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Copy pathWolseyStrengthening.cpp
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WolseyStrengthening.cpp
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#include "WolseyStrengthening.h"
#include "Global.h"
#include "OptModel.h"
#include "TwoConstrainSetCutGenerator.h"
#include "ResourceCutGenerator.h"
#include "PortfolioInstanceGenerator.h"
extern string CAT_NAME;
int WolseyStrengthening::iteration_cnt = 0;
vector<double> WolseyStrengthening::beta= vector<double>(2*DataModel::m, 0);
WolseyStrengthening::WolseyStrengthening(OptModel* _model)
{
model_p = _model;
WolseyStrengthening::beta= vector<double>(DataModel::m, 0);
timeLimit = 1/SMALL_DECIMAL;
timeElapsed = 0;
}
void WolseyStrengthening::strengthenModel(int method)
{
min_model = new OptModel(*model_p);
if (method == 3)
{
TwoConstrainSetCutGenerator cutGen(min_model);
cutGen.addAllPairFacets(OptModel::CUT_AS_FORMULATION);
}
LHS lhs = model_p->getObjective();
RHS rhs = model_p->LP_optimal_value;
CUT cut(lhs,rhs);
string cutName = "objcut";
min_model->addAConstToCPXModel(cut, cutName, 0);
int num_rows = model_p->getNumRows();
int surplus;
CPXENVptr& cpxenv =model_p->getCPXEnv();
CPXLPptr& cpxlp = model_p->getCPXLP();
double lp_optimal = model_p->LP_optimal_value;
int num_cols = CPXgetnumcols(cpxenv, cpxlp);
vector< double > gs;
vector< int > list_i;
vector< int > list_j;
vector<double> list_rhs;
int status = CPXgetrowname (cpxenv, cpxlp, NULL, NULL, 0, &surplus, 0,num_rows-1);
vector<string> rowsToDelete;
vector<string> varsToDelete;
int cur_rownamespace = - surplus;
if ( cur_rownamespace > 0 )
{
char **cur_rowname = (char **) malloc (sizeof(char *)*(num_rows));
char *cur_rownamestore = (char *) malloc (cur_rownamespace);
if ( cur_rowname == NULL ||
cur_rownamestore == NULL ) {
fprintf (stderr, "Failed to get memory for column names.\n");
status = -1;
cout<< endl <<" error in reading column names"<<endl;
return;
}
status = CPXgetrowname (cpxenv, cpxlp, cur_rowname, cur_rownamestore,
cur_rownamespace, &surplus, 0, num_rows-1);
// map name with column index
for (int r = 0; r <num_rows ; r ++)
{
string rowName = cur_rowname[r];
string cpyRowName = rowName;
size_t t =rowName.find_first_of("0123456789");
if (t != string::npos)
rowName.erase(t);
if (rowName != "SN")
continue;
int nzcnt;
int * rmatbeg = new int(0);
int * rmatind = new int[num_cols]();
double * rmatval = new double[num_cols]();
int rmatspace = num_cols;
int surplus;
double rhs;
CPXgetrows(cpxenv, cpxlp, &nzcnt, rmatbeg, rmatind, rmatval, rmatspace, &surplus, r, r);
CPXgetrhs(cpxenv, cpxlp, &rhs, r, r);
int index_z = 0;
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
{
index_z = rmatind[j];
break;
}
}
double g_i ;
if (method == 0)
g_i = calculateBetaBySolvingMIP(nzcnt, rmatind, rmatval, lp_optimal); //
else if(method == 1 || method == 3 )
g_i = calculateBetaBySolvingMIP_rev1(nzcnt, rmatind, rmatval, lp_optimal);
else if(method == 2)
g_i = calculateBetaBySolvingMIP_2ConstSet(nzcnt, rmatind, rmatval, lp_optimal);
gs.push_back(g_i);
list_i.push_back(r);
list_j.push_back(index_z);
list_rhs.push_back(rhs);
if(rhs - g_i < 0)
{
rowsToDelete.push_back(cpyRowName);
map<int, string>::iterator itr = model_p->idx_var_name_table.find(index_z);
if (itr!= model_p->idx_var_name_table.end())
{
varsToDelete.push_back(itr->second);
}
}
delete rmatbeg;
delete []rmatind;
delete []rmatval;
