modifications of examples/cplusplus/ipopt_nl.cpp

gistfile1.cpp

/*
 *    This file is part of CasADi.
 *
 *    CasADi -- A symbolic framework for dynamic optimization.
 *    Copyright (C) 2010 by Joel Andersson, Moritz Diehl, K.U.Leuven. All rights reserved.
 *
 *    CasADi is free software; you can redistribute it and/or
 *    modify it under the terms of the GNU Lesser General Public
 *    License as published by the Free Software Foundation; either
 *    version 3 of the License, or (at your option) any later version.
 *
 *    CasADi is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 *    Lesser General Public License for more details.
 *
 *    You should have received a copy of the GNU Lesser General Public
 *    License along with CasADi; if not, write to the Free Software
 *    Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
 *
 */
#include <symbolic/casadi.hpp>
#include <interfaces/ipopt/ipopt_solver.hpp>
#include <nonlinear_programming/sqp_method.hpp>
#include <nonlinear_programming/nlp_qp_solver.hpp>
#include <nonlinear_programming/symbolic_nlp.hpp>

/**
 * This example demonstrates how NL-files, which can be generated
 * by AMPl or Pyomo, can be imported in CasADi and solved using
 * e.g. the interface to AMPL

 \author Joel Andersson
 \date 2012
*/


using namespace CasADi;

int main(int argc, char **argv){
  // Get the problem
  std::string problem = (argc==2) ? argv[1] : "../examples/nl_files/hs107.nl";
  
  // Parse an NL-file
  SymbolicNLP nl;
  nl.parseNL(problem);
  
  // NLP
  SXFunction nlp(nlIn("x",nl.x),nlOut("f",nl.f,"g",nl.g));

  // Allocate NLP solver
  SQPMethod nlp_solver(nlp);
    
  // Set options
  //  nlp_solver.setOption("max_iter",10);
  //  nlp_solver.setOption("verbose",true);
  //  nlp_solver.setOption("linear_solver","ma57");
  nlp_solver.setOption("hessian_mode","exact");
  //  nlp_solver.setOption("derivative_test","second-order");
  
  nlp_solver.setOption("qp_solver",NLPQPSolver::creator);
  Dictionary qp_solver_options;
  qp_solver_options["nlp_solver"] = IpoptSolver::creator;

  Dictionary nlp_solver_options;
  nlp_solver_options["print_level"] = 0;
  nlp_solver_options["print_time"] = 0;
  qp_solver_options["nlp_solver_options"] = nlp_solver_options;

  nlp_solver.setOption("qp_solver_options",qp_solver_options);

  // Initialize NLP solver
  nlp_solver.init();
  
  // Pass the bounds and initial guess
  nlp_solver.setInput(nl.x_lb,"lbx");
  nlp_solver.setInput(nl.x_ub,"ubx");
  nlp_solver.setInput(nl.g_lb,"lbg");
  nlp_solver.setInput(nl.g_ub,"ubg");
  nlp_solver.setInput(nl.x_init,"x0");
  
  // Solve NLP
  nlp_solver.solve();
  
  return 0;
}