`T. Davis`1997`structural problem` | |
| 809`Shyy`shyy161`76480`76480`329762`yes`76480`25761`321`0`73%`18%`real`unsymmetric`no`no`W. Shyy`T. Davis`1994`computational fluid dynamics problem` | |
| 810`Shyy`shyy41`4720`4720`20042`yes`4720`1641`81`0`72%`18%`real`unsymmetric`no`no`W. Shyy`T. Davis`1994`computational fluid dynamics problem` | |
| 811`Simon`appu`14000`14000`1853104`unknown`unknown`unknown`1`0`symmetric`94%`real`unsymmetric`no`no`H. Simon`H. Simon`1993`directed weighted random graph` | |
| 812`Simon`bbmat`38744`38744`1771722`yes`38744`1`1`0`53%`0%`real`unsymmetric`no`no`H. Simon`H. Simon`1993`computational fluid dynamics problem` | |
| 813`Simon`olafu`16146`16146`1015156`yes`16146`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`H. Simon`H. Simon`1993`structural problem` | |
| 814`Simon`raefsky1`3242`3242`293409`yes`3242`1`1`867`symmetric`9%`real`unsymmetric`no`no`A. Raefsky`H. Simon`1993`computational fluid dynamics problem sequence`\nnext: Simon/raefsky2 first: Simon/raefsky1\n | |
| 815`Simon`raefsky2`3242`3242`293551`yes`3242`1`1`725`symmetric`10%`real`unsymmetric`no`no`A. Raefsky`H. Simon`1993`subsequent computational fluid dynamics problem`\nnext: - first: Simon/raefsky1\n | |
| 816`Simon`raefsky3`21200`21200`1488768`yes`21200`1`1`0`symmetric`48%`real`unsymmetric`no`no`A. Raefsky`H. Simon`1993`computational fluid dynamics problem` | |
| 817`Simon`raefsky4`19779`19779`1316789`yes`19779`1`1`11822`symmetric`symmetric`real`symmetric`yes`yes`A. Raefsky`H. Simon`1993`structural problem` | |
| 818`Simon`raefsky5`6316`6316`167178`yes`6316`6316`6316`1480`0%`0%`real`unsymmetric`no`no`A. Raefsky`H. Simon`1993`structural problem` | |
| 819`Simon`raefsky6`3402`3402`130371`yes`3402`3402`3402`7474`0%`0%`real`unsymmetric`no`no`A. Raefsky`H. Simon`1993`structural problem` | |
| 820`Simon`venkat01`62424`62424`1717792`yes`62424`1`1`0`symmetric`6%`real`unsymmetric`no`no`V. Venkatakrishnan`H. Simon`1993`computational fluid dynamics problem sequence`\nnext: Simon/venkat25 first: Simon/venkat01\n | |
| 821`Simon`venkat25`62424`62424`1717763`yes`62424`1`1`29`symmetric`6%`real`unsymmetric`no`no`V. Venkatakrishnan`H. Simon`1993`subsequent computational fluid dynamics problem`\nnext: Simon/venkat50 first: Simon/venkat01\n | |
| 822`Simon`venkat50`62424`62424`1717777`yes`62424`1`1`15`symmetric`6%`real`unsymmetric`no`no`V. Venkatakrishnan`H. Simon`1993`subsequent computational fluid dynamics problem`\nnext: - first: Simon/venkat01\n | |
| 823`TOKAMAK`utm1700b`1700`1700`21509`yes`1700`83`83`0`52%`0%`real`unsymmetric`no`no`Y. Saad`Y. Saad`1996`electromagnetics problem` | |
| 824`TOKAMAK`utm300`300`300`3155`yes`300`31`31`0`47%`0%`real`unsymmetric`no`no`Y. Saad`Y. Saad`1996`electromagnetics problem` | |
| 825`TOKAMAK`utm3060`3060`3060`42211`yes`3060`83`83`0`52%`0%`real`unsymmetric`no`no`Y. Saad`Y. Saad`1996`electromagnetics problem` | |
| 826`TOKAMAK`utm5940`5940`5940`83842`yes`5940`147`147`0`53%`0%`real`unsymmetric`no`no`Y. Saad`Y. Saad`1996`electromagnetics problem` | |
| 827`Vavasis`av41092`41092`41092`1683902`yes`41092`4`4`0`0%`0%`real`unsymmetric`no`no`S. Vavasis`S. Li`1994`2D/3D problem` | |
| 828`Wang`swang1`3169`3169`20841`yes`3169`1`1`0`symmetric`0%`real`unsymmetric`no`no`S. Wang`T. Davis`1994`semiconductor device problem sequence`\nnext: Wang/swang2 first: Wang/swang1\n | |
| 829`Wang`swang2`3169`3169`20841`yes`3169`1`1`0`symmetric`0%`real`unsymmetric`no`no`S. Wang`T. Davis`1994`subsequent semiconductor device problem`\nnext: - first: Wang/swang1\n | |
| 830`Wang`wang1`2903`2903`19093`yes`2903`1`1`0`symmetric`81%`real`unsymmetric`no`no`S. Wang`T. Davis`1994`semiconductor device problem sequence`\nnext: Wang/wang2 first: Wang/wang1\n | |
| 831`Wang`wang2`2903`2903`19093`yes`2903`1`1`0`symmetric`81%`real`unsymmetric`no`no`S. Wang`T. Davis`1994`subsequent semiconductor device problem`\nnext: - first: Wang/wang1\n | |
| 832`Wang`wang3`26064`26064`177168`yes`26064`1`1`0`symmetric`98%`real`unsymmetric`no`no`S. Wang`T. Davis`1994`semiconductor device problem` | |
| 833`Wang`wang4`26068`26068`177196`yes`26068`1`1`0`symmetric`5%`real`unsymmetric`no`no`S. Wang`T. Davis`1994`semiconductor device problem` | |
| 834`Zhao`Zhao1`33861`33861`166453`yes`33861`1`1`0`92%`0%`real`unsymmetric`no`no`L. Zhao`T. Davis`2001`electromagnetics problem` | |
| 835`Zhao`Zhao2`33861`33861`166453`yes`33861`1`1`0`92%`0%`real`unsymmetric`no`no`L. Zhao`T. Davis`2001`electromagnetics problem` | |
| 836`Zitney`extr1`2837`2837`10967`yes`2837`880`1`440`0%`0%`real`unsymmetric`no`no`S. Zitney`T. Davis`1997`chemical process simulation problem` | |
| 837`Zitney`hydr1`5308`5308`22680`yes`5308`1076`1`1072`0%`0%`real`unsymmetric`no`no`S. Zitney`T. Davis`1997`chemical process simulation problem` | |
| 838`Zitney`radfr1`1048`1048`13299`yes`1048`98`2`0`5%`0%`real`unsymmetric`no`no`S. Zitney`T. Davis`1997`chemical process simulation problem` | |
| 839`Zitney`rdist1`4134`4134`94408`yes`4134`199`2`0`6%`0%`real`unsymmetric`no`no`S. Zitney`T. Davis`1992`chemical process simulation problem` | |
| 840`Zitney`rdist2`3198`3198`56834`yes`3198`199`2`100`5%`0%`real`unsymmetric`no`no`S. Zitney`T. Davis`1992`chemical process simulation problem` | |
| 841`Zitney`rdist3a`2398`2398`61896`yes`2398`99`2`0`14%`0%`real`unsymmetric`no`no`S. Zitney`T. Davis`1992`chemical process simulation problem` | |
| 842`Cunningham`k3plates`11107`11107`378927`yes`11107`1`1`0`symmetric`100%`real`unsymmetric`no`no`A. Cunningham`T. Davis`2002`acoustics problem` | |
| 843`Cunningham`m3plates`11107`11107`6639`no`6639`6641`11107`0`symmetric`symmetric`real`symmetric`no`no`A. Cunningham`T. Davis`2002`acoustics problem` | |
| 844`Cunningham`qa8fk`66127`66127`1660579`yes`66127`1`1`0`symmetric`symmetric`real`symmetric`yes`no`A. Cunningham`T. Davis`2002`acoustics problem` | |
| 845`Cunningham`qa8fm`66127`66127`1660579`yes`66127`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Cunningham`T. Davis`2002`acoustics problem` | |
| 846`Boeing`bcsstk39`46772`46772`2060662`yes`46772`1`1`28632`symmetric`symmetric`real`symmetric`yes`no`R. Grimes`T. Davis`2002`structural problem` | |
| 847`Chen`pkustk01`22044`22044`979380`yes`22044`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 848`Chen`pkustk02`10800`10800`810000`yes`10800`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 849`Chen`pkustk03`63336`63336`3130416`yes`63336`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 850`Chen`pkustk04`55590`55590`4218660`yes`55590`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 851`Chen`pkustk05`37164`37164`2205144`yes`37164`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 852`Chen`pkustk06`43164`43164`2571768`yes`43164`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 853`Chen`pkustk07`16860`16860`2418804`yes`16860`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 854`Chen`pkustk08`22209`22209`3226671`yes`22209`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 855`Chen`pkustk09`33960`33960`1583640`yes`33960`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 856`Chen`pkustk10`80676`80676`4308984`yes`80676`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 857`Chen`pkustk11`87804`87804`5217912`yes`87804`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 858`Chen`pkustk12`94653`94653`7512317`yes`94653`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 859`Chen`pkustk13`94893`94893`6616827`yes`94893`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 860`Chen`pkustk14`151926`151926`14836504`yes`151926`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`P. Chen`T. Davis`2002`structural problem` | |
| 861`MathWorks`pivtol`102`102`306`yes`102`1`1`0`99%`0%`real`unsymmetric`no`no`B. Cheng`T. Davis`2002`statistical/mathematical problem` | |
| 862`Kim`kim1`38415`38415`933195`yes`38415`1`1`0`99%`0%`complex`unsymmetric`no`no`W. Kim`T. Davis`2002`2D/3D problem` | |
| 863`Kim`kim2`456976`456976`11330020`yes`456976`1`1`0`100%`0%`complex`unsymmetric`no`no`W. Kim`T. Davis`2002`2D/3D problem` | |
| 864`Langemyr`comsol`1500`1500`97645`yes`1500`1`1`0`100%`0%`real`unsymmetric`no`no`L. Langemyr`T. Davis`2002`structural problem` | |
| 865`Pothen`barth`6691`6691`46187`yes`6691`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 866`Pothen`barth4`6019`6019`40965`yes`6019`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 867`Pothen`barth5`15606`15606`107362`yes`15606`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 868`Pothen`bodyy4`17546`17546`121550`yes`17546`1`1`388`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 869`Pothen`bodyy5`18589`18589`128853`yes`18589`1`1`428`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 870`Pothen`bodyy6`19366`19366`134208`yes`19366`1`1`540`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 871`Pothen`commanche_dual`7920`7920`31680`yes`7920`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 872`Pothen`mesh1e1`48`48`306`yes`48`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 873`Pothen`mesh1em1`48`48`306`yes`48`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 874`Pothen`mesh1em6`48`48`306`yes`48`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 875`Pothen`mesh2e1`306`306`2018`yes`306`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 876`Pothen`mesh2em5`306`306`2018`yes`306`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 877`Pothen`mesh3e1`289`289`1377`yes`289`1`1`512`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 878`Pothen`mesh3em5`289`289`1377`yes`289`1`1`512`symmetric`symmetric`real`symmetric`yes`yes`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 879`Pothen`onera_dual`85567`85567`419201`yes`85567`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 880`Pothen`pwt`36519`36519`326107`yes`36519`57`57`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 881`Pothen`shuttle_eddy`10429`10429`103599`yes`10429`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 882`Pothen`skirt`12598`12598`196520`yes`12598`7`7`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 883`Pothen`sphere2`66`66`450`yes`66`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 884`Pothen`sphere3`258`258`1794`yes`258`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 885`Pothen`tandem_dual`94069`94069`460493`yes`94069`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 886`Pothen`tandem_vtx`18454`18454`253350`yes`18454`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`2003`structural problem` | |
| 887`Norris`fv1`9604`9604`85264`yes`9604`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`S. Norris`T. Davis`2003`2D/3D problem` | |
| 888`Norris`fv2`9801`9801`87025`yes`9801`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`S. Norris`T. Davis`2003`2D/3D problem` | |
| 889`Norris`fv3`9801`9801`87025`yes`9801`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`S. Norris`T. Davis`2003`2D/3D problem` | |
| 890`Norris`heart1`3557`3557`1385317`yes`3557`1`1`2456`symmetric`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`2D/3D problem` | |
| 891`Norris`heart2`2339`2339`680341`yes`2339`1`1`2456`symmetric`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`2D/3D problem` | |
| 892`Norris`heart3`2339`2339`680341`yes`2339`1`1`2456`symmetric`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`2D/3D problem` | |
| 893`Norris`lung1`1650`1650`7419`yes`1650`2`2`0`57%`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`computational fluid dynamics problem` | |
| 894`Norris`lung2`109460`109460`492564`yes`109460`2`2`0`57%`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`computational fluid dynamics problem` | |
| 895`Norris`stomach`213360`213360`3021648`yes`213360`1`1`0`85%`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`2D/3D problem` | |
| 896`Norris`torso1`116158`116158`8516500`yes`116158`1`1`0`42%`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`2D/3D problem` | |
| 897`Norris`torso2`115967`115967`1033473`yes`115967`1`1`0`99%`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`2D/3D problem` | |
| 898`Norris`torso3`259156`259156`4429042`yes`259156`1`1`0`95%`0%`real`unsymmetric`no`no`S. Norris`T. Davis`2003`2D/3D problem` | |
| 899`Shen`e40r0100`17281`17281`553562`yes`17281`1`1`0`31%`0%`real`unsymmetric`no`no`K. Shen`T. Davis`2003`2D/3D problem` | |
| 900`Shen`shermanACa`3432`3432`25220`yes`3432`59`59`0`16%`2%`real`unsymmetric`no`no`K. Shen`T. Davis`2003`2D/3D problem` | |
| 901`Shen`shermanACb`18510`18510`145149`yes`18510`851`851`0`15%`3%`real`unsymmetric`no`no`K. Shen`T. Davis`2003`2D/3D problem` | |
| 902`Shen`shermanACd`6136`6136`53329`yes`6136`92`92`0`15%`2%`real`unsymmetric`no`no`K. Shen`T. Davis`2003`2D/3D problem` | |
| 903`Pereyra`landmark`71952`2704`1146848`no`2673`5`32`4384`0%`0%`real`rectangular`no`no`V. Pereyra`T. Davis`2003`least squares problem` | |
| 904`vanHeukelum`cage3`5`5`19`unknown`unknown`unknown`1`0`symmetric`0%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 905`vanHeukelum`cage4`9`9`49`unknown`unknown`unknown`1`0`symmetric`0%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 906`vanHeukelum`cage5`37`37`233`unknown`unknown`unknown`1`0`symmetric`4%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 907`vanHeukelum`cage6`93`93`785`unknown`unknown`unknown`1`0`symmetric`9%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 908`vanHeukelum`cage7`340`340`3084`unknown`unknown`unknown`1`0`symmetric`10%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 909`vanHeukelum`cage8`1015`1015`11003`unknown`unknown`unknown`1`0`symmetric`14%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 910`vanHeukelum`cage9`3534`3534`41594`unknown`unknown`unknown`1`0`symmetric`15%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 911`vanHeukelum`cage10`11397`11397`150645`unknown`unknown`unknown`1`0`symmetric`17%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 912`vanHeukelum`cage11`39082`39082`559722`unknown`unknown`unknown`1`0`symmetric`18%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 913`vanHeukelum`cage12`130228`130228`2032536`unknown`unknown`unknown`1`0`symmetric`19%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 914`vanHeukelum`cage13`445315`445315`7479343`unknown`unknown`unknown`1`0`symmetric`20%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 915`vanHeukelum`cage14`1505785`1505785`27130349`unknown`unknown`unknown`1`0`symmetric`21%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 916`vanHeukelum`cage15`5154859`5154859`99199551`yes`5154859`1`1`0`symmetric`21%`real`unsymmetric`no`no`A. van Heukelum`T. Davis`2003`directed weighted graph` | |
| 917`Hohn`fd12`7500`7500`28462`yes`7500`713`1`0`0%`0%`real`unsymmetric`no`no`M. Hohn`T. Davis`2003`materials problem` | |
| 918`Hohn`fd15`11532`11532`44206`yes`11532`887`1`0`0%`0%`real`unsymmetric`no`no`M. Hohn`T. Davis`2003`materials problem` | |
| 919`Hohn`fd18`16428`16428`63406`yes`16428`1061`1`0`0%`0%`real`unsymmetric`no`no`M. Hohn`T. Davis`2003`materials problem` | |
| 920`Hohn`sinc12`7500`7500`283992`yes`7500`527`1`10994`2%`0%`real`unsymmetric`no`no`M. Hohn`T. Davis`2003`materials problem` | |
| 921`Hohn`sinc15`11532`11532`551184`yes`11532`653`1`17342`1%`0%`real`unsymmetric`no`no`M. Hohn`T. Davis`2003`materials problem` | |
| 922`Hohn`sinc18`16428`16428`948696`yes`16428`779`1`25130`1%`0%`real`unsymmetric`no`no`M. Hohn`T. Davis`2003`materials problem` | |
| 923`Alemdar`Alemdar`6245`6245`42581`yes`6245`6`6`0`symmetric`symmetric`integer`symmetric`yes`no`B. Alemdar`T. Davis`2003`2D/3D problem` | |
| 924`Andrews`Andrews`60000`60000`760154`yes`60000`1`1`0`symmetric`symmetric`integer`symmetric`yes`yes`S. Andrews`T. Davis`2003`computer graphics/vision problem` | |
| 925`FEMLAB`ns3Da`20414`20414`1679599`yes`20414`1`1`0`100%`0%`real`unsymmetric`no`no`COMSOL`T. Davis`2003`computational fluid dynamics problem` | |
| 926`FEMLAB`poisson2D`367`367`2417`yes`367`1`1`0`symmetric`0%`real`unsymmetric`no`no`COMSOL`T. Davis`2003`computational fluid dynamics problem` | |
| 927`FEMLAB`poisson3Da`13514`13514`352762`yes`13514`1`1`0`symmetric`0%`real`unsymmetric`no`no`COMSOL`T. Davis`2003`computational fluid dynamics problem` | |
| 928`FEMLAB`poisson3Db`85623`85623`2374949`yes`85623`1`1`0`symmetric`0%`real`unsymmetric`no`no`COMSOL`T. Davis`2003`computational fluid dynamics problem` | |
| 929`FEMLAB`problem1`415`415`2779`yes`415`1`1`0`symmetric`65%`real`unsymmetric`no`no`COMSOL`T. Davis`2003`2D/3D problem` | |
| 930`FEMLAB`sme3Da`12504`12504`874887`yes`12504`1`1`0`100%`44%`real`unsymmetric`no`no`COMSOL`T. Davis`2003`structural problem` | |
| 931`FEMLAB`sme3Db`29067`29067`2081063`yes`29067`1`1`0`100%`44%`real`unsymmetric`no`no`COMSOL`T. Davis`2003`structural problem` | |
| 932`FEMLAB`sme3Dc`42930`42930`3148656`yes`42930`1`1`0`100%`44%`real`unsymmetric`no`no`COMSOL`T. Davis`2003`structural problem` | |
| 933`FEMLAB`waveguide3D`21036`21036`303468`yes`21036`1`1`0`symmetric`0%`complex`unsymmetric`no`no`COMSOL`T. Davis`2003`electromagnetics problem` | |
| 934`Lucifora`cell1`7055`7055`30082`unknown`unknown`unknown`1`4773`100%`0%`real`unsymmetric`no`no`S. Lucifora`T. Davis`2003`directed weighted graph` | |
| 935`Lucifora`cell2`7055`7055`30082`unknown`unknown`unknown`1`4773`100%`0%`real`unsymmetric`no`no`S. Lucifora`T. Davis`2003`directed weighted graph` | |
| 936`ND`nd3k`9000`9000`3279690`yes`9000`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`author unknown`T. Davis`2003`2D/3D problem` | |
| 937`ND`nd6k`18000`18000`6897316`yes`18000`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`author unknown`T. Davis`2003`2D/3D problem` | |
| 938`ND`nd12k`36000`36000`14220946`yes`36000`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`author unknown`T. Davis`2003`2D/3D problem` | |
| 939`ND`nd24k`72000`72000`28715634`yes`72000`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`author unknown`T. Davis`2003`2D/3D problem` | |
| 940`Schenk_AFE`af_shell1`504855`504855`17562051`yes`504855`1`1`26824`symmetric`symmetric`real`symmetric`yes`no`AutoForm Eng.`O. Schenk`2003`structural problem sequence`\nnext: Schenk_AFE/af_shell2 first: Schenk_AFE/af_shell1\n | |
| 941`Schenk_AFE`af_shell2`504855`504855`17562051`yes`504855`1`1`26824`symmetric`symmetric`real`symmetric`yes`no`AutoForm Eng.`O. Schenk`2003`subsequent structural problem`\nnext: Schenk_AFE/af_shell3 first: Schenk_AFE/af_shell1\n | |
| 942`Schenk_AFE`af_shell3`504855`504855`17562051`yes`504855`1`1`26824`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2003`subsequent structural problem`\nnext: Schenk_AFE/af_shell4 first: Schenk_AFE/af_shell1\n | |
| 943`Schenk_AFE`af_shell4`504855`504855`17562051`yes`504855`1`1`26824`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2003`subsequent structural problem`\nnext: Schenk_AFE/af_shell5 first: Schenk_AFE/af_shell1\n | |
| 944`Schenk_AFE`af_shell5`504855`504855`17579155`yes`504855`1`1`9720`symmetric`symmetric`real`symmetric`yes`no`AutoForm Eng.`O. Schenk`2003`subsequent structural problem`\nnext: Schenk_AFE/af_shell6 first: Schenk_AFE/af_shell1\n | |
| 945`Schenk_AFE`af_shell6`504855`504855`17579155`yes`504855`1`1`9720`symmetric`symmetric`real`symmetric`yes`no`AutoForm Eng.`O. Schenk`2003`subsequent structural problem`\nnext: Schenk_AFE/af_shell7 first: Schenk_AFE/af_shell1\n | |
| 946`Schenk_AFE`af_shell7`504855`504855`17579155`yes`504855`1`1`9720`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2003`subsequent structural problem`\nnext: Schenk_AFE/af_shell8 first: Schenk_AFE/af_shell1\n | |
| 947`Schenk_AFE`af_shell8`504855`504855`17579155`yes`504855`1`1`9720`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2003`subsequent structural problem`\nnext: Schenk_AFE/af_shell9 first: Schenk_AFE/af_shell1\n | |
| 948`Schenk_AFE`af_shell9`504855`504855`17588845`yes`504855`1`1`30`symmetric`symmetric`real`symmetric`yes`no`AutoForm Eng.`O. Schenk`2003`subsequent structural problem`\nnext: - first: Schenk_AFE/af_shell1\n | |
| 949`Schenk_IBMNA`c-62`41731`41731`559341`yes`41731`2`2`2`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2003`optimization problem sequence`\nnext: GHS_indef/c-62ghs first: Schenk_IBMNA/c-62 \nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 950`Schenk_IBMNA`c-64`51035`51035`707985`yes`51035`1`1`9856`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2003`optimization problem sequence`\nnext: Schenk_IBMNA/c-64b first: Schenk_IBMNA/c-64\n | |
| 951`Schenk_IBMNA`c-66`49989`49989`444853`yes`49989`6`6`54154`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2003`optimization problem sequence`\nnext: Schenk_IBMNA/c-66b first: Schenk_IBMNA/c-66\n | |
| 952`Schenk_IBMNA`c-67`57975`57975`530229`yes`57975`342`342`1706`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2003`optimization problem sequence`\nnext: Schenk_IBMNA/c-67b first: Schenk_IBMNA/c-67\n | |
| 953`Schenk_IBMNA`c-73`169422`169422`1279274`yes`169422`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2003`optimization problem sequence`\nnext: Schenk_IBMNA/c-73b first: Schenk_IBMNA/c-73\n | |
| 954`Schenk_IBMSDS`2D_27628_bjtcai`27628`27628`206670`yes`27628`6361`6361`236228`100%`22%`real`unsymmetric`no`no`IBM`O. Schenk`2003`semiconductor device problem` | |
| 955`Schenk_IBMSDS`2D_54019_highK`54019`54019`486129`yes`54019`7157`7157`510285`100%`19%`real`unsymmetric`no`no`IBM`O. Schenk`2003`semiconductor device problem` | |
| 956`Schenk_IBMSDS`3D_28984_Tetra`28984`28984`285092`yes`28984`5439`5439`314078`99%`36%`real`unsymmetric`no`no`IBM`O. Schenk`2003`semiconductor device problem` | |
| 957`Schenk_IBMSDS`3D_51448_3D`51448`51448`537038`yes`51448`6627`6627`519572`99%`19%`real`unsymmetric`no`no`IBM`O. Schenk`2003`semiconductor device problem` | |
| 958`Schenk_IBMSDS`ibm_matrix_2`51448`51448`537038`yes`51448`6627`6627`519572`99%`19%`real`unsymmetric`no`no`IBM`O. Schenk`2003`semiconductor device problem` | |
| 959`Schenk_IBMSDS`matrix_9`103430`103430`1205518`yes`103430`4059`4059`916032`100%`17%`real`unsymmetric`no`no`IBM`O. Schenk`2003`semiconductor device problem` | |
| 960`Schenk_IBMSDS`matrix-new_3`125329`125329`893984`yes`125329`46658`46658`1784766`99%`28%`real`unsymmetric`no`no`IBM`O. Schenk`2003`semiconductor device problem` | |
| 961`Schenk_ISEI`barrier2-10`115625`115625`2158759`yes`115625`436`436`1738798`symmetric`20%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: Schenk_ISEI/barrier2-11 first: Schenk_ISEI/barrier2-9\n | |
| 962`Schenk_ISEI`barrier2-11`115625`115625`2158759`yes`115625`436`436`1738798`symmetric`20%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: Schenk_ISEI/barrier2-12 first: Schenk_ISEI/barrier2-9\n | |
| 963`Schenk_ISEI`barrier2-12`115625`115625`2158759`yes`115625`436`436`1738798`symmetric`20%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: - first: Schenk_ISEI/barrier2-9\n | |
| 964`Schenk_ISEI`barrier2-1`113076`113076`2129496`yes`113076`1`1`1675572`symmetric`20%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`semiconductor device problem sequence`\nnext: Schenk_ISEI/barrier2-2 first: Schenk_ISEI/barrier2-1\n | |
| 965`Schenk_ISEI`barrier2-2`113076`113076`2129496`yes`113076`1`1`1675572`symmetric`20%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: Schenk_ISEI/barrier2-3 first: Schenk_ISEI/barrier2-1\n | |
| 966`Schenk_ISEI`barrier2-3`113076`113076`2129496`yes`113076`1`1`1675572`symmetric`20%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: Schenk_ISEI/barrier2-4 first: Schenk_ISEI/barrier2-1\n | |
| 967`Schenk_ISEI`barrier2-4`113076`113076`2129496`yes`113076`1`1`1675572`symmetric`19%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: - first: Schenk_ISEI/barrier2-1\n | |
| 968`Schenk_ISEI`barrier2-9`115625`115625`2158759`yes`115625`436`436`1738798`symmetric`20%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`semiconductor device problem sequence`\nnext: Schenk_ISEI/barrier2-10 first: Schenk_ISEI/barrier2-9\n | |
| 969`Schenk_ISEI`igbt3`10938`10938`130500`yes`10938`1`1`103506`symmetric`17%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`semiconductor device problem` | |
| 970`Schenk_ISEI`nmos3`18588`18588`237130`yes`18588`1`1`149464`symmetric`17%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`semiconductor device problem` | |
| 971`Schenk_ISEI`ohne2`181343`181343`6869939`yes`181343`1`1`4193606`symmetric`9%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`semiconductor device problem` | |
| 972`Schenk_ISEI`para-10`155924`155924`2094873`yes`155924`565`565`3321485`symmetric`20%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: - first: Schenk_ISEI/para-5\n | |
| 973`Schenk_ISEI`para-4`153226`153226`2930882`yes`153226`1`1`2395346`symmetric`29%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`semiconductor device problem` | |
| 974`Schenk_ISEI`para-5`155924`155924`2094873`yes`155924`565`565`3321485`symmetric`37%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`semiconductor device problem sequence`\nnext: Schenk_ISEI/para-6 first: Schenk_ISEI/para-5\n | |
| 975`Schenk_ISEI`para-6`155924`155924`2094873`yes`155924`565`565`3321485`symmetric`37%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: Schenk_ISEI/para-7 first: Schenk_ISEI/para-5\n | |
| 976`Schenk_ISEI`para-7`155924`155924`2094873`yes`155924`565`565`3321485`symmetric`37%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: Schenk_ISEI/para-8 first: Schenk_ISEI/para-5\n | |
| 977`Schenk_ISEI`para-8`155924`155924`2094873`yes`155924`565`565`3321485`symmetric`18%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: Schenk_ISEI/para-9 first: Schenk_ISEI/para-5\n | |
| 978`Schenk_ISEI`para-9`155924`155924`2094873`yes`155924`565`565`3321485`symmetric`18%`real`unsymmetric`no`no`Integrated Sys. Eng.`O. Schenk`2003`subsequent semiconductor device problem`\nnext: Schenk_ISEI/para-10 first: Schenk_ISEI/para-5\n | |
| 979`Kamvar`Stanford`281903`281903`2312497`unknown`unknown`unknown`29914`0`28%`28%`binary`unsymmetric`no`no`S. Kamvar`T. Davis`2003`directed graph` | |
| 980`Kamvar`Stanford_Berkeley`683446`683446`7583376`unknown`unknown`unknown`109238`0`25%`25%`binary`unsymmetric`no`no`S. Kamvar`T. Davis`2003`directed graph` | |
| 981`Sumner`graphics`29493`11822`117954`yes`11822`1`1`0`0%`0%`real`rectangular`no`no`R. Sumner`T. Davis`2003`computer graphics/vision problem` | |
| 982`Tromble`language`399130`399130`1216334`unknown`unknown`unknown`2456`0`6%`0%`real`unsymmetric`no`no`R. Tromble`T. Davis`2003`directed weighted graph` | |
| 983`Sanghavi`ecl32`51993`51993`380415`yes`51993`9653`9653`0`92%`60%`real`unsymmetric`no`no`J. Sanghavi`C. Voemel`2003`semiconductor device problem` | |
| 984`Sandia`adder_dcop_01`1813`1813`11156`yes`1813`469`6`0`65%`2%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_02 first: Sandia/init_adder1\n | |
| 985`Sandia`adder_dcop_02`1813`1813`11246`yes`1813`469`6`0`65%`3%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_03 first: Sandia/init_adder1\n | |
| 986`Sandia`adder_dcop_03`1813`1813`11148`yes`1813`483`7`0`64%`4%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_04 first: Sandia/init_adder1\n | |
| 987`Sandia`adder_dcop_04`1813`1813`11107`yes`1813`474`8`0`65%`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_05 first: Sandia/init_adder1\n | |
| 988`Sandia`adder_dcop_05`1813`1813`11097`yes`1813`473`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_06 first: Sandia/init_adder1\n | |
| 989`Sandia`adder_dcop_06`1813`1813`11224`yes`1813`470`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_07 first: Sandia/init_adder1\n | |
| 990`Sandia`adder_dcop_07`1813`1813`11226`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_08 first: Sandia/init_adder1\n | |
| 991`Sandia`adder_dcop_08`1813`1813`11242`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_09 first: Sandia/init_adder1\n | |
| 992`Sandia`adder_dcop_09`1813`1813`11239`yes`1813`470`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_10 first: Sandia/init_adder1\n | |
| 993`Sandia`adder_dcop_10`1813`1813`11232`yes`1813`473`7`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_11 first: Sandia/init_adder1\n | |
| 994`Sandia`adder_dcop_11`1813`1813`11243`yes`1813`470`6`0`65%`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_12 first: Sandia/init_adder1\n | |
| 995`Sandia`adder_dcop_12`1813`1813`11246`yes`1813`469`6`0`65%`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_13 first: Sandia/init_adder1\n | |
| 996`Sandia`adder_dcop_13`1813`1813`11245`yes`1813`469`6`0`65%`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_14 first: Sandia/init_adder1\n | |
| 997`Sandia`adder_dcop_14`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_15 first: Sandia/init_adder1\n | |
| 998`Sandia`adder_dcop_15`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_16 first: Sandia/init_adder1\n | |
| 999`Sandia`adder_dcop_16`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_17 first: Sandia/init_adder1\n | |
