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kpeter (Peter Kovacs)
Use XTI implementation instead of ATI in NetworkSimplex (#234) XTI (eXtended Threaded Index) is an imporved version of the widely known ATI (Augmented Threaded Index) method for storing and updating the spanning tree structure in Network Simplex algorithms. In the ATI data structure three indices are stored for each node: predecessor, thread and depth. In the XTI data structure depth is replaced by the number of successors and the last successor (according to the thread index).
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/* -*- mode: C++; indent-tabs-mode: nil; -*-

 *

 * This file is a part of LEMON, a generic C++ optimization library.

 *

 * Copyright (C) 2003-2008

 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport

 * (Egervary Research Group on Combinatorial Optimization, EGRES).

 *

 * Permission to use, modify and distribute this software is granted

 * provided that this copyright notice appears in all copies. For

 * precise terms see the accompanying LICENSE file.

 *

 * This software is provided "AS IS" with no warranty of any kind,

 * express or implied, and with no claim as to its suitability for any

 * purpose.

 *

 */



#include "test_tools.h"





#ifdef HAVE_CONFIG_H

#include <lemon/config.h>

#endif



#ifdef HAVE_CPLEX

#include <lemon/cplex.h>

#endif



#ifdef HAVE_GLPK

#include <lemon/glpk.h>

#endif





using namespace lemon;



void solveAndCheck(MipSolver& mip, MipSolver::ProblemType stat,

                   double exp_opt) {

  using std::string;



  mip.solve();

  //int decimal,sign;

  std::ostringstream buf;

  buf << "Type should be: " << int(stat)<<" and it is "<<int(mip.type());





  //  itoa(stat,buf1, 10);

  check(mip.type()==stat, buf.str());



  if (stat ==  MipSolver::OPTIMAL) {

    std::ostringstream sbuf;

    buf << "Wrong optimal value: the right optimum is " << exp_opt;

    check(std::abs(mip.solValue()-exp_opt) < 1e-3, sbuf.str());

    //+ecvt(exp_opt,2)

  }

}



void aTest(MipSolver& mip)

{

 //The following example is very simple





  typedef MipSolver::Row Row;

  typedef MipSolver::Col Col;







  Col x1 = mip.addCol();

  Col x2 = mip.addCol();





  //Objective function

  mip.obj(x1);



  mip.max();





  //Unconstrained optimization

  mip.solve();

  //Check it out!



  //Constraints

  mip.addRow(2*x1+x2 <=2);

  mip.addRow(x1-2*x2 <=0);



  //Nonnegativity of the variable x1

  mip.colLowerBound(x1, 0);



  //Maximization of x1

  //over the triangle with vertices (0,0),(4/5,2/5),(0,2)

  double expected_opt=4.0/5.0;

  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);



  //Restrict x2 to integer

  mip.colType(x2,MipSolver::INTEGER);

  expected_opt=1.0/2.0;

  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);





  //Restrict both to integer

  mip.colType(x1,MipSolver::INTEGER);

  expected_opt=0;

  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);







}





int main()

{



#ifdef HAVE_GLPK

  {

    GlpkMip mip1;

    aTest(mip1);

  }

#endif



#ifdef HAVE_CPLEX

  try {

    CplexMip mip2;

    aTest(mip2);

  } catch (CplexEnv::LicenseError& error) {

#ifdef LEMON_FORCE_CPLEX_CHECK

    check(false, error.what());

#else

    std::cerr << error.what() << std::endl;

    std::cerr << "Cplex license check failed, lp check skipped" << std::endl;

#endif

  }

#endif



  return 0;



}