wk-11a-Fall 2016-pulp-example

wk-11a-Fall 2016-pulp-example.ipynb

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   "source": [
    "import pulp as plp"
   ]
  },
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   "execution_count": null,
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   "outputs": [],
   "source": [
    "# Testing the module\n",
    "# plp.puplTestAll()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "# A new LP problem\n",
    "myProblem = plp.LpProblem(\"Shader\", plp.LpMaximize)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "# Define decision variables\n",
    "x = plp.LpVariable(\"x\", 0)\n",
    "y = plp.LpVariable(\"y\", 0)\n",
    " \n",
    "# Define objective function\n",
    "myProblem += 7*x + 5*y, \"obj\"\n",
    "\n",
    "# define constraints\n",
    "myProblem += 4*x + 3*y <= 240, \"c1\"\n",
    "myProblem += 2*x + 1*y <= 100, \"c2\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "# Save and solve the problem\n",
    "myProblem.writeLP(\"Shader.lp\")\n",
    "# myProblem.solve()              # This will work too because it will use COIN solver\n",
    "myProblem.solve(plp.GLPK())      # This uses GLPK solver\n",
    "print (\"Status:\", plp.LpStatus[myProblem.status])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Print the results\n",
    "for v in myProblem.variables():\n",
    "    print (v.name, \"=\", v.varValue)\n",
    "print (\"objective =\", plp.value(myProblem.objective))\n",
    "print (\"\\nSensitivity Analysis\\nConstraint\\t\\tShadow Price\\tSlack\")\n",
    "for name, c in myProblem.constraints.items():\n",
    "    print (name, \":\", c, \"\\t\", c.pi, \"\\t\\t\", c.slack)"
   ]
  }
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