| 1000`Sandia`adder_dcop_17`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_18 first: Sandia/init_adder1\n | |
| 1001`Sandia`adder_dcop_18`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_19 first: Sandia/init_adder1\n | |
| 1002`Sandia`adder_dcop_19`1813`1813`11245`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_20 first: Sandia/init_adder1\n | |
| 1003`Sandia`adder_dcop_20`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_21 first: Sandia/init_adder1\n | |
| 1004`Sandia`adder_dcop_21`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_22 first: Sandia/init_adder1\n | |
| 1005`Sandia`adder_dcop_22`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_23 first: Sandia/init_adder1\n | |
| 1006`Sandia`adder_dcop_23`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_24 first: Sandia/init_adder1\n | |
| 1007`Sandia`adder_dcop_24`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_25 first: Sandia/init_adder1\n | |
| 1008`Sandia`adder_dcop_25`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_26 first: Sandia/init_adder1\n | |
| 1009`Sandia`adder_dcop_26`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_27 first: Sandia/init_adder1\n | |
| 1010`Sandia`adder_dcop_27`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_28 first: Sandia/init_adder1\n | |
| 1011`Sandia`adder_dcop_28`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_29 first: Sandia/init_adder1\n | |
| 1012`Sandia`adder_dcop_29`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_30 first: Sandia/init_adder1\n | |
| 1013`Sandia`adder_dcop_30`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_31 first: Sandia/init_adder1\n | |
| 1014`Sandia`adder_dcop_31`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_32 first: Sandia/init_adder1\n | |
| 1015`Sandia`adder_dcop_32`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_33 first: Sandia/init_adder1\n | |
| 1016`Sandia`adder_dcop_33`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_34 first: Sandia/init_adder1\n | |
| 1017`Sandia`adder_dcop_34`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_35 first: Sandia/init_adder1\n | |
| 1018`Sandia`adder_dcop_35`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_36 first: Sandia/init_adder1\n | |
| 1019`Sandia`adder_dcop_36`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_37 first: Sandia/init_adder1\n | |
| 1020`Sandia`adder_dcop_37`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_38 first: Sandia/init_adder1\n | |
| 1021`Sandia`adder_dcop_38`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_39 first: Sandia/init_adder1\n | |
| 1022`Sandia`adder_dcop_39`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_40 first: Sandia/init_adder1\n | |
| 1023`Sandia`adder_dcop_40`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_41 first: Sandia/init_adder1\n | |
| 1024`Sandia`adder_dcop_41`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_42 first: Sandia/init_adder1\n | |
| 1025`Sandia`adder_dcop_42`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_43 first: Sandia/init_adder1\n | |
| 1026`Sandia`adder_dcop_43`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_44 first: Sandia/init_adder1\n | |
| 1027`Sandia`adder_dcop_44`1813`1813`11245`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_45 first: Sandia/init_adder1\n | |
| 1028`Sandia`adder_dcop_45`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_46 first: Sandia/init_adder1\n | |
| 1029`Sandia`adder_dcop_46`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_47 first: Sandia/init_adder1\n | |
| 1030`Sandia`adder_dcop_47`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_48 first: Sandia/init_adder1\n | |
| 1031`Sandia`adder_dcop_48`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_49 first: Sandia/init_adder1\n | |
| 1032`Sandia`adder_dcop_49`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_50 first: Sandia/init_adder1\n | |
| 1033`Sandia`adder_dcop_50`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_51 first: Sandia/init_adder1\n | |
| 1034`Sandia`adder_dcop_51`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_52 first: Sandia/init_adder1\n | |
| 1035`Sandia`adder_dcop_52`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_53 first: Sandia/init_adder1\n | |
| 1036`Sandia`adder_dcop_53`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_54 first: Sandia/init_adder1\n | |
| 1037`Sandia`adder_dcop_54`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_55 first: Sandia/init_adder1\n | |
| 1038`Sandia`adder_dcop_55`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_56 first: Sandia/init_adder1\n | |
| 1039`Sandia`adder_dcop_56`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_57 first: Sandia/init_adder1\n | |
| 1040`Sandia`adder_dcop_57`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_58 first: Sandia/init_adder1\n | |
| 1041`Sandia`adder_dcop_58`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_59 first: Sandia/init_adder1\n | |
| 1042`Sandia`adder_dcop_59`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_60 first: Sandia/init_adder1\n | |
| 1043`Sandia`adder_dcop_60`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_61 first: Sandia/init_adder1\n | |
| 1044`Sandia`adder_dcop_61`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_62 first: Sandia/init_adder1\n | |
| 1045`Sandia`adder_dcop_62`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_63 first: Sandia/init_adder1\n | |
| 1046`Sandia`adder_dcop_63`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_64 first: Sandia/init_adder1\n | |
| 1047`Sandia`adder_dcop_64`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_65 first: Sandia/init_adder1\n | |
| 1048`Sandia`adder_dcop_65`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_66 first: Sandia/init_adder1\n | |
| 1049`Sandia`adder_dcop_66`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_67 first: Sandia/init_adder1\n | |
| 1050`Sandia`adder_dcop_67`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_68 first: Sandia/init_adder1\n | |
| 1051`Sandia`adder_dcop_68`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/adder_dcop_69 first: Sandia/init_adder1\n | |
| 1052`Sandia`adder_dcop_69`1813`1813`11246`yes`1813`469`6`0`65%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: - first: Sandia/init_adder1\n | |
| 1053`Sandia`adder_trans_01`1814`1814`14579`yes`1814`20`3`0`symmetric`3%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`circuit simulation problem sequence`\nnext: Sandia/adder_trans_02 first: Sandia/adder_trans_01\n | |
| 1054`Sandia`adder_trans_02`1814`1814`14579`yes`1814`20`3`0`symmetric`3%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: - first: Sandia/adder_trans_01\n | |
| 1055`Sandia`fpga_dcop_01`1220`1220`5892`yes`1220`188`34`0`82%`27%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`circuit simulation problem sequence`\nnext: Sandia/fpga_dcop_02 first: Sandia/fpga_dcop_01\n | |
| 1056`Sandia`fpga_dcop_02`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_03 first: Sandia/fpga_dcop_01\n | |
| 1057`Sandia`fpga_dcop_03`1220`1220`5892`yes`1220`188`34`0`82%`34%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_04 first: Sandia/fpga_dcop_01\n | |
| 1058`Sandia`fpga_dcop_04`1220`1220`5884`yes`1220`189`34`0`82%`35%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_05 first: Sandia/fpga_dcop_01\n | |
| 1059`Sandia`fpga_dcop_05`1220`1220`5852`yes`1220`194`34`0`82%`36%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_06 first: Sandia/fpga_dcop_01\n | |
| 1060`Sandia`fpga_dcop_06`1220`1220`5860`yes`1220`193`34`0`82%`35%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_07 first: Sandia/fpga_dcop_01\n | |
| 1061`Sandia`fpga_dcop_07`1220`1220`5855`yes`1220`193`34`0`82%`34%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_08 first: Sandia/fpga_dcop_01\n | |
| 1062`Sandia`fpga_dcop_08`1220`1220`5888`yes`1220`189`34`0`82%`34%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_09 first: Sandia/fpga_dcop_01\n | |
| 1063`Sandia`fpga_dcop_09`1220`1220`5888`yes`1220`189`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_10 first: Sandia/fpga_dcop_01\n | |
| 1064`Sandia`fpga_dcop_10`1220`1220`5884`yes`1220`190`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_11 first: Sandia/fpga_dcop_01\n | |
| 1065`Sandia`fpga_dcop_11`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_12 first: Sandia/fpga_dcop_01\n | |
| 1066`Sandia`fpga_dcop_12`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_13 first: Sandia/fpga_dcop_01\n | |
| 1067`Sandia`fpga_dcop_13`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_14 first: Sandia/fpga_dcop_01\n | |
| 1068`Sandia`fpga_dcop_14`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_15 first: Sandia/fpga_dcop_01\n | |
| 1069`Sandia`fpga_dcop_15`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_16 first: Sandia/fpga_dcop_01\n | |
| 1070`Sandia`fpga_dcop_16`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_17 first: Sandia/fpga_dcop_01\n | |
| 1071`Sandia`fpga_dcop_17`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_18 first: Sandia/fpga_dcop_01\n | |
| 1072`Sandia`fpga_dcop_18`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_19 first: Sandia/fpga_dcop_01\n | |
| 1073`Sandia`fpga_dcop_19`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_20 first: Sandia/fpga_dcop_01\n | |
| 1074`Sandia`fpga_dcop_20`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_21 first: Sandia/fpga_dcop_01\n | |
| 1075`Sandia`fpga_dcop_21`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_22 first: Sandia/fpga_dcop_01\n | |
| 1076`Sandia`fpga_dcop_22`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_23 first: Sandia/fpga_dcop_01\n | |
| 1077`Sandia`fpga_dcop_23`1220`1220`5892`yes`1220`188`34`0`82%`32%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_24 first: Sandia/fpga_dcop_01\n | |
| 1078`Sandia`fpga_dcop_24`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_25 first: Sandia/fpga_dcop_01\n | |
| 1079`Sandia`fpga_dcop_25`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_26 first: Sandia/fpga_dcop_01\n | |
| 1080`Sandia`fpga_dcop_26`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_27 first: Sandia/fpga_dcop_01\n | |
| 1081`Sandia`fpga_dcop_27`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_28 first: Sandia/fpga_dcop_01\n | |
| 1082`Sandia`fpga_dcop_28`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_29 first: Sandia/fpga_dcop_01\n | |
| 1083`Sandia`fpga_dcop_29`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_30 first: Sandia/fpga_dcop_01\n | |
| 1084`Sandia`fpga_dcop_30`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_31 first: Sandia/fpga_dcop_01\n | |
| 1085`Sandia`fpga_dcop_31`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_32 first: Sandia/fpga_dcop_01\n | |
| 1086`Sandia`fpga_dcop_32`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_33 first: Sandia/fpga_dcop_01\n | |
| 1087`Sandia`fpga_dcop_33`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_34 first: Sandia/fpga_dcop_01\n | |
| 1088`Sandia`fpga_dcop_34`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_35 first: Sandia/fpga_dcop_01\n | |
| 1089`Sandia`fpga_dcop_35`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_36 first: Sandia/fpga_dcop_01\n | |
| 1090`Sandia`fpga_dcop_36`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_37 first: Sandia/fpga_dcop_01\n | |
| 1091`Sandia`fpga_dcop_37`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_38 first: Sandia/fpga_dcop_01\n | |
| 1092`Sandia`fpga_dcop_38`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_39 first: Sandia/fpga_dcop_01\n | |
| 1093`Sandia`fpga_dcop_39`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_40 first: Sandia/fpga_dcop_01\n | |
| 1094`Sandia`fpga_dcop_40`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_41 first: Sandia/fpga_dcop_01\n | |
| 1095`Sandia`fpga_dcop_41`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_42 first: Sandia/fpga_dcop_01\n | |
| 1096`Sandia`fpga_dcop_42`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_43 first: Sandia/fpga_dcop_01\n | |
| 1097`Sandia`fpga_dcop_43`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_44 first: Sandia/fpga_dcop_01\n | |
| 1098`Sandia`fpga_dcop_44`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_45 first: Sandia/fpga_dcop_01\n | |
| 1099`Sandia`fpga_dcop_45`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_46 first: Sandia/fpga_dcop_01\n | |
| 1100`Sandia`fpga_dcop_46`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_47 first: Sandia/fpga_dcop_01\n | |
| 1101`Sandia`fpga_dcop_47`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_48 first: Sandia/fpga_dcop_01\n | |
| 1102`Sandia`fpga_dcop_48`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_49 first: Sandia/fpga_dcop_01\n | |
| 1103`Sandia`fpga_dcop_49`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_50 first: Sandia/fpga_dcop_01\n | |
| 1104`Sandia`fpga_dcop_50`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/fpga_dcop_51 first: Sandia/fpga_dcop_01\n | |
| 1105`Sandia`fpga_dcop_51`1220`1220`5892`yes`1220`188`34`0`82%`33%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: - first: Sandia/fpga_dcop_01\n | |
| 1106`Sandia`fpga_trans_01`1220`1220`7382`yes`1220`133`1`0`symmetric`21%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`circuit simulation problem sequence`\nnext: Sandia/fpga_trans_02 first: Sandia/fpga_trans_01\n | |
| 1107`Sandia`fpga_trans_02`1220`1220`7382`yes`1220`133`1`0`symmetric`21%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: - first: Sandia/fpga_trans_01\n | |
| 1108`Sandia`init_adder1`1813`1813`11156`yes`1813`469`6`0`65%`2%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`circuit simulation problem sequence`\nnext: Sandia/adder_dcop_01 first: Sandia/init_adder1\n | |
| 1109`Sandia`mult_dcop_01`25187`25187`193276`yes`25187`7417`107`0`61%`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`circuit simulation problem sequence`\nnext: Sandia/mult_dcop_02 first: Sandia/mult_dcop_01\n | |
| 1110`Sandia`mult_dcop_02`25187`25187`193276`yes`25187`7417`107`0`61%`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/mult_dcop_03 first: Sandia/mult_dcop_01\n | |
| 1111`Sandia`mult_dcop_03`25187`25187`193216`yes`25187`7447`107`0`61%`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: - first: Sandia/mult_dcop_01\n | |
| 1112`Sandia`oscil_dcop_01`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`circuit simulation problem sequence`\nnext: Sandia/oscil_dcop_02 first: Sandia/oscil_dcop_01\n | |
| 1113`Sandia`oscil_dcop_02`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_03 first: Sandia/oscil_dcop_01\n | |
| 1114`Sandia`oscil_dcop_03`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_04 first: Sandia/oscil_dcop_01\n | |
| 1115`Sandia`oscil_dcop_04`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_05 first: Sandia/oscil_dcop_01\n | |
| 1116`Sandia`oscil_dcop_05`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_06 first: Sandia/oscil_dcop_01\n | |
| 1117`Sandia`oscil_dcop_06`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_07 first: Sandia/oscil_dcop_01\n | |
| 1118`Sandia`oscil_dcop_07`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_08 first: Sandia/oscil_dcop_01\n | |
| 1119`Sandia`oscil_dcop_08`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_09 first: Sandia/oscil_dcop_01\n | |
| 1120`Sandia`oscil_dcop_09`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_10 first: Sandia/oscil_dcop_01\n | |
| 1121`Sandia`oscil_dcop_10`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_11 first: Sandia/oscil_dcop_01\n | |
| 1122`Sandia`oscil_dcop_11`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_12 first: Sandia/oscil_dcop_01\n | |
| 1123`Sandia`oscil_dcop_12`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_13 first: Sandia/oscil_dcop_01\n | |
| 1124`Sandia`oscil_dcop_13`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_14 first: Sandia/oscil_dcop_01\n | |
| 1125`Sandia`oscil_dcop_14`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_15 first: Sandia/oscil_dcop_01\n | |
| 1126`Sandia`oscil_dcop_15`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_16 first: Sandia/oscil_dcop_01\n | |
| 1127`Sandia`oscil_dcop_16`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_17 first: Sandia/oscil_dcop_01\n | |
| 1128`Sandia`oscil_dcop_17`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_18 first: Sandia/oscil_dcop_01\n | |
| 1129`Sandia`oscil_dcop_18`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_19 first: Sandia/oscil_dcop_01\n | |
| 1130`Sandia`oscil_dcop_19`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_20 first: Sandia/oscil_dcop_01\n | |
| 1131`Sandia`oscil_dcop_20`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_21 first: Sandia/oscil_dcop_01\n | |
| 1132`Sandia`oscil_dcop_21`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_22 first: Sandia/oscil_dcop_01\n | |
| 1133`Sandia`oscil_dcop_22`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_23 first: Sandia/oscil_dcop_01\n | |
| 1134`Sandia`oscil_dcop_23`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_24 first: Sandia/oscil_dcop_01\n | |
| 1135`Sandia`oscil_dcop_24`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_25 first: Sandia/oscil_dcop_01\n | |
| 1136`Sandia`oscil_dcop_25`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_26 first: Sandia/oscil_dcop_01\n | |
| 1137`Sandia`oscil_dcop_26`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_27 first: Sandia/oscil_dcop_01\n | |
| 1138`Sandia`oscil_dcop_27`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_28 first: Sandia/oscil_dcop_01\n | |
| 1139`Sandia`oscil_dcop_28`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_29 first: Sandia/oscil_dcop_01\n | |
| 1140`Sandia`oscil_dcop_29`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_30 first: Sandia/oscil_dcop_01\n | |
| 1141`Sandia`oscil_dcop_30`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_31 first: Sandia/oscil_dcop_01\n | |
| 1142`Sandia`oscil_dcop_31`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_32 first: Sandia/oscil_dcop_01\n | |
| 1143`Sandia`oscil_dcop_32`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_33 first: Sandia/oscil_dcop_01\n | |
| 1144`Sandia`oscil_dcop_33`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_34 first: Sandia/oscil_dcop_01\n | |
| 1145`Sandia`oscil_dcop_34`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_35 first: Sandia/oscil_dcop_01\n | |
| 1146`Sandia`oscil_dcop_35`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_36 first: Sandia/oscil_dcop_01\n | |
| 1147`Sandia`oscil_dcop_36`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_37 first: Sandia/oscil_dcop_01\n | |
| 1148`Sandia`oscil_dcop_37`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_38 first: Sandia/oscil_dcop_01\n | |
| 1149`Sandia`oscil_dcop_38`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_39 first: Sandia/oscil_dcop_01\n | |
| 1150`Sandia`oscil_dcop_39`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_40 first: Sandia/oscil_dcop_01\n | |
| 1151`Sandia`oscil_dcop_40`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_41 first: Sandia/oscil_dcop_01\n | |
| 1152`Sandia`oscil_dcop_41`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_42 first: Sandia/oscil_dcop_01\n | |
| 1153`Sandia`oscil_dcop_42`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_43 first: Sandia/oscil_dcop_01\n | |
| 1154`Sandia`oscil_dcop_43`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_44 first: Sandia/oscil_dcop_01\n | |
| 1155`Sandia`oscil_dcop_44`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_45 first: Sandia/oscil_dcop_01\n | |
| 1156`Sandia`oscil_dcop_45`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_46 first: Sandia/oscil_dcop_01\n | |
| 1157`Sandia`oscil_dcop_46`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_47 first: Sandia/oscil_dcop_01\n | |
| 1158`Sandia`oscil_dcop_47`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_48 first: Sandia/oscil_dcop_01\n | |
| 1159`Sandia`oscil_dcop_48`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_49 first: Sandia/oscil_dcop_01\n | |
| 1160`Sandia`oscil_dcop_49`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_50 first: Sandia/oscil_dcop_01\n | |
| 1161`Sandia`oscil_dcop_50`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_51 first: Sandia/oscil_dcop_01\n | |
| 1162`Sandia`oscil_dcop_51`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_52 first: Sandia/oscil_dcop_01\n | |
| 1163`Sandia`oscil_dcop_52`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_53 first: Sandia/oscil_dcop_01\n | |
| 1164`Sandia`oscil_dcop_53`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_54 first: Sandia/oscil_dcop_01\n | |
| 1165`Sandia`oscil_dcop_54`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_55 first: Sandia/oscil_dcop_01\n | |
| 1166`Sandia`oscil_dcop_55`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_56 first: Sandia/oscil_dcop_01\n | |
| 1167`Sandia`oscil_dcop_56`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: Sandia/oscil_dcop_57 first: Sandia/oscil_dcop_01\n | |
| 1168`Sandia`oscil_dcop_57`430`430`1544`yes`430`31`9`0`98%`70%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`subsequent circuit simulation problem`\nnext: - first: Sandia/oscil_dcop_01\n | |
| 1169`Sandia`oscil_trans_01`430`430`1614`yes`430`19`9`0`97%`72%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2003`circuit simulation problem` | |
| 1170`MathWorks`Pd`8081`8081`13036`yes`8081`7877`7877`0`0%`0%`real`unsymmetric`no`no`P. Anderson`T. Davis`2002`counter-example problem` | |
| 1171`MathWorks`Pd_rhs`8081`12406`6323`no`4368`2872`14549`0`0%`0%`real`rectangular`no`no`P. Anderson`T. Davis`2002`counter-example problem` | |
| 1172`MathWorks`Harvard500`500`500`2636`unknown`unknown`unknown`147`0`41%`41%`binary`unsymmetric`no`no`C. Moler`T. Davis`2002`directed graph` | |
| 1173`HB`cegb2802`2802`2802`277362`no`2694`3`109`0`symmetric`symmetric`binary`symmetric`no`no`A. Donovan`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1174`HB`cegb2919`2919`2919`321543`no`2859`3`61`0`symmetric`symmetric`binary`symmetric`no`no`A. Donovan`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1175`HB`cegb3024`3024`3024`79848`no`2996`3`29`0`symmetric`symmetric`binary`symmetric`no`no`A. Donovan`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1176`HB`cegb3306`3306`3306`74916`no`3222`3`85`0`symmetric`symmetric`binary`symmetric`no`no`A. Donovan`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1177`HB`lap_25`25`25`169`yes`25`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`I. Duff`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1178`HB`lock1074`1074`1074`51588`no`1038`3`37`0`symmetric`symmetric`binary`symmetric`no`no`W. Loden`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1179`HB`lock2232`2232`2232`80352`no`2208`3`25`0`symmetric`symmetric`binary`symmetric`no`no`W. Loden`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1180`HB`lock3491`3491`3491`160444`no`3416`3`76`0`symmetric`symmetric`binary`symmetric`no`no`W. Loden`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1181`HB`lock_700`700`700`22175`no`691`3`10`0`symmetric`symmetric`binary`symmetric`no`no`W. Loden`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1182`HB`man_5976`5976`5976`225046`no`5882`3`95`0`symmetric`symmetric`binary`symmetric`no`no`T. Manteuffel`I. Duff, R. Grimes, J. Lewis`1980`structural problem` | |
| 1183`IBM_Austin`coupled`11341`11341`97193`yes`11341`49`1`1330`symmetric`78%`real`unsymmetric`no`no`E. Acar`T. Davis`2004`circuit simulation problem` | |
| 1184`ACUSIM`Pres_Poisson`14822`14822`715804`yes`14822`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`F. Shakib`T. Davis`2004`computational fluid dynamics problem` | |
| 1185`Rajat`rajat01`6833`6833`43250`yes`6833`507`66`0`100%`100%`binary`unsymmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1186`Rajat`rajat02`1960`1960`11187`yes`1960`58`10`0`symmetric`symmetric`binary`symmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1187`Rajat`rajat03`7602`7602`32653`yes`7602`103`1`0`symmetric`40%`real`unsymmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1188`Rajat`rajat04`1041`1041`8725`yes`1041`67`1`917`symmetric`4%`real`unsymmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1189`Rajat`rajat05`301`301`1250`yes`301`15`9`134`77%`71%`real`unsymmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1190`Rajat`rajat06`10922`10922`46983`yes`10922`123`1`0`symmetric`symmetric`binary`symmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1191`Rajat`rajat07`14842`14842`63913`yes`14842`143`1`0`symmetric`symmetric`binary`symmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1192`Rajat`rajat08`19362`19362`83443`yes`19362`163`1`0`symmetric`symmetric`binary`symmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1193`Rajat`rajat09`24482`24482`105573`yes`24482`183`1`0`symmetric`symmetric`binary`symmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1194`Rajat`rajat10`30202`30202`130303`yes`30202`203`1`0`symmetric`symmetric`binary`symmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1195`Rajat`rajat11`135`135`665`yes`135`7`1`147`89%`63%`real`unsymmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1196`Rajat`rajat12`1879`1879`12818`yes`1879`24`1`108`symmetric`45%`real`unsymmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1197`Rajat`rajat13`7598`7598`48762`yes`7598`134`109`160`symmetric`30%`real`unsymmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1198`Rajat`rajat14`180`180`1475`yes`180`19`1`28`symmetric`2%`real`unsymmetric`no`no`Rajat`T. Davis`2004`circuit simulation problem` | |
| 1199`Hamrle`Hamrle1`32`32`98`yes`32`1`1`0`6%`0%`real`unsymmetric`no`no`J. Hamrle`T. Davis`2004`circuit simulation problem` | |
| 1200`Hamrle`Hamrle2`5952`5952`22162`yes`5952`1`1`0`0%`0%`real`unsymmetric`no`no`J. Hamrle`T. Davis`2004`circuit simulation problem` | |
| 1201`Hamrle`Hamrle3`1447360`1447360`5514242`yes`1447360`1`1`0`0%`0%`real`unsymmetric`no`no`J. Hamrle`T. Davis`2004`circuit simulation problem` | |
| 1202`Oberwolfach`gyro_k`17361`17361`1021159`yes`17361`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`D. Billger`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1203`Oberwolfach`gyro_m`17361`17361`340431`yes`17361`3`3`0`symmetric`symmetric`real`symmetric`yes`yes`D. Billger`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1204`Oberwolfach`t2dah_a`11445`11445`176117`yes`11445`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1205`Oberwolfach`t2dah_e`11445`11445`176117`yes`11445`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`E. Rudnyi`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1206`Oberwolfach`t2dal_a`4257`4257`37465`yes`4257`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1207`Oberwolfach`t2dal_e`4257`4257`4257`yes`4257`4257`4257`0`symmetric`symmetric`real`symmetric`yes`yes`E. Rudnyi`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1208`Oberwolfach`t3dh_a`79171`79171`4352105`yes`79171`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1209`Oberwolfach`t3dh_e`79171`79171`4352105`yes`79171`1`1`0`symmetric`symmetric`real`symmetric`yes`no`E. Rudnyi`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1210`Oberwolfach`t3dl_a`20360`20360`509866`yes`20360`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1211`Oberwolfach`t3dl_e`20360`20360`20360`yes`20360`20360`20360`0`symmetric`symmetric`real`symmetric`yes`yes`E. Rudnyi`E. Rudnyi`2004`duplicate model reduction problem` | |
| 1212`LiuWenzhuo`powersim`15838`15838`64424`yes`15838`3600`3600`3138`59%`53%`real`unsymmetric`no`no`W. Liu`T. Davis`2004`power network problem` | |
| 1213`Lin`Lin`256000`256000`1766400`yes`256000`1`1`0`symmetric`symmetric`real`symmetric`yes`no`C. Lin`T. Davis`2004`structural problem` | |
| 1214`Cannizzo`sts4098`4098`4098`72356`yes`4098`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`F. Cannizzo`T. Davis`2004`structural problem` | |
| 1215`GHS_indef`aug2d`29008`29008`76832`no`19208`2`1`0`symmetric`symmetric`integer`symmetric`no`no`N. Gould`N. Gould`1994`2D/3D problem` | |
| 1216`GHS_indef`aug2dc`30200`30200`80000`no`20000`2`1`0`symmetric`symmetric`integer`symmetric`no`no`N. Gould`N. Gould`1994`2D/3D problem` | |
| 1217`GHS_indef`aug3d`24300`24300`69984`no`11664`2`1`0`symmetric`symmetric`integer`symmetric`no`no`N. Gould`N. Gould`1994`2D/3D problem` | |
| 1218`GHS_indef`aug3dcqp`35543`35543`128115`yes`35543`2`2`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1994`2D/3D problem` | |
| 1219`GHS_indef`bmw3_2`227362`227362`11288630`yes`227362`1`1`0`symmetric`symmetric`real`symmetric`yes`no`S. Mayer`J. Koster`2004`structural problem` | |