}
free_and_null( (char **)&cur_rowname);
free_and_null((char **)&cur_rownamestore);
}
// change the coeffients
int * rowlist = new int[list_i.size()];
int * collist = new int[list_j.size()];
double * vallist = new double[gs.size()];
for (int k = 0 ; k < gs.size(); k++)
{
rowlist[k] = list_i[k];
collist[k] = list_j[k];
vallist[k] = (list_rhs[k] - gs[k])<=0 ? list_rhs[k] : list_rhs[k] - gs[k];
}
CPXchgcoeflist(cpxenv, cpxlp, gs.size(), rowlist, collist, vallist);
delete [] rowlist;
delete []collist;
delete []vallist;
for (map<int, OptModel*>::iterator itr = LBmodels.begin(); itr != LBmodels.end(); ++itr)
{
OptModel* p = itr->second;
delete p;
}
LBmodels.clear();
}
void WolseyStrengthening::strengthenModelWiTheoreticalBound()
{
int num_rows = model_p->getNumRows();
int surplus;
CPXENVptr& cpxenv =model_p->getCPXEnv();
CPXLPptr& cpxlp = model_p->getCPXLP();
double lp_optimal = model_p->LP_optimal_value;
int num_cols = CPXgetnumcols(cpxenv, cpxlp);
vector< double > gs;
vector< int > list_i;
vector< int > list_j;
vector<double> list_rhs;
int status = CPXgetrowname (cpxenv, cpxlp, NULL, NULL, 0, &surplus, 0,num_rows-1);
vector<string> rowsToDelete;
vector<string> varsToDelete;
int cur_rownamespace = - surplus;
if ( cur_rownamespace > 0 )
{
char **cur_rowname = (char **) malloc (sizeof(char *)*(num_rows));
char *cur_rownamestore = (char *) malloc (cur_rownamespace);
if ( cur_rowname == NULL ||
cur_rownamestore == NULL ) {
fprintf (stderr, "Failed to get memory for column names.\n");
status = -1;
cout<< endl <<" error in reading column names"<<endl;
return;
}
status = CPXgetrowname (cpxenv, cpxlp, cur_rowname, cur_rownamestore,
cur_rownamespace, &surplus, 0, num_rows-1);
for (int r = 0; r <num_rows ; r ++)
{
string rowName = cur_rowname[r];
string cpyRowName = rowName;
size_t t =rowName.find_first_of("0123456789");
if (t != string::npos)
rowName.erase(t);
if (rowName != "SN")
continue;
int nzcnt;
int * rmatbeg = new int(0);
int * rmatind = new int[num_cols]();
double * rmatval = new double[num_cols]();
int rmatspace = num_cols;
int surplus;
double rhs;
map<double,int> sortedRo;
CPXgetrows(cpxenv, cpxlp, &nzcnt, rmatbeg, rmatind, rmatval, rmatspace, &surplus, r, r);
CPXgetrhs(cpxenv, cpxlp, &rhs, r, r);
int index_z = 0;
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
{
index_z = rmatind[j];
break;
}
sortedRo.insert(make_pair(rmatval[j]/PortfolioInstanceGenerator::ro[j],0));
}
double g_i = sortedRo.begin()->first;
g_i = g_i*((double)(DataModel::m-DataModel::k))/(DataModel::m-g_i*DataModel::k);
gs.push_back(g_i);
list_i.push_back(r);
list_j.push_back(index_z);
list_rhs.push_back(rhs);
if(rhs - g_i < 0)
{
rowsToDelete.push_back(cpyRowName);
map<int, string>::iterator itr = model_p->idx_var_name_table.find(index_z);
if (itr!= model_p->idx_var_name_table.end())
{
varsToDelete.push_back(itr->second);
}
}
delete rmatbeg;
delete []rmatind;
delete []rmatval;
}
free_and_null( (char **)&cur_rowname);
free_and_null((char **)&cur_rownamestore);
}
// change the coeffients
int * rowlist = new int[list_i.size()];
int * collist = new int[list_j.size()];
double * vallist = new double[gs.size()];
for (int k = 0 ; k < gs.size(); k++)
{
rowlist[k] = list_i[k];
collist[k] = list_j[k];
vallist[k] = (list_rhs[k] - gs[k])<=0 ? list_rhs[k] : list_rhs[k] - gs[k];
}
CPXchgcoeflist(cpxenv, cpxlp, gs.size(), rowlist, collist, vallist);
delete [] rowlist;
delete []collist;
