test/mip_test.cc
author Peter Kovacs <kpeter@inf.elte.hu>
Fri, 13 Nov 2009 00:24:39 +0100
changeset 819 d93490b861e9
parent 631 d21b38647e53
permissions -rw-r--r--
Adds tests for the new MCF algorithms (#180)
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/* -*- mode: C++; indent-tabs-mode: nil; -*-
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 *
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 * This file is a part of LEMON, a generic C++ optimization library.
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 *
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 * Copyright (C) 2003-2009
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 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
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 * (Egervary Research Group on Combinatorial Optimization, EGRES).
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 *
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 * Permission to use, modify and distribute this software is granted
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 * provided that this copyright notice appears in all copies. For
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 * precise terms see the accompanying LICENSE file.
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 *
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 * This software is provided "AS IS" with no warranty of any kind,
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 * express or implied, and with no claim as to its suitability for any
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 * purpose.
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 *
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 */
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#include "test_tools.h"
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#include <lemon/config.h>
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#ifdef LEMON_HAVE_CPLEX
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#include <lemon/cplex.h>
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#endif
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#ifdef LEMON_HAVE_GLPK
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#include <lemon/glpk.h>
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#endif
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#ifdef LEMON_HAVE_CBC
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#include <lemon/cbc.h>
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#endif
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using namespace lemon;
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void solveAndCheck(MipSolver& mip, MipSolver::ProblemType stat,
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                   double exp_opt) {
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  using std::string;
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  mip.solve();
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  //int decimal,sign;
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  std::ostringstream buf;
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  buf << "Type should be: " << int(stat)<<" and it is "<<int(mip.type());
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  //  itoa(stat,buf1, 10);
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  check(mip.type()==stat, buf.str());
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  if (stat ==  MipSolver::OPTIMAL) {
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    std::ostringstream sbuf;
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    sbuf << "Wrong optimal value ("<< mip.solValue()
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         <<" instead of " << exp_opt << ")";
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    check(std::abs(mip.solValue()-exp_opt) < 1e-3, sbuf.str());
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    //+ecvt(exp_opt,2)
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  }
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}
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void aTest(MipSolver& mip)
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{
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  //The following example is very simple
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  typedef MipSolver::Row Row;
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  typedef MipSolver::Col Col;
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  Col x1 = mip.addCol();
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  Col x2 = mip.addCol();
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  //Objective function
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  mip.obj(x1);
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  mip.max();
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  //Unconstrained optimization
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  mip.solve();
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  //Check it out!
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  //Constraints
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  mip.addRow(2 * x1 + x2 <= 2);
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  Row y2 = mip.addRow(x1 - 2 * x2 <= 0);
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  //Nonnegativity of the variable x1
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  mip.colLowerBound(x1, 0);
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  //Maximization of x1
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  //over the triangle with vertices (0,0),(4/5,2/5),(0,2)
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  double expected_opt=4.0/5.0;
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  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);
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  //Restrict x2 to integer
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  mip.colType(x2,MipSolver::INTEGER);
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  expected_opt=1.0/2.0;
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  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);
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  //Restrict both to integer
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  mip.colType(x1,MipSolver::INTEGER);
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  expected_opt=0;
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  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);
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  //Erase a variable
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  mip.erase(x2);
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  mip.rowUpperBound(y2, 8);
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  expected_opt=1;
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  solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt);
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}
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template<class MIP>
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void cloneTest()
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{
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  MIP* mip = new MIP();
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  MIP* mipnew = mip->newSolver();
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  MIP* mipclone = mip->cloneSolver();
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  delete mip;
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  delete mipnew;
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  delete mipclone;
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}
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int main()
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{
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#ifdef LEMON_HAVE_GLPK
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  {
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    GlpkMip mip1;
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    aTest(mip1);
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    cloneTest<GlpkMip>();
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  }
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#endif
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#ifdef LEMON_HAVE_CPLEX
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  try {
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    CplexMip mip2;
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    aTest(mip2);
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    cloneTest<CplexMip>();
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  } catch (CplexEnv::LicenseError& error) {
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    check(false, error.what());
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  }
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#endif
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#ifdef LEMON_HAVE_CBC
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  {
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    CbcMip mip1;
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    aTest(mip1);
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    cloneTest<CbcMip>();
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  }
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#endif
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  return 0;
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}