| 1220`GHS_indef`c-55`32780`32780`403450`yes`32780`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1221`GHS_indef`c-58`37595`37595`552551`yes`37595`4`4`6`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1222`GHS_indef`c-59`41282`41282`480536`yes`41282`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1223`GHS_indef`c-62ghs`41731`41731`559339`yes`41731`3`3`4`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`subsequent optimization problem`\nnext: - first: Schenk_IBMNA/c-62 \nA version of this matrix was first obtained from Olaf Schenk in October\n2003. That version appears in this collection as Schenk_IBMNA/c-62. \nIn August 2004, a new version appeared in the GHS collection, under the\nsame name, and was added here as GHS_indef/c-62ghs. The c-62ghs matrix\nis the same as the version on Schenk's web site as of Nov 2006, except \nthat the right-hand-side was missing in the version in the UF Sparse \nMatrix Collection (now included). The two matrices c-62 and c-62ghs \nare very similar, but not identical. \n | |
| 1224`GHS_indef`c-63`44234`44234`434704`yes`44234`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1225`GHS_indef`c-68`64810`64810`565996`yes`64810`6`6`10`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1226`GHS_indef`c-69`67458`67458`623914`yes`67458`29`29`56`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1227`GHS_indef`c-70`68924`68924`658986`yes`68924`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1228`GHS_indef`c-71`76638`76638`859520`yes`76638`18`18`34`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1229`GHS_indef`c-72`84064`84064`707546`yes`84064`7`7`12`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2004`optimization problem`\nRevised Nov 2006; relative eps changes to A, right-hand-side added.\nNote that this matrix should have been placed in the Schenk_IBMNA/ \ndirectory when it was first added in August 2004, but moving it now\nwould disrupt exising users of the collection. \n | |
| 1230`GHS_indef`copter2`55476`55476`759952`yes`55476`1`1`0`symmetric`symmetric`real`symmetric`no`no`G. Kumfert, A. Pothen`N. Gould, Y. Hu, J. Scott`2004`computational fluid dynamics problem` | |
| 1231`GHS_indef`d_pretok`182730`182730`1641672`yes`182730`1`1`0`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1232`GHS_indef`darcy003`389874`389874`2097566`yes`389874`920`920`3676`symmetric`symmetric`real`symmetric`no`no`M. Arioli, G. Manzini`N. Gould, Y. Hu, J. Scott`2002`2D/3D problem` | |
| 1233`GHS_indef`dawson5`51537`51537`1010777`yes`51537`307`307`0`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1234`GHS_indef`dtoc`24993`24993`69972`no`19994`2`1`0`symmetric`symmetric`real`symmetric`no`no`T. Coleman, A. Liao`P. Toint`1992`optimization problem` | |
| 1235`GHS_indef`exdata_1`6001`6001`2269500`yes`6001`1`1`1`symmetric`symmetric`real`symmetric`no`no`S. Wright`N. Gould, Y. Hu, J. Scott`2004`optimization problem` | |
| 1236`GHS_indef`helm2d03`392257`392257`2741935`yes`392257`1`1`0`symmetric`symmetric`real`symmetric`yes`no`unknown`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1237`GHS_indef`helm3d01`32226`32226`428444`yes`32226`1`1`0`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1238`GHS_indef`k1_san`67759`67759`559774`no`67758`3`2`0`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1239`GHS_indef`laser`3002`3002`9000`no`3000`1002`1`0`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`materials problem` | |
| 1240`GHS_indef`mario001`38434`38434`204912`yes`38434`312`312`1244`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1241`GHS_indef`mario002`389874`389874`2097566`yes`389874`920`920`3676`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`duplicate 2D/3D problem`\nduplicate of GHS_indef/darcy003\n | |
| 1242`GHS_indef`ncvxqp1`12111`12111`73963`yes`12111`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1994`optimization problem` | |
| 1243`GHS_indef`ncvxqp9`16554`16554`54040`yes`16554`555`555`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1994`optimization problem` | |
| 1244`GHS_indef`olesnik0`88263`88263`744216`yes`88263`3`1`0`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1245`GHS_indef`sit100`10262`10262`61046`yes`10262`1`1`0`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1246`GHS_indef`stokes128`49666`49666`558594`yes`49666`1`1`0`symmetric`symmetric`real`symmetric`no`no`M. Arioli`N. Gould, Y. Hu, J. Scott`2004`computational fluid dynamics problem` | |
| 1247`GHS_indef`stokes64`12546`12546`140034`yes`12546`1`1`0`symmetric`symmetric`real`symmetric`no`no`M. Arioli`N. Gould, Y. Hu, J. Scott`2004`computational fluid dynamics problem` | |
| 1248`GHS_indef`stokes64s`12546`12546`140034`yes`12546`1`1`0`symmetric`symmetric`real`symmetric`no`no`M. Arioli`N. Gould, Y. Hu, J. Scott`2004`computational fluid dynamics problem` | |
| 1249`GHS_indef`tuma1`22967`22967`87760`yes`22967`1437`1`0`symmetric`symmetric`real`symmetric`no`no`M. Tuma`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1250`GHS_indef`tuma2`12992`12992`49365`yes`12992`1101`1`0`symmetric`symmetric`real`symmetric`no`no`M. Tuma`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1251`GHS_indef`turon_m`189924`189924`1690876`yes`189924`5`1`0`symmetric`symmetric`real`symmetric`no`no`unknown`N. Gould, Y. Hu, J. Scott`2004`2D/3D problem` | |
| 1252`GHS_psdef`audikw_1`943695`943695`77651847`yes`943695`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`S. Mayer`J. Koster`2004`structural problem` | |
| 1253`GHS_psdef`bmw7st_1`141347`141347`7318399`yes`141347`2`2`21268`symmetric`symmetric`real`symmetric`yes`yes`S. Mayer`J. Koster`2004`structural problem` | |
| 1254`GHS_psdef`bmwcra_1`148770`148770`10641602`yes`148770`1`1`2400`symmetric`symmetric`real`symmetric`yes`yes`S. Mayer`J. Koster`2004`structural problem` | |
| 1255`GHS_psdef`copter1`17222`17222`211064`yes`17222`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Kumfert, A. Pothen`N. Gould, Y. Hu, J. Scott`2004`computational fluid dynamics problem` | |
| 1256`GHS_psdef`copter2`55476`55476`759952`yes`55476`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Kumfert, A. Pothen`N. Gould, Y. Hu, J. Scott`2004`duplicate computational fluid dynamics problem`\nGHS_psdef/copter2 is the nonzero pattern of GHS_indef/copter2.\n | |
| 1257`GHS_psdef`crankseg_1`52804`52804`10614210`yes`52804`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`S. Mayer`J. Koster`2004`structural problem` | |
| 1258`GHS_psdef`crankseg_2`63838`63838`14148858`yes`63838`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`S. Mayer`J. Koster`2004`structural problem` | |
| 1259`DNVS`crplat2`18010`18010`960946`yes`18010`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1260`DNVS`fcondp2`201822`201822`11294316`yes`201822`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1261`GHS_psdef`finance256`37376`37376`298496`yes`37376`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Berger, J. Mulvey, E. Rothberg, R. Vanderbei`N. Gould, Y. Hu, J. Scott`1997`optimization problem` | |
| 1262`GHS_psdef`ford1`18728`18728`101576`yes`18728`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Kumfert, A. Pothen`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1263`GHS_psdef`ford2`100196`100196`544688`yes`100196`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`G. Kumfert, A. Pothen`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1264`DNVS`fullb`199187`199187`11708077`yes`199187`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1265`DNVS`halfb`224617`224617`12387821`yes`224617`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1266`GHS_psdef`hood`220542`220542`9895422`yes`220542`9908`9908`873014`symmetric`symmetric`real`symmetric`yes`yes`J. Weiher`J. Koster`2004`structural problem` | |
| 1267`GHS_psdef`inline_1`503712`503712`36816170`yes`503712`1`1`172`symmetric`symmetric`real`symmetric`yes`yes`S. Mayer`J. Koster`2004`structural problem` | |
| 1268`GHS_psdef`ldoor`952203`952203`42493817`yes`952203`42667`42667`4028658`symmetric`symmetric`real`symmetric`yes`yes`J. Weiher`J. Koster`2004`structural problem` | |
| 1269`DNVS`m_t1`97578`97578`9753570`yes`97578`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`C. Damhaug`J. Koster`1999`structural problem` | |
| 1270`GHS_psdef`oilpan`73752`73752`2148558`yes`73752`17459`17459`1448630`symmetric`symmetric`real`symmetric`yes`yes`J. Weiher`J. Koster`2004`structural problem` | |
| 1271`GHS_psdef`opt1`15449`15449`1930655`yes`15449`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1272`GHS_psdef`pds10`16558`16558`149658`yes`16558`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`J. Kennington`G. Kumfert, A. Pothen`2004`optimization problem` | |
| 1273`GHS_psdef`pwt`36519`36519`326107`yes`36519`57`57`0`symmetric`symmetric`binary`symmetric`yes`no`NASA`G. Kumfert, A. Pothen`1995`duplicate structural problem`\nNasa/pwt, GHS_psdef/pwt and Pothen/pwt are identical; Pothen/ has xyz coord.\n | |
| 1274`GHS_psdef`ramage02`16830`16830`2866352`yes`16830`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Ramage`N. Gould, Y. Hu, J. Scott`2004`computational fluid dynamics problem` | |
| 1275`GHS_psdef`s3dkq4m2`90449`90449`4427725`yes`90449`1`1`393166`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s3dkq4m2.mtx \n%TITLE Cyl shell R/t=1000 unif 150x100 quad mesh DKQ elem with drill rot \n%KEY s3dkq4m2 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%REFERENCE M. Benzi, R. Kouhia, M.Tuma: An assesment of some \n% preconditioning techniques in shell problems \n% Technical Report LA-UR-97-3892, Los Alamos National Laboratory \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 1000 \n% Length to radius ratio R/L = 1 \n% One octant discretized with uniform 150 x 100 quadrilateral mesh \n% element: \n% facet-type shell element where the bending part is formulated \n% using the discrete Kirchhoff quadrilateral (Lyons-Crisfield version), \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 2x2 Gauss-Legendre integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% and the FE mesh is uniform there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1276`GHS_psdef`s3dkt3m2`90449`90449`3686223`yes`90449`1`1`67238`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s3dkt3m2.mtx \n%TITLE Cyl shell R/t=1000 unif 150x100 triang mesh DKT elem with drill rot \n%KEY s3dkt3m2 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 1000 \n% Length to radius ratio R/L = 1 \n% One octant discretized with uniform 150 x 100 triangular mesh \n% element: \n% facet-type shell element where the bending part is formulated \n% using the stabilized MITC theory (stabilization paramater 0.4) \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 3-point integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% and the FE mesh is uniform there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1277`DNVS`ship_001`34920`34920`3896496`yes`34920`1`1`747734`symmetric`symmetric`real`symmetric`yes`yes`C. Damhaug`J. Koster`1999`structural problem` | |
| 1278`DNVS`ship_003`121728`121728`3777036`yes`121728`1`1`4308998`symmetric`symmetric`real`symmetric`yes`yes`C. Damhaug`J. Koster`1999`structural problem` | |
| 1279`DNVS`shipsec1`140874`140874`3568176`yes`140874`3`3`4245228`symmetric`symmetric`real`symmetric`yes`yes`C. Damhaug`J. Koster`1999`structural problem` | |
| 1280`DNVS`shipsec5`179860`179860`4598604`yes`179860`36`36`5514492`symmetric`symmetric`real`symmetric`yes`yes`C. Damhaug`J. Koster`1999`structural problem` | |
| 1281`DNVS`shipsec8`114919`114919`3303553`yes`114919`49`49`3349846`symmetric`symmetric`real`symmetric`yes`yes`C. Damhaug`J. Koster`1999`structural problem` | |
| 1282`GHS_psdef`srb1`54924`54924`2962152`yes`54924`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1283`DNVS`thread`29736`29736`4444880`yes`29736`1`1`25168`symmetric`symmetric`real`symmetric`yes`yes`C. Damhaug`J. Koster`1999`structural problem` | |
| 1284`DNVS`trdheim`22098`22098`1935324`yes`22098`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1285`DNVS`troll`213453`213453`11985111`yes`213453`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1286`DNVS`tsyl201`20685`20685`2454957`yes`20685`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`C. Damhaug`N. Gould, Y. Hu, J. Scott`2004`structural problem` | |
| 1287`GHS_psdef`vanbody`47072`47072`2329056`yes`47072`1`1`7842`symmetric`symmetric`real`symmetric`yes`yes`S. Mayer`J. Koster`2004`structural problem` | |
| 1288`GHS_psdef`wathen100`30401`30401`471601`yes`30401`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Wathen`N. Gould, Y. Hu, J. Scott`2004`random 2D/3D problem`\nrand('state',0); A = gallery('wathen',100100) ; % (in MATLAB)\n | |
| 1289`GHS_psdef`wathen120`36441`36441`565761`yes`36441`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`A. Wathen`N. Gould, Y. Hu, J. Scott`2004`random 2D/3D problem`\nA = gallery('wathen',100120) ; % (in MATLAB) \nTo initialize the MATLAB random number generator to replicate \nthis matrix, first do the following: \nrand('state',0); A = gallery('wathen',100100) \nand then generate this matrix using the 100120 arguments above.\n | |
| 1290`DNVS`x104`108384`108384`8713602`yes`108384`1`1`1454022`symmetric`symmetric`real`symmetric`yes`yes`C. Damhaug`J. Koster`1999`structural problem` | |
| 1291`GHS_indef`a0nsdsil`80016`80016`355034`yes`80016`1`1`0`symmetric`symmetric`real`symmetric`no`no`M. Ferris`N. Gould`2004`optimization problem` | |
| 1292`GHS_indef`a2nnsnsl`80016`80016`347222`yes`80016`1`1`0`symmetric`symmetric`real`symmetric`no`no`M. Ferris`N. Gould`2004`optimization problem` | |
| 1293`GHS_indef`a5esindl`60008`60008`255004`yes`60008`1`1`0`symmetric`symmetric`real`symmetric`no`no`M. Ferris`N. Gould`2004`optimization problem` | |
| 1294`GHS_indef`blockqp1`60012`60012`640033`yes`60012`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1994`optimization problem` | |
| 1295`GHS_indef`bloweya`30004`30004`150009`yes`30004`1`1`0`symmetric`symmetric`real`symmetric`no`no`J. Blowey`N. Gould`1992`materials problem` | |
| 1296`GHS_indef`boyd1`93279`93279`1211231`yes`93279`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`2004`optimization problem` | |
| 1297`GHS_indef`boyd2`466316`466316`1500397`yes`466316`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`2004`optimization problem` | |
| 1298`GHS_indef`brainpc2`27607`27607`179395`yes`27607`2`2`0`symmetric`symmetric`real`symmetric`no`no`N. Duatrebande`P. Toint`1994`optimization problem` | |
| 1299`GHS_indef`bratu3d`27792`27792`173796`yes`27792`3460`285`0`symmetric`symmetric`real`symmetric`no`no`J. More'`P. Toint`1989`2D/3D problem` | |
| 1300`GHS_indef`cont-201`80595`80595`438795`yes`80595`1`1`0`symmetric`symmetric`real`symmetric`no`no`I. Maros, C. Meszaros`N. Gould`2004`optimization problem` | |
| 1301`GHS_indef`cont-300`180895`180895`988195`yes`180895`1`1`0`symmetric`symmetric`real`symmetric`no`no`I. Maros, C. Meszaros`N. Gould`2004`optimization problem` | |
| 1302`GHS_indef`dixmaanl`60000`60000`299998`yes`60000`1`1`0`symmetric`symmetric`real`symmetric`yes`no`L. Dixon, Z. Maany`P. Toint`1989`optimization problem` | |
| 1303`GHS_indef`linverse`11999`11999`95977`yes`11999`1`1`0`symmetric`symmetric`real`symmetric`yes`no`P. Toint`P. Toint`1991`statistical/mathematical problem` | |
| 1304`GHS_indef`ncvxbqp1`50000`50000`349968`yes`50000`6`6`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1995`optimization problem` | |
| 1305`GHS_indef`ncvxqp3`75000`75000`499964`yes`75000`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1995`optimization problem` | |
| 1306`GHS_indef`ncvxqp5`62500`62500`424966`yes`62500`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1995`optimization problem` | |
| 1307`GHS_indef`ncvxqp7`87500`87500`574962`yes`87500`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1995`optimization problem` | |
| 1308`GHS_indef`sparsine`50000`50000`1548988`yes`50000`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1995`structural problem` | |
| 1309`GHS_indef`spmsrtls`29995`29995`229947`yes`29995`1`1`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`2004`statistical/mathematical problem` | |
| 1310`GHS_psdef`cvxbqp1`50000`50000`349968`yes`50000`6`6`0`symmetric`symmetric`real`symmetric`yes`yes`N. Gould`N. Gould`1995`optimization problem` | |
| 1311`GHS_psdef`gridgena`48962`48962`512084`yes`48962`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`P. Barrera, A. Perez, L. Castellanos`P. Toint`1991`optimization problem` | |
| 1312`GHS_psdef`jnlbrng1`40000`40000`199200`yes`40000`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. More', G. Toraldo`N. Gould, Y. Hu, J. Scott`1991`optimization problem` | |
| 1313`GHS_psdef`minsurfo`40806`40806`203622`yes`40806`3`3`0`symmetric`symmetric`real`symmetric`yes`yes`E. Dolan, J. More'`N. Gould`2000`optimization problem` | |
| 1314`GHS_psdef`obstclae`40000`40000`197608`yes`40000`5`5`0`symmetric`symmetric`real`symmetric`yes`yes`R. Dembo, U. Tulowitzki`P. Toint`1983`optimization problem` | |
| 1315`GHS_psdef`torsion1`40000`40000`197608`yes`40000`5`5`0`symmetric`symmetric`real`symmetric`yes`yes`R. Dembo, U. Tulowitzki`P. Toint`1983`duplicate optimization problem`\nduplicate of GHS_psdef/obstclae\n | |
| 1316`Rajat`rajat15`37261`37261`443573`yes`37261`19`1`0`symmetric`94%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1317`Bydder`mri1`65536`147456`589824`no`64517`258`32820`0`0%`0%`real`rectangular`no`no`M. Bydder`T. Davis`2005`computer graphics/vision problem`\nx = lsqr (A,b) ; imagesc (abs (fftshift (fft2 (reshape (x, 384, 384))))) ;\n | |
| 1318`Bydder`mri2`63240`147456`569160`no`48321`438`42860`0`0%`0%`real`rectangular`no`no`M. Bydder`T. Davis`2005`computer graphics/vision problem`\nx = lsqr (A,b) ; imagesc (abs (fftshift (fft2 (reshape (x, 384, 384))))) ;\n | |
| 1319`Engwirda`airfoil_2d`14214`14214`259688`yes`14214`638`638`0`98%`0%`real`unsymmetric`no`no`D. Engwirda`T. Davis`2006`computational fluid dynamics problem`\ntrimesh(t,coord(:,1),coord(:,2),A\ones(n,1))\n | |
| 1320`IBM_EDA`dc1`116835`116835`766396`yes`116835`19`19`0`85%`24%`real`unsymmetric`no`no`T. Lehner`T. Davis`2005`circuit simulation problem sequence`\nnext: IBM_EDA/dc2 first: IBM_EDA/dc1\n | |
| 1321`IBM_EDA`dc2`116835`116835`766396`yes`116835`19`19`0`85%`24%`real`unsymmetric`no`no`T. Lehner`T. Davis`2005`subsequent circuit simulation problem`\nnext: IBM_EDA/dc3 first: IBM_EDA/dc1\n | |
| 1322`IBM_EDA`dc3`116835`116835`766396`yes`116835`19`19`0`85%`24%`real`unsymmetric`no`no`T. Lehner`T. Davis`2005`subsequent circuit simulation problem`\nnext: - first: IBM_EDA/dc1\n | |
| 1323`IBM_EDA`trans4`116835`116835`749800`yes`116835`19`19`16596`85%`30%`real`unsymmetric`no`no`T. Lehner`T. Davis`2005`circuit simulation problem sequence`\nnext: IBM_EDA/trans5 first: IBM_EDA/trans4\n | |
| 1324`IBM_EDA`trans5`116835`116835`749800`yes`116835`19`19`16596`85%`30%`real`unsymmetric`no`no`T. Lehner`T. Davis`2005`subsequent circuit simulation problem`\nnext: - first: IBM_EDA/trans4\n | |
| 1325`Morandini`robot`120`120`870`yes`120`19`1`0`22%`5%`real`unsymmetric`no`no`M. Morandini`T. Davis`2006`robotics problem` | |
| 1326`Morandini`rotor1`100`100`708`yes`100`48`1`0`51%`7%`real`unsymmetric`no`no`M. Morandini`T. Davis`2006`structural problem` | |
| 1327`Morandini`rotor2`791`791`10685`yes`791`36`7`0`23%`12%`real`unsymmetric`no`no`M. Morandini`T. Davis`2006`structural problem` | |
| 1328`MathWorks`tomography`500`500`28726`yes`500`37`37`0`symmetric`93%`real`unsymmetric`no`no`D.Yang`T. Davis`2003`computer graphics/vision problem` | |
| 1329`Kemelmacher`Kemelmacher`28452`9693`100875`yes`9693`1`1`0`0%`0%`real`rectangular`no`no`I. Kemelmacher`T. Davis`2005`computer graphics/vision problem` | |
| 1330`MathWorks`Kuu`7102`7102`340200`yes`7102`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`B. Cheng`T. Davis`2006`structural problem` | |
| 1331`MathWorks`Muu`7102`7102`170134`yes`7102`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`B. Cheng`T. Davis`2006`structural problem` | |
| 1332`Toledo`deltaX`68600`21961`247424`yes`21961`1`1`0`0%`0%`real`rectangular`no`no`S. Toledo`T. Davis`2006`counter-example problem` | |
| 1333`VanVelzen`std1_Jac2_db`21982`21982`498771`yes`21982`11091`11091`0`33%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1334`VanVelzen`std1_Jac2`21982`21982`1248213`yes`21982`11091`1`518`0%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1335`VanVelzen`std1_Jac3_db`21982`21982`531826`yes`21982`11091`11091`0`36%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1336`VanVelzen`std1_Jac3`21982`21982`1455374`yes`21982`11091`1`474`0%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1337`VanVelzen`Zd_Jac2_db`22835`22835`676439`yes`22835`9833`9833`0`30%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1338`VanVelzen`Zd_Jac2`22835`22835`1642407`yes`22835`9833`1`426`0%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1339`VanVelzen`Zd_Jac3_db`22835`22835`713907`yes`22835`9833`9833`0`33%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1340`VanVelzen`Zd_Jac3`22835`22835`1915726`yes`22835`9833`1`426`0%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1341`VanVelzen`Zd_Jac6_db`22835`22835`663643`yes`22835`9990`9990`0`32%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1342`VanVelzen`Zd_Jac6`22835`22835`1711557`yes`22835`9990`1`426`0%`0%`real`unsymmetric`no`no`N. van Velzen`T. Davis`2006`chemical process simulation problem` | |
| 1343`Rajat`rajat16`94294`94294`476766`yes`94294`8549`5232`164393`99%`64%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1344`Rajat`rajat17`94294`94294`479246`yes`94294`8546`5229`161913`99%`27%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1345`Rajat`rajat18`94294`94294`479151`yes`94294`8549`5232`5992`63%`28%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1346`Rajat`rajat19`1157`1157`3699`yes`1157`734`166`1700`90%`92%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1347`Lourakis`bundle1`10581`10581`770811`yes`10581`1`1`90`symmetric`symmetric`real`symmetric`yes`yes`M. Lourakis`T. Davis`2006`computer graphics/vision problem` | |
| 1348`PARSEC`benzene`8219`8219`242669`yes`8219`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1349`PARSEC`CO`221119`221119`7666057`yes`221119`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1350`PARSEC`Ga10As10H30`113081`113081`6115633`yes`113081`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1351`PARSEC`Ga19As19H42`133123`133123`8884839`yes`133123`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1352`PARSEC`Ga3As3H12`61349`61349`5970947`yes`61349`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1353`PARSEC`Ga41As41H72`268096`268096`18488476`yes`268096`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1354`PARSEC`GaAsH6`61349`61349`3381809`yes`61349`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1355`PARSEC`Ge87H76`112985`112985`7892195`yes`112985`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1356`PARSEC`Ge99H100`112985`112985`8451395`yes`112985`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1357`PARSEC`H2O`67024`67024`2216736`yes`67024`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1358`PARSEC`Na5`5832`5832`305630`yes`5832`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1359`PARSEC`Si10H16`17077`17077`875923`yes`17077`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1360`PARSEC`Si2`769`769`17801`yes`769`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1361`PARSEC`Si34H36`97569`97569`5156379`yes`97569`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1362`PARSEC`Si41Ge41H72`185639`185639`15011265`yes`185639`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1363`PARSEC`Si5H12`19896`19896`738598`yes`19896`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1364`PARSEC`Si87H76`240369`240369`10661631`yes`240369`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1365`PARSEC`SiH4`5041`5041`171903`yes`5041`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1366`PARSEC`SiNa`5743`5743`198787`yes`5743`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1367`PARSEC`SiO2`155331`155331`11283503`yes`155331`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1368`PARSEC`SiO`33401`33401`1317655`yes`33401`1`1`0`symmetric`symmetric`real`symmetric`yes`no`Y. Zhou, Y. Saad, M. Tiago, J. Chelikowsky`T. Davis`2005`theoretical/quantum chemistry problem` | |
| 1369`Rajat`rajat20`86916`86916`604299`yes`86916`3672`1355`746`99%`11%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1370`Rajat`rajat21`411676`411676`1876011`yes`411676`10195`5956`17359`76%`61%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1371`Rajat`rajat22`39899`39899`195429`yes`39899`4466`1384`1835`98%`33%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1372`Rajat`rajat23`110355`110355`555441`yes`110355`6052`1410`1497`99%`33%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1373`Rajat`rajat24`358172`358172`1946979`yes`358172`3497`1178`1256`100%`27%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1374`Rajat`rajat25`87190`87190`606489`yes`87190`3495`1178`746`99%`11%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1375`Rajat`rajat26`51032`51032`247528`yes`51032`4666`1568`1774`99%`33%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1376`Rajat`rajat27`20640`20640`97353`yes`20640`4593`1556`2424`96%`30%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1377`Rajat`rajat28`87190`87190`606489`yes`87190`3495`1178`746`99%`11%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1378`MathWorks`Sieber`2290`2290`14873`yes`2290`1`1`0`73%`0%`real`unsymmetric`no`no`Sieber`T. Davis`2006`counter-example problem` | |
| 1379`Andrianov`ex3sta1`16782`16782`678998`yes`16782`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1380`Andrianov`fxm3_6`5026`5026`94026`yes`5026`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1381`Andrianov`fxm4_6`18892`18892`497844`yes`18892`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1382`Andrianov`ins2`309412`309412`2751484`yes`309412`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1383`Andrianov`lp1`534388`534388`1643420`yes`534388`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1384`Andrianov`lpl1`32460`32460`328036`yes`32460`3`3`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1385`Andrianov`mip1`66463`66463`10352819`yes`66463`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1386`Andrianov`net100`29920`29920`2033200`yes`29920`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1387`Andrianov`net125`36720`36720`2577200`yes`36720`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1388`Andrianov`net150`43520`43520`3121200`yes`43520`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1389`Andrianov`net25`9520`9520`401200`yes`9520`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1390`Andrianov`net4-1`88343`88343`2441727`yes`88343`97`97`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1391`Andrianov`net50`16320`16320`945200`yes`16320`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1392`Andrianov`net75`23120`23120`1489200`yes`23120`2`2`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1393`Andrianov`pattern1`19242`19242`9323432`yes`19242`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1394`Andrianov`pf2177`9728`9728`725144`yes`9728`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`A. Andrianov`T. Davis`2006`optimization problem` | |
| 1395`MKS`fp`7548`7548`834222`yes`7548`1`1`14331`76%`0%`real`unsymmetric`no`no`D. Smith`T. Davis`2006`electromagnetics problem` | |
| 1396`Rajat`rajat29`643994`643994`3760246`yes`643994`14307`4512`1106024`69%`69%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1397`Rajat`rajat30`643994`643994`6175244`yes`643994`11756`1434`133`99%`1%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1398`Rajat`rajat31`4690002`4690002`20316253`yes`4690002`2503`1`0`symmetric`40%`real`unsymmetric`no`no`Rajat`T. Davis`2006`circuit simulation problem` | |
| 1399`Raju`laminar_duct3D`67173`67173`3788857`yes`67173`13025`13025`44220`90%`55%`real`unsymmetric`no`no`M. Raju`T. Davis`2006`computational fluid dynamics problem` | |
| 1400`Bates`Chem97Zt`2541`31022`62044`yes`2541`163`131`0`0%`0%`binary`rectangular`no`no`D. Bates`T. Davis`2006`statistical/mathematical problem` | |
| 1401`Bates`Chem97ZtZ`2541`2541`7361`yes`2541`131`131`0`symmetric`symmetric`real`symmetric`yes`yes`D. Bates`T. Davis`2006`statistical/mathematical problem` | |
| 1402`Schmid`thermal1`82654`82654`574458`yes`82654`249`249`0`symmetric`symmetric`real`symmetric`yes`yes`D. Schmid`T. Davis`2006`thermal problem` | |
| 1403`Schmid`thermal2`1228045`1228045`8580313`yes`1228045`959`959`0`symmetric`symmetric`real`symmetric`yes`yes`D. Schmid`T. Davis`2006`thermal problem` | |
| 1404`MathWorks`Kaufhold`8765`8765`42471`yes`8765`256`256`0`symmetric`78%`real`unsymmetric`no`no`Kaufhold`T. Davis`2006`counter-example problem` | |
