test/mip_test.cc
author deba
Tue, 21 Aug 2007 13:22:21 +0000
changeset 2463 19651a04d056
parent 2391 14a343be7a5a
child 2553 bfced05fa852
permissions -rw-r--r--
Query functions: aMatching and bMatching
Modified algorithm function interfaces
ANodeMap<UEdge> matching map
BNodeMap<bool> barrier map

Consistency between augmenting path and push-relabel algorithm
     1 /* -*- C++ -*-
     2  *
     3  * This file is a part of LEMON, a generic C++ optimization library
     4  *
     5  * Copyright (C) 2003-2007
     6  * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
     7  * (Egervary Research Group on Combinatorial Optimization, EGRES).
     8  *
     9  * Permission to use, modify and distribute this software is granted
    10  * provided that this copyright notice appears in all copies. For
    11  * precise terms see the accompanying LICENSE file.
    12  *
    13  * This software is provided "AS IS" with no warranty of any kind,
    14  * express or implied, and with no claim as to its suitability for any
    15  * purpose.
    16  *
    17  */
    18 
    19 #include "test_tools.h"
    20 
    21 
    22 #ifdef HAVE_CONFIG_H
    23 #include <config.h>
    24 #endif
    25 
    26 #ifdef HAVE_CPLEX
    27 #include <lemon/mip_cplex.h>
    28 #endif
    29 
    30 #ifdef HAVE_GLPK
    31 #include <lemon/mip_glpk.h>
    32 #endif
    33 
    34 
    35 using namespace lemon;
    36 
    37 void solveAndCheck(MipSolverBase& lp, MipSolverBase::SolutionStatus stat, 
    38 		   double exp_opt) {
    39   using std::string;
    40 
    41   lp.solve();
    42   //int decimal,sign;
    43   std::ostringstream buf;
    44   buf << "Primalstatus should be: " << int(stat)<<" and it is "<<int(lp.mipStatus());
    45 
    46 
    47   //  itoa(stat,buf1, 10);
    48   check(lp.mipStatus()==stat, buf.str());
    49 
    50   if (stat ==  MipSolverBase::OPTIMAL) {
    51     std::ostringstream sbuf;
    52     buf << "Wrong optimal value: the right optimum is " << exp_opt; 
    53     check(std::abs(lp.primalValue()-exp_opt) < 1e-3, sbuf.str());
    54     //+ecvt(exp_opt,2)
    55   }
    56 }
    57 
    58 void aTest(MipSolverBase& mip)
    59 {
    60  //The following example is very simple
    61 
    62 
    63   typedef MipSolverBase::Row Row;
    64   typedef MipSolverBase::Col Col;
    65 
    66 
    67 
    68   Col x1 = mip.addCol();
    69   Col x2 = mip.addCol();
    70 
    71 
    72   //Objective function
    73   mip.obj(x1);
    74 
    75   mip.max();
    76 
    77 
    78   //Unconstrained optimization
    79   mip.solve();
    80   //Check it out!
    81 
    82   //Constraints
    83   mip.addRow(2*x1+x2 <=2);  
    84   mip.addRow(x1-2*x2 <=0);
    85 
    86   //Nonnegativity of the variable x1
    87   mip.colLowerBound(x1, 0);
    88 
    89   //Maximization of x1
    90   //over the triangle with vertices (0,0),(4/5,2/5),(0,2)
    91   double expected_opt=4.0/5.0;
    92   solveAndCheck(mip, MipSolverBase::OPTIMAL, expected_opt);
    93 
    94   //Restrict x2 to integer
    95   mip.colType(x2,MipSolverBase::INT);  
    96   expected_opt=1.0/2.0;
    97   solveAndCheck(mip, MipSolverBase::OPTIMAL, expected_opt);
    98 
    99 
   100   //Restrict both to integer
   101   mip.colType(x1,MipSolverBase::INT);  
   102   expected_opt=0;
   103   solveAndCheck(mip, MipSolverBase::OPTIMAL, expected_opt);
   104 
   105  
   106 
   107 }
   108 
   109 
   110 int main() 
   111 {
   112 
   113 #ifdef HAVE_GLPK
   114   MipGlpk mip1;
   115   aTest(mip1);
   116 #endif
   117 
   118 #ifdef HAVE_CPLEX
   119   MipCplex mip2;
   120   aTest(mip2);
   121 #endif
   122 
   123   return 0;
   124 
   125 }