3 * This file is a part of LEMON, a generic C++ optimization library
5 * Copyright (C) 2003-2006
6 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
7 * (Egervary Research Group on Combinatorial Optimization, EGRES).
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.
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
19 #ifndef LEMON_MIP_CPLEX_CC
20 #define LEMON_MIP_CPLEX_CC
23 ///\brief Implementation of the LEMON-CPLEX mip solver interface.
25 #include <lemon/mip_cplex.h>
29 MipCplex::MipCplex() {
30 //This is unnecessary: setting integrality constraints on
31 //variables will set this, too
33 ///\todo The constant CPXPROB_MIP is
34 ///called CPXPROB_MILP in later versions
36 CPXchgprobtype( env, lp, CPXPROB_MIP);
38 CPXchgprobtype( env, lp, CPXPROB_MILP);
43 void MipCplex::_colType(int i, MipCplex::ColTypes col_type){
45 // Note If a variable is to be changed to binary, a call to CPXchgbds
46 // should also be made to change the bounds to 0 and 1.
53 ctype[0]=CPX_INTEGER;//'I'
56 ctype[0]=CPX_CONTINUOUS ;//'C'
61 CPXchgctype (env, lp, 1, indices, ctype);
64 MipCplex::ColTypes MipCplex::_colType(int i){
67 status = CPXgetctype (env, lp, ctype, i, i);
80 LpCplex::SolveExitStatus MipCplex::_solve(){
82 status = CPXmipopt (env, lp);
91 LpCplex::SolutionStatus MipCplex::_getMipStatus(){
93 int stat = CPXgetstat(env, lp);
95 //Fortunately, MIP statuses did not change for cplex 8.0
100 //This also exists in later issues
101 // case CPXMIP_UNBOUNDED:
103 case CPXMIP_INFEASIBLE:
108 //Unboundedness not treated well: the following is from cplex 9.0 doc
109 // About Unboundedness
111 // The treatment of models that are unbounded involves a few
112 // subtleties. Specifically, a declaration of unboundedness means that
113 // ILOG CPLEX has determined that the model has an unbounded
114 // ray. Given any feasible solution x with objective z, a multiple of
115 // the unbounded ray can be added to x to give a feasible solution
116 // with objective z-1 (or z+1 for maximization models). Thus, if a
117 // feasible solution exists, then the optimal objective is
118 // unbounded. Note that ILOG CPLEX has not necessarily concluded that
119 // a feasible solution exists. Users can call the routine CPXsolninfo
120 // to determine whether ILOG CPLEX has also concluded that the model
121 // has a feasible solution.
125 MipCplex::Value MipCplex::_getPrimal(int i){
127 CPXgetmipx(env, lp, &x, i, i);
131 MipCplex::Value MipCplex::_getPrimalValue(){
133 status = CPXgetmipobjval(env, lp, &objval);
136 } //END OF NAMESPACE LEMON
138 #endif //END OF MIP_CPLEX_CC