| 1405`Bindel`ted_A`10605`10605`424587`yes`10605`4244`1`0`57%`11%`real`unsymmetric`no`no`D. Bindel`T. Davis`2006`thermal problem` | |
| 1406`Bindel`ted_B`10605`10605`144579`yes`10605`4245`4245`0`symmetric`symmetric`real`symmetric`yes`yes`D. Bindel`T. Davis`2006`thermal problem` | |
| 1407`Bindel`ted_AB`10605`10605`522387`yes`10605`1`1`0`64%`0%`complex`unsymmetric`no`no`D. Bindel`T. Davis`2006`thermal problem` | |
| 1408`Bindel`ted_A_unscaled`10605`10605`424587`yes`10605`4244`1`0`57%`11%`real`unsymmetric`no`no`D. Bindel`T. Davis`2006`thermal problem` | |
| 1409`Bindel`ted_B_unscaled`10605`10605`144579`yes`10605`4245`4245`0`symmetric`symmetric`real`symmetric`yes`yes`D. Bindel`T. Davis`2006`thermal problem` | |
| 1410`Bindel`ted_AB_unscaled`10605`10605`522387`yes`10605`1`1`0`64%`0%`complex`unsymmetric`no`no`D. Bindel`T. Davis`2006`thermal problem` | |
| 1411`Koutsovasilis`F1`343791`343791`26837113`yes`343791`1`1`0`symmetric`symmetric`real`symmetric`yes`no`P. Koutsovasilis`T. Davis`2006`structural problem`\nStiffness matrix from an AUDI engine crankshaft\n | |
| 1412`AMD`G2_circuit`150102`150102`726674`yes`150102`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`U. Okuyucu`T. Davis`2006`circuit simulation problem` | |
| 1413`IBM_EDA`ckt11752_dc_1`49702`49702`333029`yes`49702`172`172`0`98%`74%`real`unsymmetric`no`no`T. Lehner`T. Davis`2006`circuit simulation problem` | |
| 1414`IBM_EDA`ckt11752_tr_0`49702`49702`332807`yes`49702`199`199`222`98%`74%`real`unsymmetric`no`no`T. Lehner`T. Davis`2006`circuit simulation problem` | |
| 1415`Sandia`ASIC_100k`99340`99340`940621`yes`99340`399`1`13542`symmetric`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2006`circuit simulation problem` | |
| 1416`Sandia`ASIC_100ks`99190`99190`578890`yes`99190`249`249`0`symmetric`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2006`circuit simulation problem` | |
| 1417`Sandia`ASIC_320k`321821`321821`1931828`yes`321821`399`1`703536`symmetric`36%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2006`circuit simulation problem` | |
| 1418`Sandia`ASIC_320ks`321671`321671`1316085`yes`321671`249`249`511722`symmetric`29%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2006`circuit simulation problem` | |
| 1419`Sandia`ASIC_680k`682862`682862`2638997`yes`682862`583921`583523`1232776`symmetric`0%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2006`circuit simulation problem` | |
| 1420`Sandia`ASIC_680ks`682712`682712`1693767`yes`682712`583771`583771`635409`symmetric`1%`real`unsymmetric`no`no`R. Hoekstra`T. Davis`2006`circuit simulation problem` | |
| 1421`AMD`G3_circuit`1585478`1585478`7660826`yes`1585478`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`U. Okuyucu`T. Davis`2006`circuit simulation problem` | |
| 1422`GHS_psdef`apache1`80800`80800`542184`yes`80800`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`unknown`N. Gould, Y. Hu, J. Scott`2006`structural problem` | |
| 1423`GHS_psdef`apache2`715176`715176`4817870`yes`715176`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`unknown`N. Gould, Y. Hu, J. Scott`2006`structural problem` | |
| 1424`GHS_indef`bloweybl`30003`30003`109999`no`30002`20003`2`10001`symmetric`symmetric`real`symmetric`no`no`J. Blowey`N. Gould`1992`materials problem` | |
| 1425`GHS_indef`bloweybq`10001`10001`49999`yes`10001`1`1`19992`symmetric`symmetric`real`symmetric`yes`yes`J. Blowey`N. Gould`1992`materials problem` | |
| 1426`GHS_indef`cvxqp3`17500`17500`114962`yes`17500`1`1`7500`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1995`optimization problem` | |
| 1427`GHS_indef`qpband`20000`20000`45000`yes`20000`5000`5000`0`symmetric`symmetric`real`symmetric`no`no`N. Gould`N. Gould`1999`optimization problem` | |
| 1428`Oberwolfach`chipcool0`20082`20082`281150`yes`20082`1`1`0`symmetric`87%`real`unsymmetric`no`no`C. Moosmann, A. Griener`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1429`Oberwolfach`chipcool1`20082`20082`281150`yes`20082`1`1`0`symmetric`9%`real`unsymmetric`no`no`C. Moosmann, A. Griener`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1430`Oberwolfach`filter2D`1668`1668`10750`yes`1668`1`1`0`symmetric`symmetric`real`symmetric`no`no`D. Hohlfield, T. Bechtold, H. Zappe`E. Rudnyi`2006`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1431`Oberwolfach`filter3D`106437`106437`2707179`yes`106437`1`1`0`symmetric`symmetric`real`symmetric`no`no`D. Hohlfield, T. Bechtold, H. Zappe`E. Rudnyi`2006`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1432`Oberwolfach`flowmeter0`9669`9669`67391`yes`9669`1`1`0`symmetric`symmetric`real`symmetric`no`no`C. Moosmann, A. Griener`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1433`Oberwolfach`flowmeter5`9669`9669`67391`yes`9669`1`1`0`symmetric`6%`real`unsymmetric`no`no`C. Moosmann, A. Griener`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1434`Oberwolfach`gas_sensor`66917`66917`1703365`yes`66917`1`1`0`symmetric`symmetric`real`symmetric`no`no`J. Hildenbrand`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1435`Oberwolfach`gyro`17361`17361`1021159`yes`17361`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`D. Billger`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1436`Oberwolfach`inlet`11730`11730`328323`yes`11730`331`331`0`61%`0%`real`unsymmetric`no`no`K. Willcox, G. Lassaux, D. Gratton`E. Rudnyi`2006`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1437`Oberwolfach`LF10000`19998`19998`99982`yes`19998`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lienemann, A. Greiner, J. Korvink`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1438`Oberwolfach`LF10`18`18`82`yes`18`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lienemann, A. Greiner, J. Korvink`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1439`Oberwolfach`LFAT5000`19994`19994`79966`yes`19994`3`3`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lienemann, A. Greiner, J. Korvink`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1440`Oberwolfach`LFAT5`14`14`46`yes`14`3`3`0`symmetric`symmetric`real`symmetric`yes`yes`J. Lienemann, A. Greiner, J. Korvink`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1441`Oberwolfach`piston`2025`2025`100015`yes`2025`1`1`0`symmetric`3%`real`unsymmetric`no`no`K. Meerbergen`E. Rudnyi`2006`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1442`Oberwolfach`rail_1357`1357`1357`8985`yes`1357`1`1`0`symmetric`symmetric`real`symmetric`no`no`P. Benner, J. Saak`E. Rudnyi`2002`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1443`Oberwolfach`rail_20209`20209`20209`139233`yes`20209`1`1`0`symmetric`symmetric`real`symmetric`no`no`P. Benner, J. Saak`E. Rudnyi`2002`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1444`Oberwolfach`rail_5177`5177`5177`35185`yes`5177`1`1`0`symmetric`symmetric`real`symmetric`no`no`P. Benner, J. Saak`E. Rudnyi`2002`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1445`Oberwolfach`rail_79841`79841`79841`553921`yes`79841`1`1`0`symmetric`symmetric`real`symmetric`no`no`P. Benner, J. Saak`E. Rudnyi`2002`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1446`Oberwolfach`spiral`1434`1434`18228`yes`1434`30`30`0`symmetric`symmetric`real`symmetric`no`no`J. Li, M. Kamon`E. Rudnyi`2006`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1447`Oberwolfach`t2dah`11445`11445`176117`yes`11445`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1448`Oberwolfach`t2dal_bci`4257`4257`37465`yes`4257`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1449`Oberwolfach`t2dal`4257`4257`37465`yes`4257`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1450`Oberwolfach`t3dh`79171`79171`4352105`yes`79171`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1451`Oberwolfach`t3dl`20360`20360`509866`yes`20360`1`1`0`symmetric`symmetric`real`symmetric`no`no`E. Rudnyi`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach A matrix\n | |
| 1452`Oberwolfach`windscreen`22692`22692`1482390`yes`22692`1`1`0`symmetric`0%`complex`symmetric`no`no`K. Meerbergen`E. Rudnyi`2004`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1453`Oberwolfach`bone010`986703`986703`47851783`yes`986703`2`2`23814542`symmetric`symmetric`real`symmetric`yes`yes`B. van Rietbergen, E. Rudnyi, J. Korvink`E. Rudnyi`2006`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1454`Oberwolfach`boneS01`127224`127224`5516602`yes`127224`1`1`1198550`symmetric`symmetric`real`symmetric`yes`yes`B. van Rietbergen, E. Rudnyi, J. Korvink`E. Rudnyi`2006`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1455`Oberwolfach`boneS10`914898`914898`40878708`yes`914898`1`1`14589714`symmetric`symmetric`real`symmetric`yes`yes`B. van Rietbergen, E. Rudnyi, J. Korvink`E. Rudnyi`2006`model reduction problem`\nPrimary matrix in this model reduction problem is the Oberwolfach K matrix\n | |
| 1456`Pajek`California`9664`9664`16150`unknown`unknown`unknown`9450`0`2%`2%`binary`unsymmetric`no`no`J. Kleinberg`V. Batagelj`2006`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n California - Pages matching the query \"California\". \n This graph was constructed by expanding a 200-page response set to \n a search engine query 'California', as in the hub/authority algorithm. \n from Jon Kleinberg: \n http://www.cs.cornell.edu/courses/cs685/2002fa/ \n adapted for Pajek, V. Batagelj, March 19, 2006 \n 0 -> 9664 \n | |
| 1457`Pajek`Cities`55`46`1342`yes`46`1`1`0`0%`0%`integer`rectangular`no`no`P. Taylor, D. Walker`V. Batagelj`2001`weighted bipartite graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n http://www.lboro.ac.uk/gawc/datasets/da6.html \n Accountancy \n Advertising \n Banking and Finance \n Law \n | |
| 1458`Pajek`CSphd`1882`1882`1740`unknown`unknown`unknown`1882`0`0%`0%`binary`unsymmetric`no`no`unknown`V. Batagelj`2006`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1459`Pajek`dictionary28`52652`52652`178076`unknown`unknown`unknown`17903`0`symmetric`symmetric`binary`symmetric`no`no`unknown`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1460`Pajek`divorce`50`9`225`yes`9`1`1`0`0%`0%`binary`rectangular`no`no`unknown`V. Batagelj`2006`bipartite graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n http://www.stat.lsa.umich.edu/~faraway/stat503/labs/ \n | |
| 1461`Pajek`EAT_RS`23219`23219`325592`unknown`unknown`unknown`15466`0`12%`3%`integer`unsymmetric`no`no`G. Kiss, C. Armstrong R. Milroy, J. Piper`V. Batagelj`1971`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n EAT - The Edinburgh Associative Thesaurus / \n response-stimulus \n -------------------------------------------------------- \n The EAT is a database of word association norms. \n - Original EAT: George Kiss, Christine Armstrong, \n Robert Milroy and J.R.I. Piper (1968-1971). \n - MRC Psycholinguistic Database Version modified by: \n Max Coltheart, S. James, J. Ramshaw, B.M. Philip, \n B. Reid, J. Benyon-Tinker and E. Doctor; \n made available by: Philip Quinlan. \n - The present version was re-structured and documented \n by Michael Wilson at the Rutherford Appleton Laboratory. \n http://monkey.cis.rl.ac.uk/Eat/htdocs/eat.zip \n \n transformed in Pajek format: V. Batagelj, 31. July 2003 \n ----- \n------------------------------------------------------------------------------\nRegarding conversion for UF sparse matrix collection: in the original data \nthere are 325624 weighted edges. Of those only 32 edges are duplicates, and \nall of them have identical edge weights as the edges they are duplicates of \nThese extraneous edges have been removed, since this this appears to be a \ngraph, not a multigraph. \n------------------------------------------------------------------------------\n | |
| 1462`Pajek`EAT_SR`23219`23219`325589`unknown`unknown`unknown`15466`0`12%`3%`integer`unsymmetric`no`no`G. Kiss, C. Armstrong R. Milroy, J. Piper`V. Batagelj`1971`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n EAT - The Edinburgh Associative Thesaurus / \n stimulus-response \n -------------------------------------------------------- \n The EAT is a database of word association norms. \n - Original EAT: George Kiss, Christine Armstrong, \n Robert Milroy and J.R.I. Piper (1968-1971). \n - MRC Psycholinguistic Database Version modified by: \n Max Coltheart, S. James, J. Ramshaw, B.M. Philip, \n B. Reid, J. Benyon-Tinker and E. Doctor; \n made available by: Philip Quinlan. \n - The present version was re-structured and documented \n by Michael Wilson at the Rutherford Appleton Laboratory. \n http://monkey.cis.rl.ac.uk/Eat/htdocs/eat.zip \n \n transformed in Pajek format: V. Batagelj, 31. July 2003 \n ----- \n | |
| 1463`Pajek`EPA`4772`4772`8965`unknown`unknown`unknown`4711`0`1%`1%`binary`unsymmetric`no`no`J. Kleinberg`V. Batagelj`2006`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Epa - Pages linking to www.epa.gov. \n This graph was constructed by expanding a 200-page response set to \n a search engine query, as in the hub/authority algorithm. \n from Jon Kleinberg: \n http://www.cs.cornell.edu/courses/cs685/2002fa/ \n adapted for Pajek, V. Batagelj, March 19, 2006 \n 0 -> 4772 \n | |
| 1464`Pajek`Erdos02`6927`6927`16944`unknown`unknown`unknown`1394`0`symmetric`symmetric`binary`symmetric`no`no`J. Grossman, P. Iain, R. Castro`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Erdos collaboration network: \n Erdos included, version 2002 \n | |
| 1465`Pajek`Erdos971`472`472`2628`unknown`unknown`unknown`42`0`symmetric`symmetric`binary`symmetric`no`no`J. Grossman, P. Iain, R. Castro`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1466`Pajek`Erdos972`5488`5488`14170`unknown`unknown`unknown`754`0`symmetric`symmetric`binary`symmetric`no`no`J. Grossman, P. Iain, R. Castro`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1467`Pajek`Erdos981`485`485`2762`unknown`unknown`unknown`44`0`symmetric`symmetric`binary`symmetric`no`no`J. Grossman, P. Iain, R. Castro`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1468`Pajek`Erdos982`5822`5822`14750`unknown`unknown`unknown`877`0`symmetric`symmetric`binary`symmetric`no`no`J. Grossman, P. Iain, R. Castro`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1469`Pajek`Erdos991`492`492`2834`unknown`unknown`unknown`43`0`symmetric`symmetric`binary`symmetric`no`no`J. Grossman, P. Iain, R. Castro`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1470`Pajek`Erdos992`6100`6100`15030`unknown`unknown`unknown`1023`0`symmetric`symmetric`binary`symmetric`no`no`J. Grossman, P. Iain, R. Castro`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1471`Pajek`EVA`8497`8497`6726`unknown`unknown`unknown`8482`0`0%`0%`binary`unsymmetric`no`no`K. Norlen, G. Lucas, M. Gebbie, J. Chuang`V. Batagelj`2002`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1472`Pajek`FA`10617`10617`72176`unknown`unknown`unknown`5764`0`23%`1%`real`unsymmetric`no`no`USF`V. Batagelj`2006`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1473`Pajek`foldoc`13356`13356`120238`unknown`unknown`unknown`71`0`48%`46%`integer`unsymmetric`no`no`D. Howe`V. Batagelj, A. Mrvar`2002`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1474`Pajek`football`35`35`118`unknown`unknown`unknown`35`0`0%`0%`integer`unsymmetric`no`no`L. Krempel`V. Batagelj`1998`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1475`Pajek`GD00_a`352`352`458`unknown`unknown`unknown`352`0`0%`0%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2000`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1476`Pajek`GD00_c`638`638`1041`unknown`unknown`unknown`566`0`2%`2%`integer`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2000`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1477`Pajek`GD01_a`311`311`645`unknown`unknown`unknown`303`0`2%`2%`integer`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2001`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1478`Pajek`GD01_A`953`953`645`unknown`unknown`unknown`945`0`2%`2%`integer`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2001`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1479`Pajek`GD01_b`18`18`37`unknown`unknown`unknown`1`0`51%`51%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2001`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1480`Pajek`GD01_c`33`33`135`unknown`unknown`unknown`33`0`0%`0%`integer`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2001`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1481`Pajek`GD02_a`23`23`87`unknown`unknown`unknown`3`0`64%`64%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2002`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1482`Pajek`GD02_b`80`80`232`unknown`unknown`unknown`11`0`0%`0%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2002`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1483`Pajek`GD06_Java`1538`1538`8032`unknown`unknown`unknown`1028`0`5%`5%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`2006`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n GD 2006 contest graph C: Java Dependency graph \n http://gd2006.org/contest/details.php#java \n graph in Pajek format \n transformed by Vladimir Batagelj, July 10, 2006 \n | |
| 1484`Pajek`GD06_theory`101`101`380`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`Graph Drawing Contest`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n GD 2006 contest graph A: Theory \n http://gd2006.org/contest/details.php#theory \n graph in Pajek format \n transformed by Vladimir Batagelj, July 10, 2006 \n | |
| 1485`Pajek`GD95_a`36`36`57`unknown`unknown`unknown`4`0`4%`4%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1995`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1486`Pajek`GD95_b`73`73`96`unknown`unknown`unknown`71`0`0%`0%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1995`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1487`Pajek`GD95_c`62`62`287`unknown`unknown`unknown`1`0`100%`100%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1995`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1488`Pajek`GD96_a`1096`1096`1677`unknown`unknown`unknown`1096`0`0%`0%`integer`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1996`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1489`Pajek`GD96_b`111`111`193`unknown`unknown`unknown`111`0`0%`0%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1996`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1490`Pajek`GD96_c`65`65`250`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`Graph Drawing Contest`V. Batagelj`1996`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1491`Pajek`GD96_d`180`180`229`unknown`unknown`unknown`168`0`1%`1%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1996`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1492`Pajek`GD97_a`84`84`332`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`Graph Drawing Contest`V. Batagelj`1997`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1493`Pajek`GD97_b`47`47`264`unknown`unknown`unknown`2`0`symmetric`symmetric`real`symmetric`no`no`Graph Drawing Contest`V. Batagelj`1997`undirected weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nRegarding conversion for UF sparse matrix collection: in the original data \nevery edge appears exactly twice, with the same edge weight. It could be a \nmultigraph, but it looks more like a graph. The duplicate edges are removed \nin this version. You can always add them back in yourself; just look at 2*A. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1494`Pajek`GD97_c`452`452`460`unknown`unknown`unknown`452`0`0%`0%`integer`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1997`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1495`Pajek`GD98_a`38`38`50`unknown`unknown`unknown`35`0`16%`16%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1998`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1496`Pajek`GD98_b`121`121`207`unknown`unknown`unknown`12`0`72%`72%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1998`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5241, and have been removed. This graph has 2D coordinates. \n | |
| 1497`Pajek`GD98_c`112`112`336`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`Graph Drawing Contest`V. Batagelj`1998`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1498`Pajek`GD99_b`64`64`252`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`Graph Drawing Contest`V. Batagelj`1999`undirected multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1499`Pajek`GD99_c`105`105`149`unknown`unknown`unknown`66`0`39%`39%`binary`unsymmetric`no`no`Graph Drawing Contest`V. Batagelj`1999`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1500`Pajek`geom`7343`7343`23796`unknown`unknown`unknown`2060`0`symmetric`symmetric`integer`symmetric`no`no`Edelsbrunner, van Leeuwen, Guibas, Stolfi`V. Batagelj`2002`undirected weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1501`Pajek`GlossGT`72`72`122`unknown`unknown`unknown`68`0`7%`7%`binary`unsymmetric`no`no`W. Cherowitzo`V. Batagelj`2001`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Bill Cherowitzo: Graph and Digraph Glossary \n http://www-math.cudenver.edu/~wcherowi/courses/m4408/glossary.html \n Pajek's network: Barbara Zemlji\"c, 2. nov 2003 \nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1502`Pajek`HEP-th`27240`27240`342437`unknown`unknown`unknown`19565`0`0%`0%`binary`unsymmetric`no`no`KDD Cup 2003`V. Batagelj`2003`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n High Energy Particle Physics (HEP) literature \n --------------------------------------------- \n Citation data from KDD Cup 2003, a knowledge discovery and data mining \n competition held in conjunction with the Ninth Annual ACM SIGKDD Conference. \n http://www.cs.cornell.edu/projects/kddcup/index.html \n The Stanford Linear Accelerator Center SPIRES-HEP database has been \n comprehensively cataloguing the High Energy Particle Physics (HEP) literature\n online since 1974, and indexes more than 500000 high-energy physics related \n articles including their full citation tree. \n The network contains a citation graph of the hep-th portion of the arXiv. \n The units names are the arXiv IDs of papers; the relation is X cites Y . \n Note that revised papers may have updated citations. As such, citations may \n refer to future papers, i.e. a paper may cite another paper that was publishe\n after the first paper. \n Update May 12, 2003 is not included. \n \n transformed in Pajek format: V. Batagelj, 26. July 2003 \n ----- \n | |
| 1503`Pajek`HEP-th-new`27770`27770`352807`unknown`unknown`unknown`20086`0`0%`0%`binary`unsymmetric`no`no`KDD Cup 2003`V. Batagelj`2003`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n High Energy Particle Physics (HEP) literature with May 12, 2003 Update \n ---------------------------------------------------------------------- \n Citation data from KDD Cup 2003, a knowledge discovery and data mining \n competition held in conjunction with the Ninth Annual ACM SIGKDD Conference. \n http://www.cs.cornell.edu/projects/kddcup/index.html \n The Stanford Linear Accelerator Center SPIRES-HEP database has been \n comprehensively cataloguing the High Energy Particle Physics (HEP) literature\n online since 1974, and indexes more than 500000 high-energy physics related \n articles including their full citation tree. \n The network contains a citation graph of the hep-th portion of the arXiv. \n The units names are the arXiv IDs of papers; the relation is X cites Y . \n Note that revised papers may have updated citations. As such, citations may \n refer to future papers, i.e. a paper may cite another paper that was publishe\n after the first paper. \n \n transformed in Pajek format: V. Batagelj, 26. July 2003 \n \n year: \n The SLAC/SPIRES dates for all hep-th papers are given. Some older papers were\n uploaded years after their intial publication and the arXiv submission date \n from the abstracts may not correspond to the publication date. An alternative\n date has been provided from SLAC/SPIRES that may be a better estimate \n for the initial publication of these old papers. \n The vector contains the year in SLAC date of each paper. \n \n date: \n SLAC date of paper was transformed to the number of days since August 1, 1991\n | |
| 1504`Pajek`IMDB`428440`896308`3782463`no`250516`34003`132714`0`0%`0%`binary`rectangular`no`no`www.imdb.com`V. Batagelj`2006`bipartite graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nA(i,j)=1 if actor j played in movie i. colname(j,:) is the name of the actor.\nColumn j = 362181 is Kevin Bacon. Year of movie i is year(i). \ncategory(i) gives the category of movie i, use code(category(i),:). \n1: Drama, 2: Short, 3: Documentary, 4: Comedy, 5: Western, 6: Family, \n7: Mystery, 8: Thriller, 9: -, 10: Music, 11: Crime, 12: Sci-Fi, 13: Horror, \n14: War, 15: Fantasy, 16: Romance, 17: Adventure, 18: Animation, 19: Action, \n20: Musical, 21: Film-Noir, 99: Unknown. \nRemember that in MATLAB, A(i,:) is slow to compute; A(:,i) is faster. If you \nwant row i of a sparse matrix, access the ith column of the transpose instead.\naux.ActorBacon(j) is the Bacon number of actor j. aux.MovieBacon(i) is the \nBacon number of movie i. The largest ActorBacon number is 8 (for 10 actors). \n------------------------------------------------------------------------------\nMATLAB code for computing the Bacon numbers \n Bacon = Problem.aux.KevinBacon ; \n Bacon = Problem.aux.KevinBacon ; \n A = Problem.A ; \n [m n] = size (A) ; \n C = [speye(m) A ; A' speye(n)] ; \n x = zeros (m+n,1) ; \n B = inf * ones (m+n,1) ; \n x (m + Bacon) = 1 ; \n B (m + Bacon) = 0 ; \n tlen = 1 ; \n for k = 1:m+n \n x = x + C*x ; \n t = find (x) ; \n if (tlen == length (t)) \n break \n end \n tlen = length (t) ; \n B (t) = min (B (t), k) ; \n end \n MovieBacon = (B (1:m) - 1) / 2 ; \n ActorBacon = B (m+1:end) / 2 ; \n | |
| 1505`Pajek`internet`124651`124651`207214`unknown`unknown`unknown`116713`0`1%`0%`integer`unsymmetric`no`no`unknown`V. Batagelj`2006`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1506`Pajek`Journals`124`124`12068`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`yes`yes`CATI Center Ljubljana`V. Batagelj`2000`undirected weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n slovenske revije / Cati center, Ljubljana \n leto 1999 + leto 2000 / vsi anketirani \n 1 dnevniki 8 revije\mo�ke specializirane \n 2 revije\poslovne 9 revije\najstni�ke \n 3 revije\racunalni�ke 10 revije\regionalne \n 4 revije\dom in oprema 11 revije\specializirane \n 5 revije\modne 12 revije\�enske specializirane \n 6 revije\informativni tedniki 13 revije\tv vodici \n 7 revije\brezplacniki 14 revije\�enske \n | |
| 1507`Pajek`Kohonen`4470`4470`12731`unknown`unknown`unknown`4459`0`0%`0%`binary`unsymmetric`no`no`E. Garfield`V. Batagelj, A. Mrvar`2002`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Articles with topic \"self-organizing maps\" or references to \"Kohonen T\", \nTue Jun 18 10:39:51 2002 \n | |
| 1508`Pajek`Lederberg`8843`8843`41601`unknown`unknown`unknown`8781`0`0%`0%`integer`unsymmetric`no`no`E. Garfield`V. Batagelj`2002`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Articles by and citing J Lederberg, 1945-2002, Wed Jul 31 13:40:22 2002 \n | |
| 1509`Barabasi`NotreDame_actors`392400`127823`1470404`no`114762`19604`11902`0`0%`0%`binary`rectangular`no`no`A Barabasi, R. Albert`H. Jeong`1999`bipartite graph`\nhttp://www.nd.edu/~networks (14 duplicate entries removed)\n | |
| 1510`Barabasi`NotreDame_www`325729`325729`929849`unknown`unknown`unknown`231666`0`33%`33%`binary`unsymmetric`no`no`R. Albert, H. Jeong, A. Barabasi`H. Jeong`1999`directed graph`\nhttp://www.nd.edu/~networks\n | |
| 1511`Barabasi`NotreDame_yeast`2114`2114`4480`unknown`unknown`unknown`417`0`symmetric`symmetric`binary`symmetric`no`no`H. Jeong, S. Mason, A. Barabasi, Z. Oltvai`H. Jeong`2001`undirected graph`\nhttp://www.nd.edu/~networks\n | |
| 1512`Pajek`ODLIS`2909`2909`18246`unknown`unknown`unknown`1028`0`20%`20%`integer`unsymmetric`no`no`J. Reitz`V. Batagelj, A. Mrvar`2000`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1513`Pajek`patents_main`240547`240547`560943`unknown`unknown`unknown`240547`0`0%`0%`real`unsymmetric`no`no`B. Hall, A. Jaffe, M. Tratjenberg`V. Batagelj`2001`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nRegarding conversion for UF sparse matrix collection: in the original data \nthere are 561060 weighted edges. Of this, 117 are duplicates, with identical\nedge weights. These extraneous edges have been removed in this version. \nAlso, the original data has auxiliary data for all 6009554 US Patents in the\ntime period. This patent network has only 240547 patents, and the auxiliary \ndata (appyear, class, etc.) is matched here to the nodes of the graph. \n------------------------------------------------------------------------------\n | |
