OptSolutionData* CPLEXRunSolver(int ProbType) {
OptSolutionData* NewSolution = NULL;
int Status = 0;
if (ProbType == LP) {
Status = CPXsetintparam (CPLEXenv, CPX_PARAM_LPMETHOD, CPX_ALG_AUTOMATIC);
if (Status) {
FErrorFile() << "Failed to set the optimization method." << endl;
FlushErrorFile();
return NULL;
}
Status = CPXsetintparam (CPLEXenv, CPX_PARAM_SIMDISPLAY, 0);
if (Status) {
FErrorFile() << "Failed to set the optimization method." << endl;
FlushErrorFile();
return NULL;
}
Status = CPXchgprobtype(CPLEXenv, CPLEXModel, CPXPROB_LP);
Status = CPXlpopt(CPLEXenv, CPLEXModel);
} else if(ProbType == MILP || ProbType == MIQP) {
//Setting the bound tightening on high
Status = CPXsetintparam (CPLEXenv, CPX_PARAM_BNDSTRENIND, 1);
if (Status) {
FErrorFile() << "Failed to set the optimization method." << endl;
FlushErrorFile();
return NULL;
}
//Setting tolerance to 1e-9 instead of 1e-6
double tolerance = atof(GetParameter("Solver tolerance").data());
Status = CPXsetdblparam(CPLEXenv,CPX_PARAM_EPRHS, 1e-9);
if (Status) {
FErrorFile() << "Failed to set the optimization method." << endl;
FlushErrorFile();
return NULL;
}
Status = CPXsetdblparam(CPLEXenv,CPX_PARAM_EPINT, 1e-9);
if (Status) {
FErrorFile() << "Failed to set the optimization method." << endl;
FlushErrorFile();
return NULL;
}
//Deactivates all messages from MIP solver
if (ProbType == MIQP) {
Status = CPXchgprobtype(CPLEXenv, CPLEXModel, CPXPROB_MIQP);
} else {
Status = CPXchgprobtype(CPLEXenv, CPLEXModel, CPXPROB_MILP);
}
Status = CPXmipopt (CPLEXenv, CPLEXModel);
} else if(ProbType == QP) {
Status = CPXchgprobtype(CPLEXenv, CPLEXModel, CPXPROB_QP);
Status = CPXqpopt (CPLEXenv, CPLEXModel);
}
if (Status ) {
cout << "Failed to optimize LP." << endl;
return NULL;
}
int Temp = CPXgetstat (CPLEXenv, CPLEXModel);
NewSolution = new OptSolutionData;
if (Temp == CPX_STAT_UNBOUNDED) {
cout << "Model is unbounded" << endl;
FErrorFile() << "Model is unbounded" << endl;
FlushErrorFile();
NewSolution->Status = UNBOUNDED;
return NewSolution;
} else if (Temp == CPX_STAT_INFEASIBLE) {
cout << "Model is infeasible" << endl;
FErrorFile() << "Model is infeasible" << endl;
FlushErrorFile();
NewSolution->Status = INFEASIBLE;
return NewSolution;
} else if (Temp == CPX_STAT_INForUNBD ) {
cout << "Model is infeasible or unbounded" << endl;
FErrorFile() << "Model is infeasible or unbounded" << endl;
FlushErrorFile();
NewSolution->Status = INFEASIBLE;
return NewSolution;
} else {
NewSolution->Status = SUCCESS;
}
int NumberColumns = CPXgetnumcols (CPLEXenv, CPLEXModel);
int NumberRows = CPXgetnumrows (CPLEXenv, CPLEXModel);
NewSolution->NumVariables = NumberColumns;
NewSolution->SolutionData.resize(NumberColumns);
double* x = new double[NumberColumns];
if (ProbType == MILP || ProbType == MIQP) {
Status = CPXgetmipobjval (CPLEXenv, CPLEXModel, &(NewSolution->Objective));
Status = CPXgetmipx (CPLEXenv, CPLEXModel, x, 0, NumberColumns-1);
} else {
Status = CPXsolution(CPLEXenv,CPLEXModel,NULL,&(NewSolution->Objective),x,NULL,NULL,NULL);
}
if ( Status ) {
cout << "Failed to obtain objective value." << endl;
delete [] x;
NewSolution->Status = INFEASIBLE;
return NewSolution;
}
cout << "Objective value: " << NewSolution->Objective << endl;
/*
string* StrNames = new string[NumberColumns];
char** Names = new char*[NumberColumns];
char* NameStore = new char[7*NumberColumns];
int Surplus = 0;
Status = CPXgetcolname(CPLEXenv, CPLEXModel, Names, NameStore, 7*NumberColumns, &Surplus, 0, NumberColumns-1);
if (Status) {
FErrorFile() << "Failed to get column names." << endl;
FlushErrorFile();
delete [] StrNames;
delete [] Names;
delete [] NameStore;
delete [] x;
delete NewSolution;
return NULL;
}
*/
for (int i=0; i < NumberColumns; i++) {
//StrNames[i].assign(Names[i]);
//StrNames[i] = StrNames[i].substr(1, StrNames[i].length()-1);
//NewSolution->SolutionData[atoi(StrNames[i].data())-1] = x[i];
NewSolution->SolutionData[i] = x[i];
}
/*
delete [] StrNames;
delete [] Names;
delete [] NameStore;
*/
delete [] x;
return NewSolution;
}
int CPLEXLoadVariables(MFAVariable* InVariable, bool RelaxIntegerVariables,bool UseTightBounds) {
int Status = 0;
//First I check the number of columns. If it's larger than the index, then this variable already exists and is only being changed
