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
35 CPXchgprobtype( env, lp, CPXPROB_MIP);
38 void MipCplex::_colType(int i, MipCplex::ColTypes col_type){
40 // Note If a variable is to be changed to binary, a call to CPXchgbds
41 // should also be made to change the bounds to 0 and 1.
48 ctype[0]=CPX_INTEGER;//'I'
51 ctype[0]=CPX_CONTINUOUS ;//'C'
56 CPXchgctype (env, lp, 1, indices, ctype);
59 MipCplex::ColTypes MipCplex::_colType(int i){
62 status = CPXgetctype (env, lp, ctype, i, i);
75 LpCplex::SolveExitStatus MipCplex::_solve(){
77 status = CPXmipopt (env, lp);
86 LpCplex::SolutionStatus MipCplex::_getMipStatus(){
88 int stat = CPXgetstat(env, lp);
90 //Fortunately, MIP statuses did not change for cplex 8.0
95 //This also exists in later issues
96 // case CPXMIP_UNBOUNDED:
98 case CPXMIP_INFEASIBLE:
103 //Unboundedness not treated well: the following is from cplex 9.0 doc
104 // About Unboundedness
106 // The treatment of models that are unbounded involves a few
107 // subtleties. Specifically, a declaration of unboundedness means that
108 // ILOG CPLEX has determined that the model has an unbounded
109 // ray. Given any feasible solution x with objective z, a multiple of
110 // the unbounded ray can be added to x to give a feasible solution
111 // with objective z-1 (or z+1 for maximization models). Thus, if a
112 // feasible solution exists, then the optimal objective is
113 // unbounded. Note that ILOG CPLEX has not necessarily concluded that
114 // a feasible solution exists. Users can call the routine CPXsolninfo
115 // to determine whether ILOG CPLEX has also concluded that the model
116 // has a feasible solution.
120 MipCplex::Value MipCplex::_getPrimal(int i){
122 CPXgetmipx(env, lp, &x, i, i);
126 MipCplex::Value MipCplex::_getPrimalValue(){
128 status = CPXgetmipobjval(env, lp, &objval);
131 } //END OF NAMESPACE LEMON
133 #endif //END OF MIP_CPLEX_CC