| 1514`Pajek`patents`3774768`3774768`14970767`unknown`unknown`unknown`3774768`0`0%`0%`binary`unsymmetric`no`no`B. Hall, A. Jaffe, M. Tratjenberg`V. Batagelj`2001`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nRegarding conversion for UF sparse matrix collection: in the original data \nthere are 14973817 edges (unweighted). Of this, 3050 are duplicates \nThis graph is binary; the duplicates have been removed. \nAlso, the original data has auxiliary data for all 6009554 US Patents in the\ntime period. This patent network has only 3774768 patents, and the auxiliar\ndata (appyear, class, etc.) is matched here to the nodes of the graph. \n------------------------------------------------------------------------------\n | |
| 1515`Pajek`Ragusa16`24`24`81`unknown`unknown`unknown`10`0`37%`20%`integer`unsymmetric`no`no`V. Batagelj`V. Batagelj`2006`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1516`Pajek`Ragusa18`23`23`64`unknown`unknown`unknown`8`0`33%`20%`integer`unsymmetric`no`no`V. Batagelj`V. Batagelj`2006`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1517`Pajek`Reuters911`13332`13332`296076`unknown`unknown`unknown`22`0`symmetric`symmetric`integer`symmetric`no`no`S. Corman, T. Kuhn, R. Mcphee, K. Dooley`V. Batagelj, A. Mrvar`2001`undirected weighted graph sequence`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. This is the \"Days\" network. \n------------------------------------------------------------------------------\nThe Reuters terror news network is based on all stories released during 66 \nconsecutive days by the news agency Reuters concerning the September 11 attack\non the U.S., beginning at 9:00 AM EST 9/11/01. The vertices of a network are \nwords (terms); there is an edge between two words iff they appear in the same \ntext unit (sentence). The weight of an edge is its frequency. The network has \nn=13332 vertices (different words in the news) and m = 243447 edges, 50859 \nwith value larger than 1. There are no loops in the network. \nSteven R. Corman, Timothy Kuhn, Robert D. Mcphee and Kevin J. Dooley \n(2002): Studying Complex Discursive Systems: Centering Resonance Analysis of \nCommunication. \n------------------------------------------------------------------------------\nWhen converted to a sparse adjacency matrix for the UF Sparse Matrix \nCollection, Day{i} is the graph of the ith day. The diagonal entry \nDay{i}(k,k) is 1 if word k appears in any news on the ith day. Note \nthat it may not appear in conjunction with other words in the same \nsentence on that day. The sum of nnz(tril(Day{i})) for i=1:66 is 243447. \nThe overall matrix A is the sum of the Day{i} matrices. A(i,j) is the number \nof times words i and j appear in same sentence (for i not equal to j). A(k,k)\nis the number of days the word k appears in any news report. \nNote that this network has been renamed to Reuters911 here. \n------------------------------------------------------------------------------\n | |
| 1518`Pajek`Roget`1022`1022`5075`unknown`unknown`unknown`77`0`56%`56%`binary`unsymmetric`no`no`D. Knuth`V. Batagelj`1993`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n | |
| 1519`Pajek`Sandi_authors`86`86`248`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`I. Klavzar`V. Batagelj`1999`undirected weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1520`Pajek`Sandi_sandi`314`360`613`no`246`122`129`0`0%`0%`binary`rectangular`no`no`I. Klavzar`V. Batagelj`1999`bipartite graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1521`Pajek`SciMet`3084`3084`10413`unknown`unknown`unknown`3072`0`0%`0%`integer`unsymmetric`no`no`E. Garfield`V. Batagelj`2002`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Articles from or citing Scientometrics, 1978-2000, Wed Jun 12 16:39:51 2002 \n | |
| 1522`Pajek`SmaGri`1059`1059`4919`unknown`unknown`unknown`1057`0`0%`0%`integer`unsymmetric`no`no`E. Garfield`V. Batagelj`2001`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Citations to Small & Griffith and Descendants, Thu Nov 8 10:40:55 2001 \n | |
| 1523`Pajek`SmallW`396`396`994`unknown`unknown`unknown`396`0`0%`0%`integer`unsymmetric`no`no`E. Garfield`V. Batagelj`2002`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Papers that cite S Milgram's 1967 Psychology Today paper or use Small World \nTue Jul 23 13:35:11 2002 \n | |
| 1524`Pajek`Stranke94`10`10`90`unknown`unknown`unknown`1`0`symmetric`symmetric`integer`symmetric`no`no`V. Batagelj`V. Batagelj`1994`undirected weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Samo Kropivnik and Andrej Mrvar: \n An Analysis of the Slovene Parliamentary Parties Network. \n Developments in Statistics and Methodology. (A. Ferligoj, A. Kramberger, ed\n Metodolo\"ski zvezki 12, FDV, Ljubljana, 1996, p. 209-216. \n SKD - Slovene Christian Democrats; \n ZLSD - Associated List of Social Democrats; \n SDSS - Social Democratic Party of Slovenia; \n LDS - Liberal Democratic Party; \n ZS-ESS - first of two Green Parties, separated after 1992 elections; \n ZS - second Green Party; \n DS - Democratic Party; \n SLS - Slovene People's Party; \n SPS SNS - a group of deputies, former members of SNS, separated after 1992 el\n SNS - Slovene National Party; \n ------------------------------------ \nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1525`Pajek`Tina_AskCal`11`11`29`unknown`unknown`unknown`4`0`28%`28%`binary`unsymmetric`no`no`V. Batagelj`V. Batagelj`1992`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n STUDENT GOVERNMENT OF UNIVERSITY OF LJUBLJANA (Hlebec 1992) \n asking for an opinion, recall \n | |
| 1526`Pajek`Tina_AskCog`11`11`36`unknown`unknown`unknown`1`0`50%`50%`binary`unsymmetric`no`no`V. Batagelj`V. Batagelj`1992`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n STUDENT GOVERNMENT OF UNIVERSITY OF LJUBLJANA (Hlebec 1992) \n asking for an opinion, recognition \n | |
| 1527`Pajek`Tina_DisCal`11`11`41`unknown`unknown`unknown`3`0`44%`44%`binary`unsymmetric`no`no`V. Batagelj`V. Batagelj`1992`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0, and have been removed. This graph has 2D coordinates. \n | |
| 1528`Pajek`Tina_DisCog`11`11`48`unknown`unknown`unknown`1`0`50%`50%`binary`unsymmetric`no`no`V. Batagelj`V. Batagelj`1992`directed graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n STUDENT GOVERNMENT OF UNIVERSITY OF LJUBLJANA (Hlebec 1992) \n discussion, recognition \n | |
| 1529`Pajek`USAir97`332`332`4252`unknown`unknown`unknown`1`0`symmetric`symmetric`real`symmetric`no`no`US Air`V. Batagelj`1997`undirected weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nThe original problem had 3D xyz coordinates, but all values of z were equal \nto 0.5, and have been removed. This graph has 2D coordinates. \n | |
| 1530`Pajek`USpowerGrid`4941`4941`13188`unknown`unknown`unknown`1`0`symmetric`symmetric`binary`symmetric`no`no`P. Tsaparas`V. Batagelj`2006`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n US power grid - unweighted network \n from Panayiotis Tsaparas: \n http://www.cs.helsinki.fi/u/tsaparas/MACN2006/data-code.html \n adapted for Pajek, V. Batagelj, March 19, 2006 \n 0 -> 4941 \n | |
| 1531`Pajek`Wordnet3`82670`82670`132964`unknown`unknown`unknown`67689`0`18%`17%`integer`unsymmetric`no`no`unknown`V. Batagelj`2006`directed weighted graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\nNOTE: this is a binary graph in the Pajek dataset, but where each edge has a \nlabel (not a weight) in the range 1 to 9. The following labels are used: \n1 hypernym pointer \n2 entailment pointer \n3 similar pointer \n4 member meronym pointer \n5 substance meronym pointer \n6 part meronym pointer \n7 cause pointer \n8 grouped pointer \n9 attribute pointer \nThis is not a multigraph. There are no edges (i,j) between the same nodes \nwith the same label. Thus, in the sparse matrix, the edge weight A(i,j) \nrepresents the label 1 through 9 of edge (i,j). No loss of information \noccurs in this translation. The above table is in aux.edgecode(1:9,:). \nEach node is a word in a dictionary. aux.category(i) gives the category \nof the word: \n 1: n (noun?) 63099 words \n 3: a (adjective?) 5501 words \n 4: r (?) 2846 words \n 5: s (?) 6728 words. \n------------------------------------------------------------------------------\n | |
| 1532`Pajek`WorldCities`315`100`7518`yes`100`1`3`0`0%`0%`integer`rectangular`no`no`P. Taylor, G. Gatalano`V. Batagelj`2004`weighted bipartite graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n World Cities and Services - two-mode network \n http://www.lboro.ac.uk/gawc/datasets/da11.html \n Transformed in Pajek format by V. Batagelj, March 20, 2006 \n city-by-service matrix. service codes: \n 1 - accountancy 2 - advertising 3 - banking/finance \n 4 - insurance 5 - law 6 - management consultancy \n | |
| 1533`Pajek`yeast`2361`2361`13828`unknown`unknown`unknown`101`0`symmetric`symmetric`binary`symmetric`no`no`S. Sun, L. Ling, N. Zhang, G. Li, R. Chen`V. Batagelj`2003`undirected graph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Yeast protein interaction / long names \n --------------------------------------- \n Dongbo Bu, etal.: Topological structure analysis of the \n protein-protein interaction network in budding yeast. \n Nucleic Acids Research, 2003, Vol. 31, No. 9 2443-2450 \n http://www.bioinfo.org.cn/PIN/ \n http://www.imb-jena.de/jcb/ppi/PPI_PDF_free/bu2003.pdf \n \n transformed in Pajek format: V. Batagelj, 25. July 2003 \n ----- \n Yeast protein interaction / PIN class \n ------------------------------------- \n Dongbo Bu, etal.: Topological structure analysis of the \n protein-protein interaction network in budding yeast. \n Nucleic Acids Research, 2003, Vol. 31, No. 9 2443-2450 \n http://www.bioinfo.org.cn/PIN/ \n \n transformed in Pajek format: V. Batagelj, 25. July 2003 \n PIN class encoding: \n 1-T, 2-M, 3-U, 4-C, 5-F, 6-P, 7-G, 8-D, 9-O, 10-E, 11-R, 12-B, 13-A \n ----- \n | |
| 1534`Pajek`Zewail`6752`6752`54233`unknown`unknown`unknown`6706`0`0%`0%`integer`unsymmetric`no`no`E. Garfield`V. Batagelj`2002`directed multigraph`\n------------------------------------------------------------------------------\nPajek network converted to sparse adjacency matrix for inclusion in UF sparse \nmatrix collection, Tim Davis. For Pajek datasets, See V. Batagelj & A. Mrvar,\nhttp://vlado.fmf.uni-lj.si/pub/networks/data/. \n------------------------------------------------------------------------------\n Articles citing and by AH Zewail, 1970-2002, Wed Jul 31 15:46:38 2002 \n | |
| 1535`Zitney`extr1b`2836`2836`10965`yes`2836`869`1`439`0%`0%`real`unsymmetric`no`no`S. Zitney`S. Hadfield, T. Davis`1994`chemical process simulation problem sequence`\naux.A{i}: ith matrix in sequence. aux.Zeros{i}: binary pattern of explicit\nzero entries provided in original data. aux.S = union of all patterns. \n | |
| 1536`Zitney`hydr1c`5308`5308`22592`yes`5308`1096`1`1160`0%`0%`real`unsymmetric`no`no`S. Zitney`S. Hadfield, T. Davis`1994`chemical process simulation problem sequence`\naux.A{i}: ith matrix in sequence. aux.Zeros{i}: binary pattern of explicit\nzero entries provided in original data. aux.S = union of all patterns. \n | |
| 1537`Schenk_IBMNA`c-18`2169`2169`15145`yes`2169`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1538`Schenk_IBMNA`c-19`2327`2327`21817`yes`2327`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1539`Schenk_IBMNA`c-20`2921`2921`20445`yes`2921`1`1`2240`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1540`Schenk_IBMNA`c-21`3509`3509`32145`yes`3509`7`7`12`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1541`Schenk_IBMNA`c-22`3792`3792`28870`yes`3792`2`2`2`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1542`Schenk_IBMNA`c-23`3969`3969`31079`yes`3969`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1543`Schenk_IBMNA`c-24`4119`4119`35699`yes`4119`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1544`Schenk_IBMNA`c-25`3797`3797`49635`yes`3797`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1545`Schenk_IBMNA`c-26`4307`4307`34537`yes`4307`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1546`Schenk_IBMNA`c-27`4563`4563`30927`yes`4563`1`1`448`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1547`Schenk_IBMNA`c-28`4598`4598`30590`yes`4598`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1548`Schenk_IBMNA`c-29`5033`5033`43731`yes`5033`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1549`Schenk_IBMNA`c-30`5321`5321`65693`yes`5321`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1550`Schenk_IBMNA`c-31`5339`5339`78571`yes`5339`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1551`Schenk_IBMNA`c-32`5975`5975`54471`yes`5975`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1552`Schenk_IBMNA`c-33`6317`6317`56123`yes`6317`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1553`Schenk_IBMNA`c-34`6611`6611`64333`yes`6611`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1554`Schenk_IBMNA`c-35`6537`6537`62891`yes`6537`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1555`Schenk_IBMNA`c-36`7479`7479`65941`yes`7479`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1556`Schenk_IBMNA`c-37`8204`8204`74676`yes`8204`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1557`Schenk_IBMNA`c-38`8127`8127`77689`yes`8127`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1558`Schenk_IBMNA`c-39`9271`9271`116587`yes`9271`1`1`20224`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1559`Schenk_IBMNA`c-40`9941`9941`81501`yes`9941`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1560`Schenk_IBMNA`c-41`9769`9769`101635`yes`9769`8`8`110`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1561`Schenk_IBMNA`c-42`10471`10471`110285`yes`10471`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1562`Schenk_IBMNA`c-43`11125`11125`123659`yes`11125`9`9`16`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1563`Schenk_IBMNA`c-44`10728`10728`85000`yes`10728`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1564`Schenk_IBMNA`c-45`13206`13206`174452`yes`13206`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1565`Schenk_IBMNA`c-46`14913`14913`130397`yes`14913`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1566`Schenk_IBMNA`c-47`15343`15343`211401`yes`15343`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1567`Schenk_IBMNA`c-48`18354`18354`166080`yes`18354`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1568`Schenk_IBMNA`c-49`21132`21132`157040`yes`21132`2`2`2`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1569`Schenk_IBMNA`c-50`22401`22401`180245`yes`22401`3`3`13380`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1570`Schenk_IBMNA`c-51`23196`23196`203048`yes`23196`2`2`2`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1571`Schenk_IBMNA`c-52`23948`23948`202708`yes`23948`5`5`8`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1572`Schenk_IBMNA`c-53`30235`30235`355139`yes`30235`42`42`17074`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1573`Schenk_IBMNA`c-54`31793`31793`385987`yes`31793`20`20`5706`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1574`Schenk_IBMNA`c-56`35910`35910`380240`yes`35910`5`5`660`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1575`Schenk_IBMNA`c-57`37833`37833`403373`yes`37833`49`49`1824`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1576`Schenk_IBMNA`c-60`43640`43640`298570`yes`43640`5`5`8`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1577`Schenk_IBMNA`c-61`43618`43618`310016`yes`43618`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1578`Schenk_IBMNA`c-65`48066`48066`360428`yes`48066`51`51`100`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1579`Schenk_IBMNA`c-big`345241`345241`2340859`yes`345241`77`77`152`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`optimization problem` | |
| 1580`Schenk_AFE`af_0_k101`503625`503625`17550675`yes`503625`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2006`structural problem` | |
| 1581`Schenk_AFE`af_1_k101`503625`503625`17550675`yes`503625`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2006`structural problem` | |
| 1582`Schenk_AFE`af_2_k101`503625`503625`17550675`yes`503625`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2006`structural problem` | |
| 1583`Schenk_AFE`af_3_k101`503625`503625`17550675`yes`503625`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2006`structural problem` | |
| 1584`Schenk_AFE`af_4_k101`503625`503625`17550675`yes`503625`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2006`structural problem` | |
| 1585`Schenk_AFE`af_5_k101`503625`503625`17550675`yes`503625`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`AutoForm Eng.`O. Schenk`2006`structural problem` | |
| 1586`Schenk_AFE`af_shell10`1508065`1508065`52259885`yes`1508065`1`1`412440`symmetric`symmetric`real`symmetric`yes`no`AutoForm Eng.`O. Schenk`2006`structural problem` | |
| 1587`Schenk_IBMNA`c-64b`51035`51035`707601`yes`51035`1`1`10240`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`subsequent optimization problem`\nnext: - first: Schenk_IBMNA/c-64 \nAn earlier version (Oct. 2003) of this matrix was obtained from Olaf \nSchenk, and appears here as Schenk_IBMNA/c-64. However, it differs \nfrom the version posted on his web site as of Nov. 2006. The new \nversion appears here as Schenk_IBMNA/c-64b. The two matrices are very\nsimilar, but not identical. \n | |
| 1588`Schenk_IBMNA`c-66b`49989`49989`444851`yes`49989`7`7`54156`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`subsequent optimization problem`\nnext: - first: Schenk_IBMNA/c-66 \nAn earlier version (Oct. 2003) of this matrix was obtained from Olaf \nSchenk, and appears here as Schenk_IBMNA/c-66. However, it differs \nfrom the version posted on his web site as of Nov. 2006. The new \nversion appears here as Schenk_IBMNA/c-66b. The two matrices are very\nsimilar, but not identical. \n | |
| 1589`Schenk_IBMNA`c-67b`57975`57975`530583`yes`57975`165`165`1352`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`subsequent optimization problem`\nnext: - first: Schenk_IBMNA/c-67 \nAn earlier version (Oct. 2003) of this matrix was obtained from Olaf \nSchenk, and appears here as Schenk_IBMNA/c-67. However, it differs \nfrom the version posted on his web site as of Nov. 2006. The new \nversion appears here as Schenk_IBMNA/c-67b. The two matrices are very\nsimilar, but not identical. \n | |
| 1590`Schenk_IBMNA`c-73b`169422`169422`1279274`yes`169422`1`1`0`symmetric`symmetric`real`symmetric`no`no`IBM`O. Schenk`2006`subsequent optimization problem`\nnext: - first: Schenk_IBMNA/c-73 \nAn earlier version (Oct. 2003) of this matrix was obtained from Olaf \nSchenk, and appears here as Schenk_IBMNA/c-73. However, it differs \nfrom the version posted on his web site as of Nov. 2006. The new \nversion appears here as Schenk_IBMNA/c-73b. The two matrices are very\nsimilar, but not identical. \n | |
| 1591`QCD`conf5_0-4x4-10`3072`3072`119808`yes`3072`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1592`QCD`conf5_0-4x4-14`3072`3072`119808`yes`3072`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1593`QCD`conf5_0-4x4-18`3072`3072`119808`yes`3072`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1594`QCD`conf5_0-4x4-22`3072`3072`119808`yes`3072`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1595`QCD`conf5_0-4x4-26`3072`3072`119808`yes`3072`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1596`QCD`conf6_0-4x4-20`3072`3072`119808`yes`3072`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1597`QCD`conf6_0-4x4-30`3072`3072`119808`yes`3072`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1598`QCD`conf5_4-8x8-05`49152`49152`1916928`yes`49152`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1599`QCD`conf5_4-8x8-10`49152`49152`1916928`yes`49152`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1600`QCD`conf5_4-8x8-15`49152`49152`1916928`yes`49152`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1601`QCD`conf5_4-8x8-20`49152`49152`1916928`yes`49152`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1602`QCD`conf6_0-8x8-20`49152`49152`1916928`yes`49152`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1603`QCD`conf6_0-8x8-30`49152`49152`1916928`yes`49152`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1604`QCD`conf6_0-8x8-80`49152`49152`1916928`yes`49152`2`1`0`92%`46%`complex`unsymmetric`no`no`B. Medeke`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1999`theoretical/quantum chemistry problem` | |
| 1605`Cylshell`s1rmq4m1`5489`5489`262411`yes`5489`1`1`18700`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s1rmq4m1.mtx \n%TITLE Cyl shell R/t = 10 unif 30x30 quad mesh stab MITC4 elem with drill rot \n%KEY s1rmq4m1 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%REFERENCE M. Benzi, R. Kouhia, M.Tuma: An assesment of some \n% preconditioning techniques in shell problems \n% Technical Report LA-UR-97-3892, Los Alamos National Laboratory \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 10 \n% Length to radius ratio R/L = 1 \n% One octant discretized with uniform 30 x 30 quadrilateral mesh \n% element: \n% facet-type shell element where the bending part is formulated \n% using the stabilized MITC theory (stabilization paramater 0.4) \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 2x2 Gauss-Legendre integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% and the FE mesh is uniform there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1606`Cylshell`s2rmq4m1`5489`5489`263351`yes`5489`1`1`17760`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s2rmq4m1.mtx \n%TITLE Cyl shell R/t = 100 unif 30x30 quad mesh stab MITC4 elem with drill rot \n%KEY s2rmq4m1 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%REFERENCE M. Benzi, R. Kouhia, M.Tuma: An assesment of some \n% preconditioning techniques in shell problems \n% Technical Report LA-UR-97-3892, Los Alamos National Laboratory \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 100 \n% Length to radius ratio R/L = 1 \n% One octant discretized with uniform 30 x 30 quadrilateral mesh \n% element: \n% facet-type shell element where the bending part is formulated \n% using the stabilized MITC theory (stabilization paramater 0.4) \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 2x2 Gauss-Legendre integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% and the FE mesh is uniform there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1607`Cylshell`s3rmq4m1`5489`5489`262943`yes`5489`1`1`18168`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s3rmq4m1.mtx \n%TITLE Cyl shell R/t=1000 unif 30x30 quad mesh stab MITC4 elem with drill rot \n%KEY s3rmq4m1 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%REFERENCE M. Benzi, R. Kouhia, M.Tuma: An assesment of some \n% preconditioning techniques in shell problems \n% Technical Report LA-UR-97-3892, Los Alamos National Laboratory \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 1000 \n% Length to radius ratio R/L = 1 \n% One octant discretized with uniform 30 x 30 quadrilateral mesh \n% element: \n% facet-type shell element where the bending part is formulated \n% using the stabilized MITC theory (stabilization paramater 0.4) \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 2x2 Gauss-Legendre integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% and the FE mesh is uniform there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1608`Cylshell`s1rmt3m1`5489`5489`217651`yes`5489`1`1`1870`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s1rmt3m1.mtx \n%TITLE Cyl shell R/t=10 unif 30x30 trian mesh stab MITC3 elem with drill rot \n%KEY s1rmt3m1 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 10 \n% Length to radius ratio R/L = 1 \n% One octant discretized with uniform 30 x 30 triangular mesh \n% element: \n% facet-type shell element where the bending part is formulated \n% using the stabilized MITC theory (stabilization paramater 0.4) \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 3-point integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% and the FE mesh is uniform there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1609`Cylshell`s2rmt3m1`5489`5489`217681`yes`5489`1`1`1840`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s2rmt3m1.mtx \n%TITLE Cyl shell R/t=100 unif 30x30 trian mesh stab MITC3 elem with drill rot \n%KEY s2rmt3m1 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 100 \n% Length to radius ratio R/L = 1 \n% One octant discretized with uniform 30 x 30 triangular mesh \n% element: \n% facet-type shell element where the bending part is formulated \n% using the stabilized MITC theory (stabilization paramater 0.4) \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 3-point integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% and the FE mesh is uniform there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1610`Cylshell`s3rmt3m1`5489`5489`217669`yes`5489`1`1`1852`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s3rmt3m1.mtx \n%TITLE Cyl shell R/t=1000 unif 30x30 trian mesh stab MITC3 elem with drill rot \n%KEY s3rmt3m1 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 1000 \n% Length to radius ratio R/L = 1 \n% One octant discretized with uniform 30 x 30 triangular mesh \n% element: \n% facet-type shell element where the bending part is formulated \n% using the stabilized MITC theory (stabilization paramater 0.4) \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 3-point integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% and the FE mesh is uniform there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1611`Cylshell`s3rmt3m3`5357`5357`207123`yes`5357`1`1`572`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`R. Boisvert, R. Pozo, K. Remington, B. Miller, R. Lipman, R. Barrett, J. Dongarra`1997`structural problem`\n% \n%FILE s3rmt3m3.mtx \n%TITLE Cyl shell R/t=1000 grad trian mesh 1666 stab MITC3 elem with drill rot \n%KEY s3rmt3m3 \n% \n% \n%CONTRIBUTOR Reijo Kouhia (reijo.kouhia@hut.fi) \n% \n%BEGIN DESCRIPTION \n% Matrix from a static analysis of a cylindrical shell \n% Radius to thickness ratio R/t = 1000 \n% Length to radius ratio R/L = 1 \n% One octant discretized with graded triangular mesh (1666 elements) \n% element: \n% facet-type shell element where the bending part is formulated \n% using the stabilized MITC theory (stabilization paramater 0.4) \n% the membrane part includes drilling rotations using \n% the Hughes-Brezzi formulation with (regularizing parameter = G/1000, \n% where G is the shear modulus) \n% full 3-point integration \n% -------------------------------------------------------------------------- \n% Note: \n% The sparsity pattern of the matrix is determined from the element \n% connectivity data assuming that the element matrix is full. \n% Since this case the material model is linear isotropically elastic \n% there exist some zeros. \n% Since the removal of those zero elements is trivial \n% but the reconstruction of the current sparsity \n% pattern is impossible from the sparsified structure without any further \n% knowledge of the element connectivity, the zeros are retained in this file. \n% --------------------------------------------------------------------------- \n%END DESCRIPTION \n% \n% \n | |
| 1612`Bai`cryg10000`10000`10000`49699`yes`10000`1`1`0`100%`0%`real`unsymmetric`no`no`C. Yang`Z. Bai, D. Day, J. Demmel, J. Dongarra`1996`materials problem` | |
| 1613`Bai`cryg2500`2500`2500`12349`yes`2500`1`1`0`99%`0%`real`unsymmetric`no`no`C. Yang`Z. Bai, D. Day, J. Demmel, J. Dongarra`1996`materials problem` | |
| 1614`Bai`dw2048`2048`2048`10114`yes`2048`1`1`0`98%`95%`real`unsymmetric`no`no`H. Dong`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`electromagnetics problem` | |
| 1615`Bai`dw8192`8192`8192`41746`yes`8192`1`1`0`96%`92%`real`unsymmetric`no`no`H. Dong`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`electromagnetics problem` | |
| 1616`Bai`dwa512`512`512`2480`yes`512`1`1`0`98%`91%`real`unsymmetric`no`no`H. Dong`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`electromagnetics problem` | |
| 1617`Bai`dwb512`512`512`2500`yes`512`1`1`0`97%`88%`real`unsymmetric`no`no`H. Dong`Z. Bai, D. Day, J. Demmel, J. Dongarra`1993`electromagnetics problem` | |
| 1618`Bai`dwg961a`961`961`3405`no`705`3`257`0`symmetric`36%`complex`symmetric`no`no`S. Gedney and U. Navasariwala`Z. Bai, D. Day, J. Demmel, J. Dongarra`1996`electromagnetics problem` | |
| 1619`Bai`dwg961b`961`961`10591`yes`961`1`1`0`symmetric`35%`complex`symmetric`no`no`S. Gedney and U. Navasariwala`Z. Bai, D. Day, J. Demmel, J. Dongarra`1996`electromagnetics problem` | |