int NumberColumns = CPXgetnumcols (CPLEXenv, CPLEXModel);
if (NumberColumns <= InVariable->Index) {
string StrName = GetMFAVariableName(InVariable);
double* LB = new double;
LB[0] = InVariable->LowerBound;
double* UB = new double;
UB[0] = InVariable->UpperBound;
if (UseTightBounds) {
LB[0] = InVariable->Min;
UB[0] = InVariable->Max;
}
double* Obj = new double;
Obj[0] = 0;
char* Temp = new char;
char** Name = new char*;
Name[0] = new char[StrName.length()+1];
strcpy(Name[0],StrName.data());
if (InVariable->Binary && !RelaxIntegerVariables) {
Temp[0] = CPX_BINARY;
Status = CPXnewcols (CPLEXenv, CPLEXModel, 1, Obj, LB, UB, Temp, Name);
} else if (InVariable->Integer && !RelaxIntegerVariables) {
Temp[0] = CPX_INTEGER;
Status = CPXnewcols (CPLEXenv, CPLEXModel, 1, Obj, LB, UB, Temp, Name);
} else {
Temp[0] = CPX_CONTINUOUS;
Status = CPXnewcols (CPLEXenv, CPLEXModel, 1, Obj, LB, UB, Temp, Name);
}
delete LB;
delete UB;
delete Obj;
delete Temp;
delete [] Name[0];
delete Name;
if (Status ) {
FErrorFile() << "Could not add variable " << InVariable->Index << endl;
FlushErrorFile();
return FAIL;
}
} else {
double* Bounds = new double[2];
Bounds[0] = InVariable->LowerBound;
Bounds[1] = InVariable->UpperBound;
int* Indices = new int[2];
Indices[0] = InVariable->Index;
Indices[1] = InVariable->Index;
Status = CPXchgbds (CPLEXenv, CPLEXModel, 2, Indices, "LU", Bounds);
delete [] Bounds;
delete [] Indices;
if (Status) {
FErrorFile() << "Could not change bounds on variable " << InVariable->Index << endl;
FlushErrorFile();
return FAIL;
}
}
return SUCCESS;
}
OptSolutionData* GLPKRunSolver(int ProbType) {
OptSolutionData* NewSolution = NULL;
int NumVariables = lpx_get_num_cols(GLPKModel);
int Status = 0;
if (ProbType == MILP) {
Status = lpx_simplex(GLPKModel);
if (Status != LPX_E_OK) {
FErrorFile() << "Failed to optimize problem." << endl;
FlushErrorFile();
return NULL;
}
Status = lpx_integer(GLPKModel);
if (Status != LPX_E_OK) {
FErrorFile() << "Failed to optimize problem." << endl;
FlushErrorFile();
return NULL;
}
NewSolution = new OptSolutionData;
Status = lpx_mip_status(GLPKModel);
if (Status == LPX_I_UNDEF || Status == LPX_I_NOFEAS) {
NewSolution->Status = INFEASIBLE;
return NewSolution;
} else if (Status == LPX_I_FEAS) {
NewSolution->Status = UNBOUNDED;
return NewSolution;
} else if (Status == LPX_I_OPT) {
NewSolution->Status = SUCCESS;
} else {
delete NewSolution;
FErrorFile() << "Problem status unrecognized." << endl;
FlushErrorFile();
return NULL;
}
NewSolution->Objective = lpx_mip_obj_val(GLPKModel);
NewSolution->SolutionData.resize(NumVariables);
for (int i=0; i < NumVariables; i++) {
NewSolution->SolutionData[i] = lpx_mip_col_val(GLPKModel, i+1);
}
} else if (ProbType == LP) {
//First we check the basis matrix to ensure it is not sigular
if (lpx_warm_up(GLPKModel) != LPX_E_OK) {
lpx_adv_basis(GLPKModel);
}
Status = lpx_simplex(GLPKModel);
if (Status == LPX_E_FAULT) {
Status = lpx_warm_up(GLPKModel);
if (Status == LPX_E_BADB) { /* the basis is invalid; build some valid basis */
lpx_adv_basis(GLPKModel);
Status = lpx_simplex(GLPKModel);
}
}
if (Status != LPX_E_OK) {
FErrorFile() << "Failed to optimize problem." << endl;
FlushErrorFile();
return NULL;
}
NewSolution = new OptSolutionData;
Status = lpx_get_status(GLPKModel);
if (Status == LPX_INFEAS || Status == LPX_NOFEAS || Status == LPX_UNDEF) {
cout << "Model is infeasible" << endl;
FErrorFile() << "Model is infeasible" << endl;
FlushErrorFile();
NewSolution->Status = INFEASIBLE;
return NewSolution;
} else if (Status == LPX_FEAS || Status == LPX_UNBND) {
cout << "Model is unbounded" << endl;
FErrorFile() << "Model is unbounded" << endl;
FlushErrorFile();
NewSolution->Status = UNBOUNDED;
return NewSolution;
} else if (Status == LPX_OPT) {
NewSolution->Status = SUCCESS;
} else {
delete NewSolution;
FErrorFile() << "Problem status unrecognized." << endl;
FlushErrorFile();
return NULL;
}
NewSolution->Objective = lpx_get_obj_val(GLPKModel);
NewSolution->SolutionData.resize(NumVariables);
for (int i=0; i < NumVariables; i++) {
NewSolution->SolutionData[i] = lpx_get_col_prim(GLPKModel, i+1);
}
} else {
FErrorFile() << "Optimization problem type cannot be handled by GLPK solver." << endl;
FlushErrorFile();
return NULL;
}
return NewSolution;
}