| 1620`Bai`mhd1280a`1280`1280`47906`yes`1280`15`15`0`90%`31%`complex`unsymmetric`no`no`A. Booten, M. Kooper, H. van der Vorst, S. Poedts, J. Goedbloed`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 1621`Bai`mhd1280b`1280`1280`22778`yes`1280`20`20`0`symmetric`symmetric`complex`Hermitian`yes`yes`A. Booten, M. Kooper, H. van der Vorst, S. Poedts, J. Goedbloed`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 1622`Bai`mhd3200a`3200`3200`68026`yes`3200`8`8`0`77%`27%`real`unsymmetric`no`no`A. Booten, M. Kooper, H. van der Vorst, S. Poedts, J. Goedbloed`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 1623`Bai`mhd3200b`3200`3200`18316`yes`3200`14`14`0`symmetric`symmetric`real`symmetric`yes`yes`A. Booten, M. Kooper, H. van der Vorst, S. Poedts, J. Goedbloed`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 1624`Bai`mhd4800a`4800`4800`102252`yes`4800`8`8`0`77%`27%`real`unsymmetric`no`no`A. Booten, M. Kooper, H. van der Vorst, S. Poedts, J. Goedbloed`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 1625`Bai`mhd4800b`4800`4800`27520`yes`4800`14`14`0`symmetric`symmetric`real`symmetric`yes`yes`A. Booten, M. Kooper, H. van der Vorst, S. Poedts, J. Goedbloed`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`electromagnetics problem` | |
| 1626`Bai`qh1484`1484`1484`6110`yes`1484`3`3`0`symmetric`5%`real`unsymmetric`no`no`D. Ndereyimana`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`power network problem` | |
| 1627`Bai`qh768`768`768`2934`yes`768`43`1`0`93%`0%`real`unsymmetric`no`no`D. Ndereyimana`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`power network problem` | |
| 1628`Bai`rdb1250`1250`1250`7300`yes`1250`1`1`0`symmetric`79%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 1629`Bai`rdb1250l`1250`1250`7300`yes`1250`1`1`0`symmetric`79%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 1630`Bai`rdb200`200`200`1120`yes`200`1`1`0`symmetric`78%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 1631`Bai`rdb200l`200`200`1120`yes`200`1`1`0`symmetric`78%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 1632`Bai`rdb2048_noL`2048`2048`12032`yes`2048`1`1`0`symmetric`79%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem`\nThis matrix (Bai/rdb2048_noL) is the NEP RDB2048 matrix. It \ndiffers from the Bai/rdb2048 matrix. The Bai/rdb2048 and NEP \nRDB2048L matrices are identical. See the notes in Bai/rdb2048 for\nmore details. \n | |
| 1633`Bai`rdb3200l`3200`3200`18880`yes`3200`1`1`0`symmetric`80%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 1634`Bai`rdb450`450`450`2580`yes`450`1`1`0`symmetric`79%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 1635`Bai`rdb450l`450`450`2580`yes`450`1`1`0`symmetric`79%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 1636`Bai`rdb800l`800`800`4640`yes`800`1`1`0`symmetric`79%`real`unsymmetric`no`no`K. Meerbergen`Z. Bai, D. Day, J. Demmel, J. Dongarra`1994`computational fluid dynamics problem` | |
| 1637`Bai`tols1090`1090`1090`3546`yes`1090`1073`801`0`32%`0%`real`unsymmetric`no`no`S. Godet-Thobie`Z. Bai, D. Day, J. Demmel, J. Dongarra`1991`computational fluid dynamics problem` | |
| 1638`Bai`tols2000`2000`2000`5184`yes`2000`1983`1529`0`34%`0%`real`unsymmetric`no`no`S. Godet-Thobie`Z. Bai, D. Day, J. Demmel, J. Dongarra`1991`computational fluid dynamics problem` | |
| 1639`Bai`tols340`340`340`2196`yes`340`323`201`0`29%`0%`real`unsymmetric`no`no`S. Godet-Thobie`Z. Bai, D. Day, J. Demmel, J. Dongarra`1991`computational fluid dynamics problem` | |
| 1640`Bai`tols4000`4000`4000`8784`yes`4000`3983`3129`0`36%`0%`real`unsymmetric`no`no`S. Godet-Thobie`Z. Bai, D. Day, J. Demmel, J. Dongarra`1991`computational fluid dynamics problem` | |
| 1641`Bai`tols90`90`90`1746`yes`90`73`1`0`27%`0%`real`unsymmetric`no`no`S. Godet-Thobie`Z. Bai, D. Day, J. Demmel, J. Dongarra`1991`computational fluid dynamics problem` | |
| 1642`POLYFLOW`invextr1_new`30412`30412`1793881`yes`30412`1`1`0`97%`72%`real`unsymmetric`no`no`J. Marchal`J. Koster`2005`computational fluid dynamics problem`\nfrom Parasol, http://www.parallab.uib.no/projects/parasol/data\n | |
| 1643`POLYFLOW`mixtank_new`29957`29957`1990919`yes`29957`1`1`4122`symmetric`99%`real`unsymmetric`no`no`J. Marchal`J. Koster`2005`computational fluid dynamics problem`\nfrom Parasol, http://www.parallab.uib.no/projects/parasol/data\n | |
| 1644`INPRO`msdoor`415863`415863`19173163`yes`415863`11079`11079`1067772`symmetric`symmetric`real`symmetric`yes`yes`J. Weiher`J. Koster`2005`structural problem`\nfrom Parasol, http://www.parallab.uib.no/projects/parasol/data\n | |
| 1645`Mittelmann`nug08-3rd`19728`29856`148416`yes`19728`1`1`0`0%`0%`integer`rectangular`no`no`S. Karisch, F. Rendl`H. Mittelmann`1995`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nNUG: computing LP lower bounds for quadratic assignment problems. see\nS.E. KARISCH and F. RENDL. Lower bounds for the quadratic assignment \nproblem via triangle decompositions. Mathematical Programming, \n71(2):137-152, 1995. \nK.G. Ramakrishnan, M.G.C. Resende, B. Ramachandran, and J.F. Pekny, \n\"Tight QAP bounds via linear programming,\" Combinatorial and Global \nOptimization, P.M. Pardalos, A. Migdalas, and R.E. Burkard, eds., \nWorld Scientific Publishing Co., Singapore, pp. 297-303, 2002. \n | |
| 1646`Mittelmann`pds-30`49944`158489`340635`no`49788`967`157`0`0%`0%`integer`rectangular`no`no`W. Carolan, J. Hill, J. Kennington, S. Niemi, S. Wichmann`H. Mittelmann`1990`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nPDS: Patient distribution (evacuation) system. see \nW. Carolan, J. Hill, J. Kennington, S. Niemi, and S. Wichmann, \"An \nEmpirical Evaluation of the KORBX Algorithms for Military Airlift,\"\nApplications, Operations Research, 38, (1990), 240-248. \n | |
| 1647`Mittelmann`pds-40`66844`217531`466800`no`66641`1302`204`0`0%`0%`integer`rectangular`no`no`W. Carolan, J. Hill, J. Kennington, S. Niemi, S. Wichmann`H. Mittelmann`1990`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nPDS: Patient distribution (evacuation) system. see \nW. Carolan, J. Hill, J. Kennington, S. Niemi, and S. Wichmann, \"An \nEmpirical Evaluation of the KORBX Algorithms for Military Airlift,\"\nApplications, Operations Research, 38, (1990), 240-248. \n | |
| 1648`Mittelmann`pds-50`83060`275814`590833`no`82837`1405`224`0`0%`0%`integer`rectangular`no`no`W. Carolan, J. Hill, J. Kennington, S. Niemi, S. Wichmann`H. Mittelmann`1990`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nPDS: Patient distribution (evacuation) system. see \nW. Carolan, J. Hill, J. Kennington, S. Niemi, and S. Wichmann, \"An \nEmpirical Evaluation of the KORBX Algorithms for Military Airlift,\"\nApplications, Operations Research, 38, (1990), 240-248. \n | |
| 1649`Mittelmann`pds-60`99431`336421`719557`no`99204`1507`228`0`0%`0%`integer`rectangular`no`no`W. Carolan, J. Hill, J. Kennington, S. Niemi, S. Wichmann`H. Mittelmann`1990`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nPDS: Patient distribution (evacuation) system. see \nW. Carolan, J. Hill, J. Kennington, S. Niemi, and S. Wichmann, \"An \nEmpirical Evaluation of the KORBX Algorithms for Military Airlift,\"\nApplications, Operations Research, 38, (1990), 240-248. \n | |
| 1650`Mittelmann`pds-70`114944`390005`833465`no`114717`1533`228`0`0%`0%`integer`rectangular`no`no`W. Carolan, J. Hill, J. Kennington, S. Niemi, S. Wichmann`H. Mittelmann`1990`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nPDS: Patient distribution (evacuation) system. see \nW. Carolan, J. Hill, J. Kennington, S. Niemi, and S. Wichmann, \"An \nEmpirical Evaluation of the KORBX Algorithms for Military Airlift,\"\nApplications, Operations Research, 38, (1990), 240-248. \n | |
| 1651`Mittelmann`pds-80`129181`434580`927826`no`128954`1546`228`0`0%`0%`integer`rectangular`no`no`W. Carolan, J. Hill, J. Kennington, S. Niemi, S. Wichmann`H. Mittelmann`1990`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nPDS: Patient distribution (evacuation) system. see \nW. Carolan, J. Hill, J. Kennington, S. Niemi, and S. Wichmann, \"An \nEmpirical Evaluation of the KORBX Algorithms for Military Airlift,\"\nApplications, Operations Research, 38, (1990), 240-248. \n | |
| 1652`Mittelmann`pds-90`142823`475448`1014136`no`142596`1546`228`0`0%`0%`integer`rectangular`no`no`W. Carolan, J. Hill, J. Kennington, S. Niemi, S. Wichmann`H. Mittelmann`1990`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nPDS: Patient distribution (evacuation) system. see \nW. Carolan, J. Hill, J. Kennington, S. Niemi, and S. Wichmann, \"An \nEmpirical Evaluation of the KORBX Algorithms for Military Airlift,\"\nApplications, Operations Research, 38, (1990), 240-248. \n | |
| 1653`Mittelmann`pds-100`156243`514577`1096002`no`156016`1618`300`0`0%`0%`integer`rectangular`no`no`W. Carolan, J. Hill, J. Kennington, S. Niemi, S. Wichmann`H. Mittelmann`1990`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset \nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nPDS: Patient distribution (evacuation) system. see \nW. Carolan, J. Hill, J. Kennington, S. Niemi, and S. Wichmann, \"An \nEmpirical Evaluation of the KORBX Algorithms for Military Airlift,\"\nApplications, Operations Research, 38, (1990), 240-248. \n | |
| 1654`Mittelmann`rail507`507`63516`409856`yes`507`1`1`0`0%`0%`integer`rectangular`no`no`P. Nobili`J. Beasley`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nRAIL: set covering problems from the Italian railroad, see \nhttp://people.brunel.ac.uk/~mastjjb/jeb/orlib/scpinfo.html \n | |
| 1655`Mittelmann`rail516`516`47827`315412`yes`516`1`14`0`0%`0%`integer`rectangular`no`no`P. Nobili`J. Beasley`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nRAIL: set covering problems from the Italian railroad, see \nhttp://people.brunel.ac.uk/~mastjjb/jeb/orlib/scpinfo.html \n | |
| 1656`Mittelmann`rail582`582`56097`402290`yes`582`1`1`0`0%`0%`integer`rectangular`no`no`P. Nobili`J. Beasley`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nRAIL: set covering problems from the Italian railroad, see \nhttp://people.brunel.ac.uk/~mastjjb/jeb/orlib/scpinfo.html \n | |
| 1657`Mittelmann`rail2586`2586`923269`8011362`yes`2586`1`8`0`0%`0%`integer`rectangular`no`no`P. Nobili`J. Beasley`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nRAIL: set covering problems from the Italian railroad, see \nhttp://people.brunel.ac.uk/~mastjjb/jeb/orlib/scpinfo.html \n | |
| 1658`Mittelmann`rail4284`4284`1096894`11284032`yes`4284`1`5`0`0%`0%`integer`rectangular`no`no`P. Nobili`J. Beasley`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n \nRAIL: set covering problems from the Italian railroad, see \nhttp://people.brunel.ac.uk/~mastjjb/jeb/orlib/scpinfo.html \n | |
| 1659`Mittelmann`sgpf5y6`246077`312540`831976`yes`246077`1`1`0`0%`0%`integer`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1660`Mittelmann`stormG2_1000`528185`1377306`3459881`no`526185`3002`5001`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1661`Mittelmann`watson_1`201155`386992`1055093`yes`201155`15326`1`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1662`Mittelmann`watson_2`352013`677224`1846391`yes`352013`26816`1`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1663`Mittelmann`cont11_l`1468599`1961394`5382999`yes`1468599`1`1`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1664`Mittelmann`cont1_l`1918399`1921596`7031999`yes`1918399`1`1`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1665`Mittelmann`fome11`12142`24460`71264`yes`12142`1`2`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1666`Mittelmann`fome12`24284`48920`142528`yes`24284`1`4`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1667`Mittelmann`fome13`48568`97840`285056`yes`48568`1`8`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1668`Mittelmann`fome20`33874`108175`232647`no`33798`853`77`0`0%`0%`integer`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1669`Mittelmann`fome21`67748`216350`465294`no`67596`1704`154`0`0%`0%`integer`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1670`Mittelmann`neos`479119`515905`1526794`yes`479119`1`1`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1671`Mittelmann`neos1`131581`133473`599590`yes`131581`1`1`0`0%`0%`integer`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1672`Mittelmann`neos2`132568`134128`685087`yes`132568`1`1`0`0%`0%`integer`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1673`Mittelmann`neos3`512209`518832`2055024`yes`512209`1`1`0`0%`0%`integer`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1674`Mittelmann`spal_004`10203`321696`46168124`yes`10203`1`1`0`0%`0%`real`rectangular`no`no`unknown`H. Mittelmann`2005`linear programming problem`\nHans Mittelmann test set, http://plato.asu.edu/ftp/lptestset\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1675`Meszaros`gams10am`114`171`407`yes`114`2`4`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1676`Meszaros`gams30am`354`531`1287`yes`354`2`4`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1677`Meszaros`gams60am`714`1071`2607`yes`714`2`4`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1678`Meszaros`gas11`459`862`2166`yes`459`8`11`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1679`Meszaros`aa01`823`8904`72965`yes`823`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1680`Meszaros`aa03`825`8627`70806`no`822`6`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1681`Meszaros`aa3`825`8627`70806`no`822`6`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1682`Meszaros`aa4`426`7195`52121`yes`426`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1683`Meszaros`aa5`801`8308`65953`no`800`2`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1684`Meszaros`aa6`646`7292`51728`yes`646`2`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1685`Meszaros`air02`50`6774`61555`yes`50`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1686`Meszaros`air03`124`10757`91028`yes`124`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1687`Meszaros`air04`823`8904`72965`yes`823`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1688`Meszaros`air05`426`7195`52121`yes`426`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1689`Meszaros`air06`825`8627`70806`no`822`6`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1690`Meszaros`aircraft`3754`7517`20267`yes`3754`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1691`Meszaros`bas1lp`5411`9825`587775`yes`5411`1`2`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1692`Meszaros`baxter`27441`30733`111576`no`24386`74`43`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1693`Meszaros`car4`16384`33052`63724`yes`16384`1`15685`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1694`Meszaros`cari`400`1200`152800`yes`400`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1695`Meszaros`ch`3700`8291`24102`yes`3700`19`19`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1696`Meszaros`co5`5774`12325`57993`yes`5774`60`75`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1697`Meszaros`co9`10789`22924`109651`yes`10789`96`123`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1698`Meszaros`complex`1023`1408`46463`yes`1023`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1699`Meszaros`cq5`5048`11748`51571`yes`5048`24`25`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1700`Meszaros`cq9`9278`21534`96653`yes`9278`32`33`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1701`Meszaros`cr42`905`1513`6614`yes`905`2`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1702`Meszaros`crew1`135`6469`46950`yes`135`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1703`Meszaros`dano3mip`3202`15851`81633`yes`3202`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1704`Meszaros`dbic1`43200`226317`1081843`yes`43200`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1705`Meszaros`dbir1`18804`45775`1077025`no`18802`2`2339`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1706`Meszaros`dbir2`18906`45877`1158159`no`18904`29`2366`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1707`Meszaros`df2177`630`10358`22336`yes`630`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1708`Meszaros`e18`24617`38602`156466`yes`24617`1`2`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2006`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1709`Meszaros`ex3sta1`17443`17516`68779`yes`17443`2`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1710`Meszaros`farm`7`17`41`yes`7`2`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1711`Meszaros`gams10a`114`171`407`yes`114`2`4`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1712`Meszaros`gams30a`354`531`1287`yes`354`2`4`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1713`Meszaros`ge`10099`16369`44825`yes`10099`482`3`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1714`Meszaros`iiasa`669`3639`7317`yes`669`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1715`Meszaros`jendrec1`2109`4228`89608`yes`2109`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1716`Meszaros`kl02`71`36699`212536`yes`71`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1717`Meszaros`l9`244`1483`4659`yes`244`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1718`Meszaros`lp22`2958`16392`68518`yes`2958`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1719`Meszaros`lpl2`3294`10881`32232`yes`3294`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1720`Meszaros`lpl3`10828`33686`100525`yes`10828`174`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1721`Meszaros`mod2`34774`66409`199810`yes`34774`420`420`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1722`Meszaros`model1`362`798`3028`yes`362`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1723`Meszaros`model2`379`1321`7607`yes`379`13`2`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1724`Meszaros`model3`1609`4578`23974`yes`1609`8`18`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1725`Meszaros`model4`1337`4962`45753`yes`1337`1`2`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1726`Meszaros`model5`1888`11802`89925`no`1744`10`145`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1727`Meszaros`model6`2096`5289`27628`no`2094`32`10`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1728`Meszaros`model7`3358`9582`51027`yes`3358`14`28`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1729`Meszaros`model8`2896`6464`25277`yes`2896`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1730`Meszaros`model9`2879`10939`55956`no`2787`43`190`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1731`Meszaros`model10`4400`16819`150372`yes`4400`5`2`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1732`Meszaros`nemsafm`334`2348`2826`yes`334`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1733`Meszaros`nemscem`651`1712`3840`yes`651`173`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1734`Meszaros`nemsemm1`3945`75352`1053986`yes`3945`59`134`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1735`Meszaros`nemsemm2`6943`48878`182012`yes`6943`22`35`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1736`Meszaros`nemspmm1`2372`8903`55867`no`2362`35`32`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1737`Meszaros`nemspmm2`2301`8734`68225`yes`2301`60`23`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1738`Meszaros`nemswrld`7138`28550`192283`no`6647`137`586`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1739`Meszaros`nl`7039`15325`47035`yes`7039`13`10`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1740`Meszaros`nw14`73`123409`904910`yes`73`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1741`Meszaros`p0033`15`48`113`yes`15`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1742`Meszaros`p0040`23`63`133`yes`23`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1743`Meszaros`p010`10090`19090`118000`yes`10090`20`10`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1744`Meszaros`p0201`133`334`2056`yes`133`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1745`Meszaros`p0282`241`523`2207`yes`241`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1746`Meszaros`p0291`252`543`2283`yes`252`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1747`Meszaros`p0548`176`724`1887`yes`176`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1748`Meszaros`p05`5090`9590`59045`yes`5090`15`10`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1749`Meszaros`p2756`755`3511`9692`yes`755`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1750`Meszaros`p6000`2095`7967`19826`yes`2095`3`23`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1751`Meszaros`pcb1000`1565`2820`20463`yes`1565`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1752`Meszaros`pcb3000`3960`7732`57479`yes`3960`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1753`Meszaros`pf2177`9728`10178`30984`yes`9728`1`271`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1754`Meszaros`primagaz`1554`10836`21665`yes`1554`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1755`Meszaros`problem`12`46`86`yes`12`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1756`Meszaros`progas`1650`1900`8897`yes`1650`15`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1757`Meszaros`qiulp`1192`1900`4492`yes`1192`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1758`Meszaros`r05`5190`9690`104145`yes`5190`25`20`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1759`Meszaros`refine`29`62`153`yes`29`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1760`Meszaros`rlfddd`4050`61521`264627`yes`4050`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1761`Meszaros`rlfdual`8052`74970`282031`yes`8052`1`5`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1762`Meszaros`rlfprim`58866`62716`320591`yes`58866`1`5`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1763`Meszaros`rosen1`520`1544`23794`yes`520`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1764`Meszaros`rosen2`1032`3080`47536`yes`1032`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1765`Meszaros`rosen7`264`776`8034`yes`264`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1766`Meszaros`rosen8`520`1544`16058`yes`520`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1767`Meszaros`rosen10`2056`6152`64192`yes`2056`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1768`Meszaros`route`20894`43019`206782`yes`20894`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1769`Meszaros`seymourl`4944`6316`38493`yes`4944`1`138`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1770`Meszaros`slptsk`2861`3347`72465`yes`2861`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1771`Meszaros`south31`18425`36321`112398`yes`18425`437`437`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1772`Meszaros`stat96v1`5995`197472`588798`yes`5995`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2005`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1773`Meszaros`stat96v2`29089`957432`2852184`yes`29089`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2005`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1774`Meszaros`stat96v3`33841`1113780`3317736`yes`33841`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2005`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1775`Meszaros`stat96v4`3173`63076`491336`yes`3173`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2005`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1776`Meszaros`stat96v5`2307`75779`233921`no`2305`3`3`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2005`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1777`Meszaros`t0331-4l`664`46915`430982`yes`664`1`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1778`Meszaros`testbig`17613`31223`61639`yes`17613`2`2`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1779`Meszaros`ulevimin`6590`46937`164538`yes`6590`197`184`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1780`Meszaros`us04`163`28016`297538`no`162`2`1`0`0%`0%`binary`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1781`Meszaros`world`34506`67147`198883`yes`34506`401`401`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1782`Meszaros`zed`116`142`666`yes`116`5`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1783`Meszaros`de063155`852`1848`4913`yes`852`1`253`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1784`Meszaros`de063157`936`1908`5119`yes`936`1`253`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1785`Meszaros`de080285`936`1908`5082`yes`936`1`253`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1786`Meszaros`gen1`769`2561`63086`yes`769`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1787`Meszaros`gen2`1121`3264`81855`yes`1121`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1788`Meszaros`gen4`1537`4298`107103`yes`1537`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1789`Meszaros`gen`769`2561`63086`yes`769`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1790`Meszaros`iprob`3001`3001`9000`yes`3001`1`1`0`symmetric`50%`real`unsymmetric`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1791`Meszaros`l30`2701`16281`52070`yes`2701`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1792`Meszaros`stoch_aircraft`3754`7517`20267`yes`3754`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1793`Meszaros`cep1`1521`4769`8233`yes`1521`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1794`Meszaros`deter0`1923`5468`11173`yes`1923`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1795`Meszaros`deter1`5527`15737`32187`yes`5527`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1796`Meszaros`deter2`6095`17313`35731`yes`6095`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1797`Meszaros`deter3`7647`21777`44547`yes`7647`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1798`Meszaros`deter4`3235`9133`19231`yes`3235`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1799`Meszaros`deter5`5103`14529`29715`yes`5103`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1800`Meszaros`deter6`4255`12113`24771`yes`4255`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1801`Meszaros`deter7`6375`18153`37131`yes`6375`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1802`Meszaros`deter8`3831`10905`22299`yes`3831`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1803`Meszaros`fxm2-6`1520`2845`12812`yes`1520`39`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1804`Meszaros`fxm2-16`3900`7335`32972`yes`3900`99`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1805`Meszaros`fxm3_6`6200`12625`57722`yes`6200`159`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1806`Meszaros`fxm3_16`41340`85575`392252`yes`41340`1059`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1807`Meszaros`fxm4_6`22400`47185`265442`yes`22400`159`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1808`Meszaros`pgp2`4034`13254`22474`yes`4034`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1809`Meszaros`stormg2-125`66185`172431`433256`no`65935`377`626`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1810`Meszaros`stormg2-27`14441`37485`94274`no`14387`83`136`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1811`Meszaros`stormg2-8`4409`11322`28553`no`4393`26`41`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1812`Meszaros`degme`185501`659415`8127528`yes`185501`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2006`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1813`Meszaros`karted`46502`133115`1770349`yes`46502`2`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2006`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1814`Meszaros`tp-6`142752`1014301`11537419`yes`142752`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2006`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1815`Meszaros`ts-palko`22002`47235`1076903`yes`22002`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2006`linear programming problem`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1816`Meszaros`delf`3170`6654`15397`yes`3170`1`1058`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1817`Meszaros`kleemin`8`16`44`yes`8`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1818`Meszaros`large`4282`8617`20635`yes`4282`1`1322`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1819`Meszaros`nsct`23003`37563`697738`no`23002`22`3698`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1820`Meszaros`nsic`465`897`3449`yes`465`7`7`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1821`Meszaros`nsir`4453`10057`154939`yes`4453`4`4`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1822`Meszaros`plddb`3069`5049`10839`yes`3069`199`397`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1823`Meszaros`rat`3136`9408`268908`yes`3136`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1824`Meszaros`small`677`1400`3207`yes`677`11`222`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \n | |
| 1825`Meszaros`pltexpa`26894`70364`143059`yes`26894`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1826`Meszaros`sc205-2r`35213`62423`123239`yes`35213`2`2`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1827`Meszaros`scagr7-2b`9743`13847`35885`yes`9743`2`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1828`Meszaros`scagr7-2c`2447`3479`9005`yes`2447`2`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1829`Meszaros`scagr7-2r`32847`46679`120141`yes`32847`2`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1830`Meszaros`scfxm1-2b`19036`33047`111052`yes`19036`771`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1831`Meszaros`scfxm1-2r`37980`65943`221388`yes`37980`1539`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1832`Meszaros`scrs8-2b`1820`3499`7367`yes`1820`262`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1833`Meszaros`scrs8-2c`1820`3499`7367`yes`1820`262`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1834`Meszaros`scrs8-2r`14364`27691`58439`yes`14364`2054`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1835`Meszaros`scsd8-2b`5130`35910`112770`yes`5130`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1836`Meszaros`scsd8-2c`5130`35910`112770`yes`5130`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1837`Meszaros`scsd8-2r`8650`60550`190210`yes`8650`1`1`0`0%`0%`real`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1838`Meszaros`sctap1-2b`15390`33858`99454`yes`15390`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1839`Meszaros`sctap1-2c`3390`7458`21854`yes`3390`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1840`Meszaros`sctap1-2r`28830`63426`186366`yes`28830`1`1`0`0%`0%`integer`rectangular`no`no`unknown`C. Meszaros`2004`linear programming problem sequence`\nhttp://www.sztaki.hu/~meszaros/public_ftp/lptestset \nConverted to standard form via Resende and Veiga's mpsrd:\nminimize c'*x, subject to A*x=b and lo <= x <= hi \nDeterminisitic equivalent of stochastic LP \n | |
| 1841`Gleich`wb-cs-stanford`9914`9914`36854`unknown`unknown`unknown`4391`0`46%`46%`binary`unsymmetric`no`no`D. Gleich`T. Davis`2001`directed graph`\nFor nodenames, see http://www.cise.ufl.edu/research/sparse/aux/Gleich\nThis graph is a subset of Gleich/wb-edu, with *.cs.stanford.edu only.\n | |
| 1842`Gleich`wb-edu`9845725`9845725`57156537`unknown`unknown`unknown`4269022`0`33%`33%`binary`unsymmetric`no`no`D. Gleich`T. Davis`2001`directed graph`\nFor nodenames, see http://www.cise.ufl.edu/research/sparse/aux/Gleich\nThis graph is a subset of the webbase-2001 graph in the collection: \nhttp://law.dsi.unimi.it/index.php?option=com_include&Itemid=65 \nThis was a web crawl performed at Stanford in 2001. \n | |
| 1843`Gleich`wikipedia-20051105`1634989`1634989`19753078`unknown`unknown`unknown`528698`0`12%`12%`binary`unsymmetric`no`no`D. Gleich`T. Davis`2005`directed graph`\nFor nodenames, see http://www.cise.ufl.edu/research/sparse/aux/Gleich\nPages outside the \"Main\", \"Category\" and \"Portal\" namespace excluded.\n | |
| 1844`Gleich`wikipedia-20060925`2983494`2983494`37269096`unknown`unknown`unknown`975731`0`12%`12%`binary`unsymmetric`no`no`D. Gleich`T. Davis`2006`directed graph`\nFor nodenames, see http://www.cise.ufl.edu/research/sparse/aux/Gleich\nPages outside the \"Main\", \"Category\" and \"Portal\" namespace excluded.\n | |
| 1845`Gleich`wikipedia-20061104`3148440`3148440`39383235`unknown`unknown`unknown`1040035`0`12%`12%`binary`unsymmetric`no`no`D. Gleich`T. Davis`2006`directed graph`\nFor nodenames, see http://www.cise.ufl.edu/research/sparse/aux/Gleich\nPages outside the \"Main\", \"Category\" and \"Portal\" namespace excluded.\n | |
| 1846`Gleich`wikipedia-20070206`3566907`3566907`45030389`unknown`unknown`unknown`1203340`0`12%`12%`binary`unsymmetric`no`no`D. Gleich`T. Davis`2007`directed graph`\nFor nodenames, see http://www.cise.ufl.edu/research/sparse/aux/Gleich\nPages outside the \"Main\", \"Category\" and \"Portal\" namespace excluded.\n | |
| 1847`UTEP`Dubcova1`16129`16129`253009`yes`16129`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`L. Dubcova, J. Cerveny, and P. Solin`T. Davis`2007`2D/3D problem` | |
| 1848`UTEP`Dubcova2`65025`65025`1030225`yes`65025`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`L. Dubcova, J. Cerveny, and P. Solin`T. Davis`2007`2D/3D problem` | |
| 1849`UTEP`Dubcova3`146689`146689`3636643`yes`146689`1`1`6`symmetric`symmetric`real`symmetric`yes`yes`L. Dubcova, J. Cerveny, and P. Solin`T. Davis`2007`2D/3D problem` | |
| 1850`BenElechi`BenElechi1`245874`245874`13150496`yes`245874`7`7`0`symmetric`symmetric`real`symmetric`yes`yes`S. Ben Elechi`T. Davis`2007`2D/3D problem` | |
| 1851`Botonakis`FEM_3D_thermal1`17880`17880`430740`yes`17880`1`1`0`symmetric`95%`real`unsymmetric`no`no`I. Botonakis`T. Davis`2007`thermal problem`\nThis is a very small test problem.\n | |
| 1852`Botonakis`FEM_3D_thermal2`147900`147900`3489300`yes`147900`1`1`0`symmetric`95%`real`unsymmetric`no`no`I. Botonakis`T. Davis`2007`thermal problem`\nThis is the smallest problem whose results are useful.\n | |
| 1853`Wissgott`parabolic_fem`525825`525825`3674625`yes`525825`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`P. Wissgott`T. Davis`2007`computational fluid dynamics problem` | |
| 1854`Watson`chem_master1`40401`40401`201201`yes`40401`1`1`0`symmetric`0%`real`unsymmetric`no`no`L. Watson and J. Zhang`T. Davis`2007`2D/3D problem`\nThe ODE system \frac{dp}{dt}=Qp is what we call a chemical master equation (a \nKolmogorov's backward/forward equation). Q is a sparse asymmetric matrix, \nwhose off-diagonal entries are non-negative and row sum to zero. On each row, \nq_{ij}h gives the probability the system makes a transition from current state\ni to some other state j, in small time interval h. By \"state\", we mean a \npossible combination of number of molecules in each chemical species. Now, h \nis small enough so that only one reaction happens. In this way q_{ij} is \nnonzero only if there exists a chemical reaction that connects state i and j, \ni.e. j=i+s_k, s_k's are constant state vectors that correspond to every \nreaction. Say we have M reactions, then there are at most M+1 nonzero \nentries on each row of Q. On the other hand, the number of possible \ncombination of molecules is huge, which means the dimension of Q is huge. \nThe linear system we want to solve is (I - Q/lambda)x=b, and we have \nto solve it several times. (Here lambda is a constant). Problem.A is the Q \nmatrix. This is a small test problem; the largest has dimension 10^8. \nIt has the nonzero pattern of a 201-by-201 mesh, minus 300 entries on the \n+1 and -1 diagonal. \n | |
| 1855`Watson`Baumann`112211`112211`748331`yes`112211`2`2`12300`symmetric`0%`real`unsymmetric`no`no`L. Watson and J. Zhang`T. Davis`2007`2D/3D problem`\nThe ODE system \frac{dp}{dt}=Qp is what we call a chemical master equation (a \nKolmogorov's backward/forward equation). Q is a sparse asymmetric matrix, \nwhose off-diagonal entries are non-negative and row sum to zero. On each row, \nq_{ij}h gives the probability the system makes a transition from current state\ni to some other state j, in small time interval h. By \"state\", we mean a \npossible combination of number of molecules in each chemical species. Now, h \nis small enough so that only one reaction happens. In this way q_{ij} is \nnonzero only if there exists a chemical reaction that connects state i and j, \ni.e. j=i+s_k, s_k's are constant state vectors that correspond to every \nreaction. Say we have M reactions, then there are at most M+1 nonzero \nentries on each row of Q. On the other hand, the number of possible \ncombination of molecules is huge, which means the dimension of Q is huge. \nThe linear system we want to solve is (I - Q/lambda)x=b, and we have \nto solve it several times. (Here lambda is a constant). Problem.A is the Q \nmatrix. This is a medium test problem; the largest has dimension 10^8. \nIt has the nonzero pattern of a 11-by-101-by-101 mesh. \n | |
| 1856`Sinclair`3Dspectralwave`680943`680943`30290827`yes`680943`1`1`3359762`symmetric`symmetric`complex`Hermitian`yes`no`C. Sinclair`T. Davis`2007`materials problem`\nThe A matrix is produced using 3-D spectral-element elastic wave modelling in\nthe frequency domain. The medium is homogeneous and isotropic with elastic \ncoefficients: c11 = 6.30, c44 = 1.00 The B matrix represents a real \ny-directed source, placed approximately in the centre. The model size in \nelements is 20x20x20. Each element is 1m x1m x 1m. Each element is a 4x4x4 \nGauss-Lobbato-Legendre mesh, so the height, width and depth of the system is \n61 nodes. There are 3 unknown components at each node - the x, y and z \ndisplacements. The A matrix therefore has dimension 680943 x 680943, where \n((20 x 4) - (20 - 1))^3 * 3 = 680943. The problem domain is earth sciences. \nNote that A is complex and b is sparse and real (b has a single nonzero). \n \nThe A matrix was provided with a nonzero imaginary part, but was otherwise \ncomplex Hermitian. To save space in the Matrix Market and Rutherford/Boeing \nformats, the A matrix here has had this imaginary diagonal removed. The \nshift can be found in the aux.shift auxiliary matrix. To reproduce the \noriginal A matrix, use A = Problem.A + Problem.aux.shift ; \n | |
| 1857`Sinclair`3Dspectralwave2`292008`292008`12935272`yes`292008`1`1`1387472`symmetric`symmetric`complex`Hermitian`yes`no`C. Sinclair`T. Davis`2007`materials problem`\nThe A matrix is produced using 3-D spectral-element elastic wave modelling in\nthe frequency domain.The medium is homogeneous and isotropic with elastic \ncoefficients: c11 = 6.30, c44 = 1.00. The B matrix contains only one non-zero\nentry, representing a real y-directed source, placed approximately in the \ncentre. The model size in elements is 10x10x10. Each element is 1m x1m x 1m.\nEach element is a 4x4x4 Gauss-Lobbato-Legendre mesh, so the height, width and\ndepth of the system is 31 nodes. There are 3 unknown complex components at \neach node - the x, y and z displacements. The A matrix therefore has \ndimension 89373 x 89373. ((10 x 4) - (10 - 1))^3 * 3 = 89373. The solution \nwill consist of x-z planes. Note that A is complex and b is sparse and real \n(b has a single nonzero). \n \nThe A matrix was provided with a nonzero imaginary part, but was otherwise \ncomplex Hermitian. To save space in the Matrix Market and Rutherford/Boeing \nformats, the A matrix here has had this imaginary diagonal removed. The \nshift can be found in the aux.shift auxiliary matrix. To reproduce the \noriginal A matrix, use A = Problem.A + Problem.aux.shift ; \n | |
| 1858`QLi`crashbasis`160000`160000`1750416`yes`160000`1`1`0`55%`0%`real`unsymmetric`no`no`Q. Li and M. Ferris`T. Davis`2007`optimization problem`\nQLi/crashbasis and QLi/majorbasis have the same nonzero pattern. However,\nUMFPACK 5.1 is much slower for majorbasis than for crashbasis, because of \nthe extensive number of denormal floating-point values that occur in \nmajorbasis (they do not occur in crashbasis). \n | |
| 1859`QLi`majorbasis`160000`160000`1750416`yes`160000`1`1`0`55%`0%`real`unsymmetric`no`no`Q. Li and M. Ferris`T. Davis`2007`optimization problem`\nQLi/crashbasis and QLi/majorbasis have the same nonzero pattern. However,\nUMFPACK 5.1 is much slower for majorbasis than for crashbasis, because of \nthe extensive number of denormal floating-point values that occur in \nmajorbasis (they do not occur in crashbasis). \n | |
| 1860`Springer`ESOC`327062`37830`6019939`no`37349`74`482`0`0%`0%`real`rectangular`no`no`T. Springer and F. Dilssner`T. Davis`2007`least squares problem` | |
| 1861`Koutsovasilis`F2`71505`71505`5294285`yes`71505`1`1`0`symmetric`symmetric`real`symmetric`yes`no`P. Koutsovasilis`T. Davis`2007`structural problem`\nStiffness matrix from an AUDI engine piston rod. This matrix is an ill- \ncondition symmetric indefinite matrix. In MATLAB 7.4, the matrix is \nfactorized three times in x=A\b. Inside backslash, CHOLMOD is tried first \nsince the matrix is symmetric and all diagonal entries are positive. CHOLMOD\nfails since the matrix is indefinite. Next, UMFPACK is used with default \npivot tolerances which maintain sparsity at the (rare) expense of a slight \ndecrease in accuracy. This succeeds, but the result is flagged as \npotentially inaccurate because the condition estimate is high. UMFPACK is \nthen used again with more conservative tolerances (but more fill-in). \n | |
| 1862`Szczerba`Ill_Stokes`20896`20896`191368`yes`20896`1`1`0`99%`33%`real`unsymmetric`no`no`D. Szczerba`T. Davis`2007`computational fluid dynamics problem`\nThe matrix comes from a global formulation of the Stokes problem posed \ndirectly (without pressure correction) on an unstructured tet mesh. It \nincludes momentum equations (3 quadrants) and continuity equation (last \nquadrant). Unknowns are organized as : vx, vy, vz, p. The last quadrant\ndoes not contain diagonal entries of course (continuity eq. does not \ncontain pressure) and is the reason bicgstab and related methods do not \nwork. Does not invert nicely with umfpack (strong oscillations in the \n4th quadrant of the solution). LSQR produces better results (smaller \noscillations) but takes ages. Dominik Szczerba, Ph.D. Computer Vision \nLab, ETH. CH-8092 Zurich. http://www.vision.ee.ethz.ch/~domi \n | |
| 1863`Rajat`Raj1`263743`263743`1300261`yes`263743`169`3`2203`100%`58%`real`unsymmetric`no`no`Raj`T. Davis`2007`circuit simulation problem`\nHigh fill-in with KLU, because the matrix is nearly singular and lots of \npartial pivoting occurs. If the pattern of A+A' is considered to be the \nnonzero pattern of a symmetric positive definite matrix, then nnz(L) has \nonly 3728967 nonzeros using p=amd(A) and chol(A(p,p)), where A excludes\nthe explicit zeros in Problem.Zeros. The flop count for the Cholesky \nfactorization is only 340.9 million. With a pivot tolerance of 2.2e-16, \nKLU Version 1.0 constructs and LU factorization with about 31 million \nnonzeros, even though it uses AMD for the diagonal blocks of the BTF for \nwhich the expected nnz(L) is only 3.705 million (for the Cholesky factor-\nization of the large diagonal block). The BTF form has little impact on \nthe factorization. \n | |
| 1864`Muite`Chebyshev1`261`261`2319`yes`261`1`1`0`50%`0%`real`unsymmetric`no`no`B. Muite`T. Davis`2007`structural problem`\nChebyshev integration matrix from Benson Muite, Oxford. Details of the \nmatrices can be found in a preprint at http://www.maths.ox.ac.uk/~muite \nentitled \"A comparison of Chebyshev methods for solving fourth-order \nsemilinear initial boundary value problems,\" June 2007. These matrices \nare very ill-conditioned, partly because of the dense rows which are hard\nto scale when coupled with the rest of the matrix. \n | |
| 1865`Muite`Chebyshev2`2053`2053`18447`yes`2053`1`1`0`50%`0%`real`unsymmetric`no`no`B. Muite`T. Davis`2007`structural problem`\nChebyshev integration matrix from Benson Muite, Oxford. Details of the \nmatrices can be found in a preprint at http://www.maths.ox.ac.uk/~muite \nentitled \"A comparison of Chebyshev methods for solving fourth-order \nsemilinear initial boundary value problems,\" June 2007. These matrices \nare very ill-conditioned, partly because of the dense rows which are hard\nto scale when coupled with the rest of the matrix. \n | |
| 1866`Muite`Chebyshev3`4101`4101`36879`yes`4101`1`1`0`50%`0%`real`unsymmetric`no`no`B. Muite`T. Davis`2007`structural problem`\nChebyshev integration matrix from Benson Muite, Oxford. Details of the \nmatrices can be found in a preprint at http://www.maths.ox.ac.uk/~muite \nentitled \"A comparison of Chebyshev methods for solving fourth-order \nsemilinear initial boundary value problems,\" June 2007. These matrices \nare very ill-conditioned, partly because of the dense rows which are hard\nto scale when coupled with the rest of the matrix. \n | |
| 1867`Muite`Chebyshev4`68121`68121`5377761`yes`68121`1`1`0`30%`0%`real`unsymmetric`no`no`B. Muite`T. Davis`2007`structural problem`\nChebyshev integration matrix from Benson Muite, Oxford. Details of the \nmatrices can be found in a preprint at http://www.maths.ox.ac.uk/~muite \nentitled \"A comparison of Chebyshev methods for solving fourth-order \nsemilinear initial boundary value problems,\" June 2007. These matrices \nare very ill-conditioned, partly because of the dense rows which are hard\nto scale when coupled with the rest of the matrix. \n | |
| 1868`Quaglino`viscoplastic1`4326`4326`61166`yes`4326`1`1`0`74%`0%`real`unsymmetric`no`no`A. Quaglino`T. Davis`2007`materials problem`\nThe matrix is in the form [A11 A12 ; A21 A22] where A11 and A22 are diagonal. \nOriginally, the matrices in this set were poorly scaled, but this was resolved\nby a scale factor of the form [A11 A12*e ; A21/e A4] where the scalar e is \nof magnitude 1e2 but can be 1e6 or 1e7 for a stiff material. The Problem.A \nmatrix is the properly scaled problem. The Problem.aux.C{1:7} matrices have \nbeen \"unscaled\" with a factor e = 10.^(-(1:7)), to give a sequence of matrices\nthat are well scaled to poorly scaled, and thus well conditioned (C{1}) to \npoorly conditioned (C{7}). This mimics the original poorly scaled and ill- \nconditioned problem, and may be of interest for those developing algorithms \nfor automatic scaling. From a FEM discretization of a viscoplastic collision \nproblem, Alessio Quaglino. \n | |
| 1869`Quaglino`viscoplastic2`32769`32769`381326`yes`32769`1`1`0`57%`0%`real`unsymmetric`no`no`A. Quaglino`T. Davis`2007`materials problem`\nThe matrix is in the form [A11 A12 ; A21 A22] where A11 and A22 are diagonal. \nOriginally, the matrices in this set were poorly scaled, but this was resolved\nby a scale factor of the form [A11 A12*e ; A21/e A4] where the scalar e is \nof magnitude 1e2 but can be 1e6 or 1e7 for a stiff material. The Problem.A \nmatrix is the properly scaled problem. The Problem.aux.C{1:7} matrices have \nbeen \"unscaled\" with a factor e = 10.^(-(1:7)), to give a sequence of matrices\nthat are well scaled to poorly scaled, and thus well conditioned (C{1}) to \npoorly conditioned (C{7}). This mimics the original poorly scaled and ill- \nconditioned problem, and may be of interest for those developing algorithms \nfor automatic scaling. From a FEM discretization of a viscoplastic collision \nproblem, Alessio Quaglino. \n | |
| 1870`YCheng`psse0`26722`11028`102432`yes`11028`1`1`0`0%`0%`real`rectangular`no`no`Y. Cheng`T. Davis`2007`power network problem`\nPower system state simulation matrix from Yunzhi Cheng, UT Arlington.\nIn MATLAB, the solution to x=A\b is desired, but this can be slow in \nMATLAB 7.3 because of the speed of sparse QR as compared to sparse \nCholesky. Using x=(A'*A)\(A'*b) is faster, but of course yields \nslightly less accurate (but still acceptable) results. Note that an \ninitial guess to the solution is provided, for use by an iterative \nmethod. However, sparse Cholesky with an AMD ordering is very fast \nfor this matrix and thus iterative methods are unlikely to be \ncompetitive. In MATLAB 7.3 on a 3.2 Ghz Pentium 4 desktop, \nx=(A'*A)\(A'*b) takes 0.07 seconds. \n | |
| 1871`YCheng`psse1`14318`11028`57376`yes`11028`1722`1`0`0%`0%`real`rectangular`no`no`Y. Cheng`T. Davis`2007`power network problem`\nPower system state simulation matrix from Yunzhi Cheng, UT Arlington.\nIn MATLAB, the solution to x=A\b is desired, but this can be slow in \nMATLAB 7.3 because of the speed of sparse QR as compared to sparse \nCholesky. Using x=(A'*A)\(A'*b) is faster, but of course yields \nslightly less accurate (but still acceptable) results. Note that an \ninitial guess to the solution is provided, for use by an iterative \nmethod. However, sparse Cholesky with an AMD ordering is very fast \nfor this matrix and thus iterative methods are unlikely to be \ncompetitive. In MATLAB 7.3 on a 3.2 Ghz Pentium 4 desktop, \nx=(A'*A)\(A'*b) takes 0.05 seconds. \n | |
| 1872`YCheng`psse2`28634`11028`115262`yes`11028`1`1`0`0%`0%`real`rectangular`no`no`Y. Cheng`T. Davis`2007`power network problem`\nPower system state simulation matrix from Yunzhi Cheng, UT Arlington.\nIn MATLAB, the solution to x=A\b is desired, but this can be slow in \nMATLAB 7.3 because of the speed of sparse QR as compared to sparse \nCholesky. Using x=(A'*A)\(A'*b) is faster, but of course yields \nslightly less accurate (but still acceptable) results. Note that an \ninitial guess to the solution is provided, for use by an iterative \nmethod. However, sparse Cholesky with an AMD ordering is very fast \nfor this matrix and thus iterative methods are unlikely to be \ncompetitive. In MATLAB 7.3 on a 3.2 Ghz Pentium 4 desktop, \nx=(A'*A)\(A'*b) takes 0.07 seconds. \n | |
| 1873`Dehghani`light_in_tissue`29282`29282`406084`yes`29282`1`1`0`symmetric`0%`complex`unsymmetric`no`no`H. Dehghani`T. Davis`2007`electromagnetics problem`\n% The problem is solving the fluence (PHI) of light in soft tissue using\n% a simplified 3rd spherical harmonic expansion (SPN3) of the Radiative \n% Transport Equation. There are two coupled equations to solve: \n% M1*phi1 = Q + (M2*phi2) eq(1) \n% (M4 - (M3*inv(M1)*M2))*phi2 = -2/3*Q + M3*inv(M1)*Q eq(2) \n% PHI = phi1 - (1/3).*phi2 eq(3) \n \nProblem = UFget ('Dehghani/light_in_tissue') ; \nA = Problem.A ; % get the problem \nQ = Problem.aux.Q ; \nk = size (A,1) / 2 ; \nM1 = A (1:k,1:k) ; \nM2 = A (1:k,k+1:end) ; \nM3 = A (k+1:end, 1:k) ; \nM4 = A (k+1:end, k+1:end) ; \nelements = Problem.aux.elements ; \nnodes = Problem.aux.nodes ; \n \nQ2 = (-(2/3).*Q) + (M3*(M1\Q)) ; % create rhs for equation 2 \nQ2 = [sparse(k,1) ; Q2] ; \nphi2 = A\Q2 ; % solve for phi2 \nphi2 = phi2 (end/2+1:end,:) ; \nQ1 = Q + M2*phi2 ; % calculate rhs for equation 1 \nphi1 = M1\Q1; % solve for phi1 \nPHI = phi1 - (1/3).*phi2; \nfigure (1) ; clf % plot results \ntrisurf(elements, nodes(:,1), nodes(:,2), nodes(:,3), log(abs(PHI))) ; \nshading interp ; \nview (2) ; \ncolorbar('horiz') ; \naxis equal ; \naxis off ; \ncolormap hot ; \n | |
| 1874`HVDC`hvdc1`24842`24842`158426`yes`24842`31`7`1555`98%`10%`real`unsymmetric`no`no`A. Wang`T. Davis`2007`power network problem` | |
| 1875`HVDC`hvdc2`189860`189860`1339638`yes`189860`69`67`7635`99%`6%`real`unsymmetric`no`no`A. Wang`T. Davis`2007`power network problem` | |
| 1876`Zaoui`kkt_power`2063494`2063494`12771361`yes`2063494`9733`9611`1841302`symmetric`symmetric`real`symmetric`no`no`F. Zaoui`T. Davis`2007`optimization problem` | |
| 1877`Rost`RFdevice`74104`74104`365580`yes`74104`114`1`0`0%`0%`complex`unsymmetric`no`no`J. Rost`T. Davis`2007`semiconductor device problem`\nNumerical Methods Laboratory, Politehnica Univ., Bucharest, Romania. \nJohann Rost, et al. RF semiconductors and electronic device simulation\nin the frequency domain. UMFPACK (x=A\b in MATLAB) experiences high \nfill-in for this matrix. KLU is worse. \n | |
| 1878`Lee`fem_filter`74062`74062`1731206`yes`74062`1`1`0`symmetric`61%`complex`unsymmetric`no`no`S.-H. Lee`T. Davis`2008`electromagnetics problem`\nFrom the Univ of Illinois at Urbana-Champaign, Center for Computational \nElectromagnetics (development and application of the finite element \nmethod for analyzing antennas, high-frequency circuits, high-speed \ncircuits, and so on). The governing equations are Maxwell's equations. \nThe matrix results from the finite-element discretization of a bandpass \nmicrowave filter at 500 MHz. The first-order vector element is employed.\nThe absorbing boundary condition is applied on the outer boundary of the\nstructure for emulating the open space. The port boundary condition is \napplied on each port of the circuit for the truncating the computational\ndomain and exciting the circuit. Due to these boundary conditions, the \nfinite-element system matrix is complex. \n | |
| 1879`Mancktelow`viscorocks`37762`37762`1133641`yes`37762`773`773`28603`symmetric`28%`real`unsymmetric`no`no`N. Mancktelow`T. Davis`2007`materials problem` | |
| 1880`Rudnyi`water_tank`60740`60740`2035281`yes`60740`2`2`0`97%`92%`real`unsymmetric`no`no`E. Rudnyi`T. Davis`2007`computational fluid dynamics problem` | |
| 1881`Rucci`Rucci1`1977885`109900`7791168`yes`109900`1`1`0`0%`0%`real`rectangular`no`no`A. Rucci`T. Davis`2007`least squares problem` | |
| 1882`McRae`ecology1`1000000`1000000`4996000`yes`1000000`1`1`0`symmetric`symmetric`real`symmetric`yes`no`B. McRae`T. Davis`2008`2D/3D problem`\nLandscape ecology problem, using electrical network theory to model \nanimal movement an gene flow. The McRae/ecology1 matrix comes from \na 2D, 1000-by-1000 mesh (5 pt stencil). It is an ill-conditioned \nsymmetric indefinite matrix. Source: Brad McRae, National Center \nfor Ecological Analysis and Synthesis Santa Barbara, CA. \n | |
| 1883`McRae`ecology2`999999`999999`4995991`yes`999999`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`B. McRae`T. Davis`2008`2D/3D problem`\nLandscape ecology problem, using electrical network theory to model \nanimal movement an gene flow. The McRae/ecology2 matrix comes from \na 2D, 1000-by-1000 mesh (5 pt stencil). It is a symmetric positive \ndefinite matrix. Source: Brad McRae, National Center for Ecological\nAnalysis and Synthesis Santa Barbara, CA. \n | |
| 1884`NYPA`Maragal_1`32`14`234`yes`14`1`1`0`0%`0%`real`rectangular`no`no`D. Maragal`T. Davis`2008`least squares problem`\nrank deficient (rank(A) < sprank(A) == size(A,2))\nrank: 10 sprank: 14 columns: 14 \n | |
| 1885`NYPA`Maragal_2`555`350`4357`no`220`13`110`0`0%`0%`real`rectangular`no`no`D. Maragal`T. Davis`2008`least squares problem`\nrank deficient (rank(A) < sprank(A) < size(A,2))\nrank: 171 sprank: 220 columns: 350 \n | |
| 1886`NYPA`Maragal_3`1690`860`18391`no`765`35`11`0`0%`0%`real`rectangular`no`no`D. Maragal`T. Davis`2008`least squares problem`\nrank deficient (rank(A) < sprank(A) < size(A,2))\nrank: 613 sprank: 765 columns: 860 \n | |
| 1887`NYPA`Maragal_4`1964`1034`26719`no`995`23`8`0`0%`0%`real`rectangular`no`no`D. Maragal`T. Davis`2008`least squares problem`\nrank deficient (rank(A) < sprank(A) < size(A,2))\nrank: 801 sprank: 995 columns: 1034 \n | |
| 1888`NYPA`Maragal_5`4654`3320`93091`no`2690`163`25`0`0%`0%`real`rectangular`no`no`D. Maragal`T. Davis`2008`least squares problem`\nrank deficient (rank(A) < sprank(A) < size(A,2))\nrank: 2147 sprank: 2690 columns: 3320 \n | |
| 1889`NYPA`Maragal_6`21255`10152`537694`no`10052`89`13`0`0%`0%`real`rectangular`no`no`D. Maragal`T. Davis`2008`least squares problem`\nrank deficient (rank(A) < sprank(A) < size(A,2))\nsprank: 10052 columns: 10152 \n | |
| 1890`NYPA`Maragal_7`46845`26564`1200537`no`25866`1294`41`0`0%`0%`real`rectangular`no`no`D. Maragal`T. Davis`2008`least squares problem`\nrank deficient (rank(A) < sprank(A) < size(A,2))\nsprank: 25866 columns: 26564 \n | |
| 1891`Marini`eurqsa`7245`7245`46142`yes`7245`3`3`0`symmetric`symmetric`real`symmetric`no`no`T. Di Fonzo, M. Marini`T. Davis`2008`economic problem`\nEconomic statistics are often published in the form of time series, as a \ncollection of observations sampled at equally-spaced time periods (months, \nquarters). Economic concepts behind such statistics are often linked by a \nsystem of linear relationships, deriving from the economic theory. However,\nthese restrictions are rarely met by the original time series for various \nreasons. Then, data sets of real-world variables generally show \ndiscrepancies with respect to prior restrictions on their values. The \nadjustment of a set of data in order to satisfy a number of accounting \nrestrictions -and thus to remove any discrepancy -is generally known as \nthe reconciliation problem. \n \nThe matrix comes from a real application composed of 183 quarterly time \nseries observed over 28 quarters, which form the system of European \nnational accounts by institutional sectors (EURQSA). Then, the number of \nobservations to be reconciled is n = 28 x 183 = 5124. The variables are \nconnected by a system of 30 linear relationships. Moreover, each quarterly \ntime series must be in line with the same variables observed yearly (due \nto different compilation practices quarterly and annual estimates might \ndiffer). The total number of constraints of the system is k = 2121. On \nthe whole, matrix A has dimension 7245, with block (11) of dimension 5124.\n | |
| 1892`Castrillon`denormal`89400`89400`1156224`yes`89400`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`J. Castrillon`T. Davis`2008`counter-example problem`\nThe problem is x=(A+alpha*I)\b as alpha varies from 0 to 100. However,\nas this occurs, performance suffers because of the many denormals that \nappear below the diagonal in L. \n | |
| 1893`QLi`largebasis`440020`440020`5240084`yes`440020`1`1`320016`symmetric`0%`real`unsymmetric`no`no`Q. Li`T. Davis`2008`optimization problem` | |
| 1894`MathWorks`QRpivot`660`749`3808`yes`660`9`1`0`0%`0%`real`rectangular`no`no`P. Quillen`T. Davis`2008`counter-example problem`\nCounter-example problem from The MathWorks, Pat Quillen \n \nThis matrix was obtained from a MATLAB user. It illustrates the \nlimitations inherent in computing a basic solution to an under- \ndetermined system without the use of column pivoting. \n \nWith column pivoting (which can only be done in MATLAB with full \nmatrices) the problem is solved properly. \n \nWhen finding the min 2-norm solution (ignoring fill-in): \n \n [Q,R] = qr (A') ; \n x = Q*(R'\b) ; \n \na good solution is found. To reduce fill-in: \n \n p = colamd (A') ; \n [Q,R] = qr (A (p,:)') ; \n x = Q*(R'\b(p)) ; \n \nwhich also finds a good solution. \n \nHowever, x=A\b computes a basic solution, using this algorithm: \n \n q = colamd (A) ; \n [Q,R] = qr (A (:,q)) ; \n x = R\(Q'*b) ; \n x (q) = q ; \n \nwhich finds an error with norm(A*x-b) of 1e-9 in MATLAB 7.6. \n \nWith random permutations, and determining the cond(R1) of the leading \ntrianglar part (R is \"squeezed\" and the columns can be partitioned into \n[R1 R2] where R1 is square and upper triangular) leads to the following \nresults. \n \nNote that the error is high when condest(R1) is high. Note in \nparticular the last trial. \n \nSo this clinches the question. MATLAB's QR, and my new sparse QR, both \nuse a rank-detection method (by Heath) that does not do column pivoting,\nand which is known to fail for some problems - for which Grimes & Lewis'\nmethod will likely succeed. \n \nThe advantage of my QR is that I now always return R as upper \ntrapezoidal, so if the user is concerned, he/she can easily check \ncondest(R(:,1:m)) if m < n. \n \n err 7.71e-07 condest R1 2.18e+12 \n err 1.25e-09 condest R1 9.82e+08 \n err 2.47e-09 condest R1 2.46e+11 \n err 4.00e-09 condest R1 4.03e+09 \n err 9.88e-10 condest R1 4.73e+09 \n err 2.25e-08 condest R1 5.34e+09 \n err 2.00e-08 condest R1 1.04e+09 \n err 1.09e-09 condest R1 6.83e+08 \n err 6.18e-08 condest R1 8.13e+10 \n err 3.13e-10 condest R1 4.23e+09 \n err 6.64e-10 condest R1 2.46e+10 \n err 5.76e-09 condest R1 4.31e+09 \n err 7.61e-07 condest R1 5.08e+10 \n err 2.27e-09 condest R1 4.94e+09 \n err 3.99e-10 condest R1 2.80e+09 \n err 1.37e-09 condest R1 3.13e+09 \n err 6.93e-05 condest R1 1.84e+14 \n err 1.35e-08 condest R1 7.18e+09 \n err 1.09e-08 condest R1 1.79e+11 \n err 1.81e-09 condest R1 2.99e+08 \n err 1.55e-01 condest R1 2.45e+18 \n \nIn summary, this is a \"feature\" not a \"bug\". If you want a reliable \nsolution to an underdetermined system, find the min 2norm solution \nvia a QR factorization of A'. \n | |
| 1895`Luong`photogrammetry`1388`390`11816`yes`390`1`1`0`0%`0%`real`rectangular`no`no`B. Luong`T. Davis`2008`computer graphics/vision problem`\nPhotogrammetry problem from Bruno Luong, FOGALE nanotech, France. \nThe problem of interest is: \n [U S V]=svd(full(A),0); \n s=diag(S); \nThe spectrum has two parts: \n- the singular values s(1) to s(end-7) are 1.7486e-004 to 3.4655e-007 \n(ratio 504.57). \n- the singular values s(end-6) to s(end) is smaller than 2.9614e-012 \n(ratio > 5.9e7). \nSo in this problem, the following are considered: \nK = span<U(:,end-6:end) > is the kernel of A, and \nL = span<U(:,1:end-7) > = orthogonal(K) is isomorph to Im(A). \n | |
| 1896`YZhou`circuit204`1020`1020`5883`yes`1020`157`114`0`44%`37%`real`unsymmetric`no`no`Y. Zhou`T. Davis`2008`circuit simulation problem`\nblock size 204*204\n | |
| 1897`CEMW`t2em`921632`921632`4590832`yes`921632`4333`4333`0`100%`100%`integer`unsymmetric`no`no`D. Isaak`T. Davis`2008`electromagnetics problem` | |
| 1898`CEMW`tmt_unsym`917825`917825`4584801`yes`917825`1`1`0`symmetric`0%`real`unsymmetric`no`no`D. Isaak`T. Davis`2008`electromagnetics problem` | |
| 1899`CEMW`tmt_sym`726713`726713`5080961`yes`726713`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`D. Isaak`T. Davis`2008`electromagnetics problem` | |
| 1900`CEMW`vfem`93476`93476`1434636`yes`93476`1`1`0`symmetric`82%`complex`unsymmetric`no`no`D. Isaak`T. Davis`2008`electromagnetics problem` | |
| 1901`Schenk`nlpkkt80`1062400`1062400`28192672`yes`1062400`1`1`512000`symmetric`symmetric`real`symmetric`no`no`O. Schenk, A. Waechter, M. Weiser`T. Davis`2008`optimization problem`\nSymmetric indefinite KKT matrices, O. Schenk, Univ. of Basel, \nSwitzerland \nNonlinear programming problems for a 3D PDE-constrained optimization \nproblem with boundary control as a function of the discretization \nparameter N using 2nd-order finite difference approximations. \n \nO. Schenk, A. W\"achter, and M. Weiser, Inertia Revealing \nPreconditioning For Large-Scale Nonconvex Constrained Optimization, \nTechnical Report, Unversity of Basel, 2008, submitted. \n \nAbstract: Fast nonlinear programming methods following the \nall-at-once approach usually employ Newton's method for solving \nlinearized Karush-Kuhn-Tucker (KKT) systems. In nonconvex problems, \nthe Newton direction is only guaranteed to be a descent direction if \nthe Hessian of the Lagrange function is positive definite on the \nnullspace of the active constraints, otherwise some modifications to \nNewton's method are necessary. This condition can be verified using \nthe signs of the KKT's eigenvalues (inertia), which are usually \navailable from direct solvers for the arising linear saddle point \nproblems. Iterative solvers are mandatory for very large-scale \nproblems, but in general do not provide the inertia. Here we present \na preconditioner based on a multilevel incomplete LBL^T \nfactorization, from which an approximation of the inertia can be \nobtained. The suitability of the heuristics for application in \noptimization methods is verified on an interior point method applied \nto the CUTE and COPS test problems, on large-scale 3D PDE-constrained \noptimal control problems, as well as 3D PDE-constrained optimization \nin biomedical cancer hyperthermia treatment planning. The efficiency \nof the preconditioner is demonstrated on convex and nonconvex \nproblems with 1503 state variables and 1502 control variables, both \nsubject to bound constraints. \n | |
| 1902`Schenk`nlpkkt120`3542400`3542400`95117792`yes`3542400`1`1`1728000`symmetric`symmetric`real`symmetric`no`no`O. Schenk, A. Waechter, M. Weiser`T. Davis`2008`optimization problem`\nSymmetric indefinite KKT matrices, O. Schenk, Univ. of Basel, \nSwitzerland \nNonlinear programming problems for a 3D PDE-constrained optimization \nproblem with boundary control as a function of the discretization \nparameter N using 2nd-order finite difference approximations. \n \nO. Schenk, A. W\"achter, and M. Weiser, Inertia Revealing \nPreconditioning For Large-Scale Nonconvex Constrained Optimization, \nTechnical Report, Unversity of Basel, 2008, submitted. \n \nAbstract: Fast nonlinear programming methods following the \nall-at-once approach usually employ Newton's method for solving \nlinearized Karush-Kuhn-Tucker (KKT) systems. In nonconvex problems, \nthe Newton direction is only guaranteed to be a descent direction if \nthe Hessian of the Lagrange function is positive definite on the \nnullspace of the active constraints, otherwise some modifications to \nNewton's method are necessary. This condition can be verified using \nthe signs of the KKT's eigenvalues (inertia), which are usually \navailable from direct solvers for the arising linear saddle point \nproblems. Iterative solvers are mandatory for very large-scale \nproblems, but in general do not provide the inertia. Here we present \na preconditioner based on a multilevel incomplete LBL^T \nfactorization, from which an approximation of the inertia can be \nobtained. The suitability of the heuristics for application in \noptimization methods is verified on an interior point method applied \nto the CUTE and COPS test problems, on large-scale 3D PDE-constrained \noptimal control problems, as well as 3D PDE-constrained optimization \nin biomedical cancer hyperthermia treatment planning. The efficiency \nof the preconditioner is demonstrated on convex and nonconvex \nproblems with 1503 state variables and 1502 control variables, both \nsubject to bound constraints. \n | |
| 1903`Schenk`nlpkkt160`8345600`8345600`225422112`yes`8345600`1`1`4096000`symmetric`symmetric`real`symmetric`no`no`O. Schenk, A. Waechter, M. Weiser`T. Davis`2008`optimization problem`\nSymmetric indefinite KKT matrices, O. Schenk, Univ. of Basel, \nSwitzerland \nNonlinear programming problems for a 3D PDE-constrained optimization \nproblem with boundary control as a function of the discretization \nparameter N using 2nd-order finite difference approximations. \n \nO. Schenk, A. W\"achter, and M. Weiser, Inertia Revealing \nPreconditioning For Large-Scale Nonconvex Constrained Optimization, \nTechnical Report, Unversity of Basel, 2008, submitted. \n \nAbstract: Fast nonlinear programming methods following the \nall-at-once approach usually employ Newton's method for solving \nlinearized Karush-Kuhn-Tucker (KKT) systems. In nonconvex problems, \nthe Newton direction is only guaranteed to be a descent direction if \nthe Hessian of the Lagrange function is positive definite on the \nnullspace of the active constraints, otherwise some modifications to \nNewton's method are necessary. This condition can be verified using \nthe signs of the KKT's eigenvalues (inertia), which are usually \navailable from direct solvers for the arising linear saddle point \nproblems. Iterative solvers are mandatory for very large-scale \nproblems, but in general do not provide the inertia. Here we present \na preconditioner based on a multilevel incomplete LBL^T \nfactorization, from which an approximation of the inertia can be \nobtained. The suitability of the heuristics for application in \noptimization methods is verified on an interior point method applied \nto the CUTE and COPS test problems, on large-scale 3D PDE-constrained \noptimal control problems, as well as 3D PDE-constrained optimization \nin biomedical cancer hyperthermia treatment planning. The efficiency \nof the preconditioner is demonstrated on convex and nonconvex \nproblems with 1503 state variables and 1502 control variables, both \nsubject to bound constraints. \n | |
| 1904`Schenk`nlpkkt200`16240000`16240000`440225632`yes`16240000`1`1`8000000`symmetric`symmetric`real`symmetric`no`no`O. Schenk, A. Waechter, M. Weiser`T. Davis`2008`optimization problem`\nSymmetric indefinite KKT matrices, O. Schenk, Univ. of Basel, \nSwitzerland \nNonlinear programming problems for a 3D PDE-constrained optimization \nproblem with boundary control as a function of the discretization \nparameter N using 2nd-order finite difference approximations. \n \nO. Schenk, A. W\"achter, and M. Weiser, Inertia Revealing \nPreconditioning For Large-Scale Nonconvex Constrained Optimization, \nTechnical Report, Unversity of Basel, 2008, submitted. \n \nAbstract: Fast nonlinear programming methods following the \nall-at-once approach usually employ Newton's method for solving \nlinearized Karush-Kuhn-Tucker (KKT) systems. In nonconvex problems, \nthe Newton direction is only guaranteed to be a descent direction if \nthe Hessian of the Lagrange function is positive definite on the \nnullspace of the active constraints, otherwise some modifications to \nNewton's method are necessary. This condition can be verified using \nthe signs of the KKT's eigenvalues (inertia), which are usually \navailable from direct solvers for the arising linear saddle point \nproblems. Iterative solvers are mandatory for very large-scale \nproblems, but in general do not provide the inertia. Here we present \na preconditioner based on a multilevel incomplete LBL^T \nfactorization, from which an approximation of the inertia can be \nobtained. The suitability of the heuristics for application in \noptimization methods is verified on an interior point method applied \nto the CUTE and COPS test problems, on large-scale 3D PDE-constrained \noptimal control problems, as well as 3D PDE-constrained optimization \nin biomedical cancer hyperthermia treatment planning. The efficiency \nof the preconditioner is demonstrated on convex and nonconvex \nproblems with 1503 state variables and 1502 control variables, both \nsubject to bound constraints. \n | |
| 1905`Schenk`nlpkkt240`27993600`27993600`760648352`yes`27993600`1`1`13824000`symmetric`symmetric`real`symmetric`no`no`O. Schenk, A. Waechter, M. Weiser`T. Davis`2008`optimization problem`\nSymmetric indefinite KKT matrices, O. Schenk, Univ. of Basel, \nSwitzerland \nNonlinear programming problems for a 3D PDE-constrained optimization \nproblem with boundary control as a function of the discretization \nparameter N using 2nd-order finite difference approximations. \n \nO. Schenk, A. W\"achter, and M. Weiser, Inertia Revealing \nPreconditioning For Large-Scale Nonconvex Constrained Optimization, \nTechnical Report, Unversity of Basel, 2008, submitted. \n \nAbstract: Fast nonlinear programming methods following the \nall-at-once approach usually employ Newton's method for solving \nlinearized Karush-Kuhn-Tucker (KKT) systems. In nonconvex problems, \nthe Newton direction is only guaranteed to be a descent direction if \nthe Hessian of the Lagrange function is positive definite on the \nnullspace of the active constraints, otherwise some modifications to \nNewton's method are necessary. This condition can be verified using \nthe signs of the KKT's eigenvalues (inertia), which are usually \navailable from direct solvers for the arising linear saddle point \nproblems. Iterative solvers are mandatory for very large-scale \nproblems, but in general do not provide the inertia. Here we present \na preconditioner based on a multilevel incomplete LBL^T \nfactorization, from which an approximation of the inertia can be \nobtained. The suitability of the heuristics for application in \noptimization methods is verified on an interior point method applied \nto the CUTE and COPS test problems, on large-scale 3D PDE-constrained \noptimal control problems, as well as 3D PDE-constrained optimization \nin biomedical cancer hyperthermia treatment planning. The efficiency \nof the preconditioner is demonstrated on convex and nonconvex \nproblems with 1503 state variables and 1502 control variables, both \nsubject to bound constraints. \n | |
| 1906`TKK`s4dkt3m2`90449`90449`3753461`yes`90449`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1907`TKK`g3rmt3m3`5357`5357`207695`yes`5357`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1908`TKK`t520`5563`5563`286341`yes`5563`1`1`0`symmetric`symmetric`integer`symmetric`yes`no`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1909`TKK`smt`25710`25710`3749582`yes`25710`1`1`3602`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html \n \nSurface mount transistor, 1704 reduced triquadratic elem, therm stress.\nThis is a stiffness matrix from a thermal stress analysis of \na surface mounted transistor. Due to symmetry only one half of \nthe model is discretized in 1704 standard reduced triquadratic elements\n(20 node serendipity). There are 5 different materials. \nThe stiffness matrix is integrated by 3x3x3 Gaussian quadrature. \nSeparate load vector file is also available. \nFigure of the FE model can be seen in a separate description, \nor downloaded as a postscript file from the contributors www-pages. \nContributor: \nReijo Kouhia, Helsinki University of Technology, \n Laboratory of Structural Mechanics \n PO Box 2100, 02015 HUT, Finland \n e-mail: reijo.kouhia@hut.fi \n http://www.hut.fi/~kouhia \n | |
| 1910`TKK`engine`143571`143571`4706073`yes`143571`1`1`0`symmetric`symmetric`integer`symmetric`yes`no`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1911`TKK`plbuckle`1282`1282`30644`yes`1282`2`2`0`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1912`TKK`cbuckle`13681`13681`676515`yes`13681`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1913`TKK`cyl6`13681`13681`714241`yes`13681`1`1`0`symmetric`symmetric`integer`symmetric`yes`no`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1914`TKK`tube1`21498`21498`897056`yes`21498`1`1`0`symmetric`symmetric`binary`symmetric`yes`no`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1915`TKK`tube2`21498`21498`897056`yes`21498`1`1`0`symmetric`symmetric`integer`symmetric`yes`no`R. Kouhia`T. Davis`2008`structural problem`\nMatrix problems from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1916`TKK`t2d_q4`9801`9801`87025`yes`9801`1`1`0`symmetric`69%`real`unsymmetric`no`no`R. Kouhia`T. Davis`2008`structural problem sequence`\nMatrix sequence from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1917`TKK`t2d_q9`9801`9801`87025`yes`9801`1`1`0`symmetric`69%`real`unsymmetric`no`no`R. Kouhia`T. Davis`2008`structural problem sequence`\nMatrix sequence from Reijo Kouhia, Structural Mechanics, Helsinki \nUniversity of Technology. http://users.tkk.fi/~kouhia/sparse.html\n | |
| 1918`Luong`photogrammetry2`4472`936`37056`yes`936`1`1`0`0%`0%`real`rectangular`no`no`B. Luong`T. Davis`2008`computer graphics/vision problem`\nPhotogrammetry problem from Bruno Luong, FOGALE nanotech, France.\nThis problem is nearly rank-deficient. \n | |
| 1919`Um`2cubes_sphere`101492`101492`1647264`yes`101492`1`1`0`symmetric`symmetric`real`symmetric`yes`yes`E. Um`T. Davis`2008`electromagnetics problem`\nA matrix from Evan Um, Geophysics, Stanford. Studying finite-element \ntime domain solvers for electromagnetic diffusion equations. The 3-D \ncomputational domain consists of 88213 tetrahedral elements. The \ncomputational domain consists of the two parts. First, there are two \n300m x 300m x 150m boxes where a fine mesh is used. Second, the two \nboxes are enclosed by a large sphere whose radius is 10 km. An element\ngrowth factor is used to increase the mesh size gradually inside the \nsphere. This is because absorbing boundary conditions are not very \ngood choices for these problems. The finite element technique is \nedge-based rather than node-based. Therefore, the unknowns are \namplitudes of electromagnetic fields on an edge of each element. \n | |
| 1920`JGD_BIBD`bibd_9_3`36`84`252`yes`36`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd.9.3.sms \n | |
| 1921`JGD_BIBD`bibd_9_5`36`126`1260`yes`36`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd.9.5.sms \n | |
| 1922`JGD_BIBD`bibd_11_5`55`462`4620`yes`55`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd.11.5.sms \n | |
| 1923`JGD_BIBD`bibd_12_4`66`495`2970`yes`66`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd.12.4.sms \n | |
| 1924`JGD_BIBD`bibd_12_5`66`792`7920`yes`66`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_12_5_66x792 \n | |
| 1925`JGD_BIBD`bibd_13_6`78`1716`25740`yes`78`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_13_6_78x1716 \n | |
| 1926`JGD_BIBD`bibd_14_7`91`3432`72072`yes`91`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_14_7_91x3432.sms \n | |
| 1927`JGD_BIBD`bibd_15_3`105`455`1365`yes`105`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd.15.3.sms \n | |
| 1928`JGD_BIBD`bibd_15_7`105`6435`135135`yes`105`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_15_7_105x6435.sms \n | |
| 1929`JGD_BIBD`bibd_16_8`120`12870`360360`yes`120`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_16_8_120x12870.sms \n | |
| 1930`JGD_BIBD`bibd_17_3`136`680`2040`yes`136`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd.17.3.sms \n | |
| 1931`JGD_BIBD`bibd_17_4b`136`2380`14280`yes`136`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_17_4_136x2380.sms \n | |
| 1932`JGD_BIBD`bibd_17_4`136`2380`14280`yes`136`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd.17.4.sms \n | |
| 1933`JGD_BIBD`bibd_17_8`136`24310`680680`yes`136`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_17_8_136x24310.sms \n | |
| 1934`JGD_BIBD`bibd_18_9`153`48620`1750320`yes`153`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_18_9_153x48620.sms \n | |
| 1935`JGD_BIBD`bibd_19_9`171`92378`3325608`yes`171`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_19_9_171x92378.sms \n | |
| 1936`JGD_BIBD`bibd_20_10`190`184756`8314020`yes`190`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_20_10_190x184756.sms \n | |
| 1937`JGD_BIBD`bibd_22_8`231`319770`8953560`yes`231`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/BIBD_22_8_231x319770 \n | |
| 1938`JGD_BIBD`bibd_49_3`1176`18424`55272`yes`1176`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_49_3_1176x18424.sms \n | |
| 1939`JGD_BIBD`bibd_81_2`3240`3240`3240`yes`3240`3240`3240`0`symmetric`symmetric`binary`symmetric`yes`yes`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_81_2_3240x3240.sms \n | |
| 1940`JGD_BIBD`bibd_81_3`3240`85320`255960`yes`3240`1`1`0`0%`0%`binary`rectangular`no`no`M. Giesbrecht`J.-G. Dumas`2008`combinatorial problem`\nBalanced Incomplete Block Design from Mark Giesbrecht, Univ. of Waterloo\nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nFilename in JGD collection: BIBD/bibd_81_3_3240x85320.sms \n | |
| 1941`JGD_CAG`CAG_mat1916`1916`1916`195985`yes`1916`31`31`0`30%`21%`integer`unsymmetric`no`no`M. Monagan`J.-G. Dumas`2008`combinatorial problem`\nCAG matrix set from Michael Monagan, Simon Fraser Univ., Canada \nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nStrongly Connected Graph Components and Computing \nCharacteristic Polynomials of Integer Matrices in Maple, \nSimon Lo, Michael Monagan, Allan Wittkopf \n{sclo,mmonagan,wittkopf} at cecm.sfu.ca \nCentre for Experimental and Constructive Mathematics, \nDepartment of Mathematics, Simon Fraser University, \nBurnaby, B.C., V5A 1S6, Canada. \n \nabstract: \nLet A be an n x n matrix of integers. We present details of our Maple \nimplementation of a simple modular method for computing the \ncharacteristic polynomial of A. We consider several different \nrepresentations for the computation modulo primes, in particular, the \nuse of double precision floats. The algorithm used in Maple releases \n7-10 is the Berkowitz algorithm. We present some timings comparing the \ntwo algorithms on a sequence of matrices arising from an application in\ncombinatorics of Jocelyn Quaintance. These matrices have a hidden block\nstructure. Once identified, we can further reduce the computing time \ndramatically. This work has been incorporated into Maple 11's \nLinearAlgebra package. \n \nhttp://www.cecm.sfu.ca/~monaganm/papers/CP8.pdf \n \nFilename in JGD collection: CAG/mat1916.sms \n | |
| 1942`JGD_CAG`CAG_mat364`364`364`13585`yes`364`12`12`0`42%`28%`integer`unsymmetric`no`no`M. Monagan`J.-G. Dumas`2008`combinatorial problem`\nCAG matrix set from Michael Monagan, Simon Fraser Univ., Canada \nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nStrongly Connected Graph Components and Computing \nCharacteristic Polynomials of Integer Matrices in Maple, \nSimon Lo, Michael Monagan, Allan Wittkopf \n{sclo,mmonagan,wittkopf} at cecm.sfu.ca \nCentre for Experimental and Constructive Mathematics, \nDepartment of Mathematics, Simon Fraser University, \nBurnaby, B.C., V5A 1S6, Canada. \n \nabstract: \nLet A be an n x n matrix of integers. We present details of our Maple \nimplementation of a simple modular method for computing the \ncharacteristic polynomial of A. We consider several different \nrepresentations for the computation modulo primes, in particular, the \nuse of double precision floats. The algorithm used in Maple releases \n7-10 is the Berkowitz algorithm. We present some timings comparing the \ntwo algorithms on a sequence of matrices arising from an application in\ncombinatorics of Jocelyn Quaintance. These matrices have a hidden block\nstructure. Once identified, we can further reduce the computing time \ndramatically. This work has been incorporated into Maple 11's \nLinearAlgebra package. \n \nhttp://www.cecm.sfu.ca/~monaganm/papers/CP8.pdf \n \nFilename in JGD collection: CAG/mat364.sms \n | |
| 1943`JGD_CAG`CAG_mat72`72`72`1012`yes`72`6`6`0`56%`33%`integer`unsymmetric`no`no`M. Monagan`J.-G. Dumas`2008`combinatorial problem`\nCAG matrix set from Michael Monagan, Simon Fraser Univ., Canada \nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection, \nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nStrongly Connected Graph Components and Computing \nCharacteristic Polynomials of Integer Matrices in Maple, \nSimon Lo, Michael Monagan, Allan Wittkopf \n{sclo,mmonagan,wittkopf} at cecm.sfu.ca \nCentre for Experimental and Constructive Mathematics, \nDepartment of Mathematics, Simon Fraser University, \nBurnaby, B.C., V5A 1S6, Canada. \n \nabstract: \nLet A be an n x n matrix of integers. We present details of our Maple \nimplementation of a simple modular method for computing the \ncharacteristic polynomial of A. We consider several different \nrepresentations for the computation modulo primes, in particular, the \nuse of double precision floats. The algorithm used in Maple releases \n7-10 is the Berkowitz algorithm. We present some timings comparing the \ntwo algorithms on a sequence of matrices arising from an application in\ncombinatorics of Jocelyn Quaintance. These matrices have a hidden block\nstructure. Once identified, we can further reduce the computing time \ndramatically. This work has been incorporated into Maple 11's \nLinearAlgebra package. \n \nhttp://www.cecm.sfu.ca/~monaganm/papers/CP8.pdf \n \nFilename in JGD collection: CAG/mat72.sms \n | |
| 1944`JGD_Forest`TF10`99`107`622`yes`99`1`2`0`0%`0%`integer`rectangular`no`no`N. Thiery`J.-G. Dumas`2008`combinatorial problem`\nForests and Trees from Nicolas Thiery \nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection,\nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nTF10 : rank = 99 , 0.0263529 s, Gauss: 0.00382595 \nTF11 : rank = 216 , 0.136469 s, Gauss: 0.0256469 \nTF12 : rank = 488 , 0.83511 s, Gauss: 0.295295 \nTF13 : rank = 1121 , 6.06873 s, Gauss: 4.97585 \nTF14 : rank = 2644 , 36.9781 s, Gauss: 81.5788 \nTF15 : rank = 6334 , 229.029 s, Gauss: 1309.48 \nTF16 : rank = 15437 , 1442.08 s, Gauss: 36000 \nTF17 : rank = 38132 , 9706.03 s, Gauss: \n \nhttp://www.lapcs.univ-lyon1.fr/~nthiery \n \nFilename in JGD collection: Forest/TF10.txt2 \n | |
| 1945`JGD_Forest`TF11`216`236`1607`yes`216`1`2`0`0%`0%`integer`rectangular`no`no`N. Thiery`J.-G. Dumas`2008`combinatorial problem`\nForests and Trees from Nicolas Thiery \nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection,\nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nTF10 : rank = 99 , 0.0263529 s, Gauss: 0.00382595 \nTF11 : rank = 216 , 0.136469 s, Gauss: 0.0256469 \nTF12 : rank = 488 , 0.83511 s, Gauss: 0.295295 \nTF13 : rank = 1121 , 6.06873 s, Gauss: 4.97585 \nTF14 : rank = 2644 , 36.9781 s, Gauss: 81.5788 \nTF15 : rank = 6334 , 229.029 s, Gauss: 1309.48 \nTF16 : rank = 15437 , 1442.08 s, Gauss: 36000 \nTF17 : rank = 38132 , 9706.03 s, Gauss: \n \nhttp://www.lapcs.univ-lyon1.fr/~nthiery \n \nFilename in JGD collection: Forest/TF11.txt2 \n | |
| 1946`JGD_Forest`TF12`488`552`4231`yes`488`1`2`0`0%`0%`integer`rectangular`no`no`N. Thiery`J.-G. Dumas`2008`combinatorial problem`\nForests and Trees from Nicolas Thiery \nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection,\nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nTF10 : rank = 99 , 0.0263529 s, Gauss: 0.00382595 \nTF11 : rank = 216 , 0.136469 s, Gauss: 0.0256469 \nTF12 : rank = 488 , 0.83511 s, Gauss: 0.295295 \nTF13 : rank = 1121 , 6.06873 s, Gauss: 4.97585 \nTF14 : rank = 2644 , 36.9781 s, Gauss: 81.5788 \nTF15 : rank = 6334 , 229.029 s, Gauss: 1309.48 \nTF16 : rank = 15437 , 1442.08 s, Gauss: 36000 \nTF17 : rank = 38132 , 9706.03 s, Gauss: \n \nhttp://www.lapcs.univ-lyon1.fr/~nthiery \n \nFilename in JGD collection: Forest/TF12.txt2 \n | |
| 1947`JGD_Forest`TF13`1121`1302`11185`yes`1121`1`2`0`0%`0%`integer`rectangular`no`no`N. Thiery`J.-G. Dumas`2008`combinatorial problem`\nForests and Trees from Nicolas Thiery \nFrom Jean-Guillaume Dumas' Sparse Integer Matrix Collection,\nhttp://ljk.imag.fr/membres/Jean-Guillaume.Dumas/simc.html \n \nTF10 : rank = 99 , 0.0263529 s, Gauss: 0.00382595 \nTF11 : rank = 216 , 0.136469 s, Gauss: 0.0256469 \nTF12 : rank = 488 , 0.83511 s, Gauss: 0.295295 \nTF13 : rank = 1121 , 6.06873 s, Gauss: 4.97585 \nTF14 : rank = 2644 , 36.9781 s, Gauss: 81.5788 \nTF15 : rank = 6334 , 229.029 s, Gauss: 1309.48 \nTF16 : rank = 15437 , 1442.08 s, Gauss: 36000 \nTF17 : rank = 38132 , 9706.03 s, Gauss: \n |
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