delete []vallist;
}
void WolseyStrengthening::strengthenModelWith2ConstSet(int method)
{
// build basic model with all 2-const set inequalities
min_model = new OptModel(*model_p);
TwoConstrainSetCutGenerator cutGen(min_model);
cutGen.addAllPairFacets(OptModel::CUT_AS_FORMULATION);
LHS lhs = model_p->getObjective();
RHS rhs = model_p->LP_optimal_value;
CUT cut(lhs,rhs);
string cutName = "objcut";
min_model->addAConstToCPXModel(cut, cutName, 0);
int num_rows = model_p->getNumRows();
int surplus;
CPXENVptr& cpxenv =model_p->getCPXEnv();
CPXLPptr& cpxlp = model_p->getCPXLP();
double lp_optimal = model_p->LP_optimal_value;
int num_cols = CPXgetnumcols(cpxenv, cpxlp);
vector< double > gs;
vector< int > list_i;
vector< int > list_j;
vector<double> list_rhs;
int status = CPXgetrowname (cpxenv, cpxlp, NULL, NULL, 0, &surplus, 0,num_rows-1);
vector<string> rowsToDelete;
vector<string> varsToDelete;
int cur_rownamespace = - surplus;
if ( cur_rownamespace > 0 )
{
char **cur_rowname = (char **) malloc (sizeof(char *)*(num_rows));
char *cur_rownamestore = (char *) malloc (cur_rownamespace);
if ( cur_rowname == NULL ||
cur_rownamestore == NULL ) {
fprintf (stderr, "Failed to get memory for column names.\n");
status = -1;
cout<< endl <<" error in reading column names"<<endl;
return;
}
status = CPXgetrowname (cpxenv, cpxlp, cur_rowname, cur_rownamestore,
cur_rownamespace, &surplus, 0, num_rows-1);
// map name with column index
for (int r = 0; r <num_rows ; r ++)
{
string rowName = cur_rowname[r];
string cpyRowName = rowName;
size_t t =rowName.find_first_of("0123456789");
if (t != string::npos)
rowName.erase(t);
if (rowName != "SN")
continue;
int nzcnt;
int * rmatbeg = new int(0);
int * rmatind = new int[num_cols]();
double * rmatval = new double[num_cols]();
int rmatspace = num_cols;
int surplus;
double rhs;
CPXgetrows(cpxenv, cpxlp, &nzcnt, rmatbeg, rmatind, rmatval, rmatspace, &surplus, r, r);
CPXgetrhs(cpxenv, cpxlp, &rhs, r, r);
int index_z = 0;
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
{
index_z = rmatind[j];
break;
}
}
double g_i ;
if (method == 0)
g_i = calculateBetaBySolvingMIP(nzcnt, rmatind, rmatval, lp_optimal); //
else if(method == 1)
g_i = calculateBetaBySolvingMIP_rev1(nzcnt, rmatind, rmatval, lp_optimal);
else if(method == 2)
g_i = calculateBetaBySolvingMIP_2ConstSet(nzcnt, rmatind, rmatval, lp_optimal);
gs.push_back(g_i);
list_i.push_back(r);
list_j.push_back(index_z);
list_rhs.push_back(rhs);
if(rhs - g_i < 0)
{
rowsToDelete.push_back(cpyRowName);
map<int, string>::iterator itr = model_p->idx_var_name_table.find(index_z);
if (itr!= model_p->idx_var_name_table.end())
{
varsToDelete.push_back(itr->second);
}
}
delete rmatbeg;
delete []rmatind;
delete []rmatval;
}
free_and_null( (char **)&cur_rowname);
free_and_null((char **)&cur_rownamestore);
}
// change the coeffients
int * rowlist = new int[list_i.size()];
int * collist = new int[list_j.size()];
double * vallist = new double[gs.size()];
for (int k = 0 ; k < gs.size(); k++)
{
rowlist[k] = list_i[k];
collist[k] = list_j[k];
vallist[k] = (list_rhs[k] - gs[k])<=0 ? list_rhs[k] : list_rhs[k] - gs[k];
}
CPXchgcoeflist(cpxenv, cpxlp, gs.size(), rowlist, collist, vallist);
delete [] rowlist;
delete []collist;
delete []vallist;
for (map<int, OptModel*>::iterator itr = LBmodels.begin(); itr != LBmodels.end(); ++itr)
{
OptModel* p = itr->second;
delete p;
}
delete min_model;
}
void WolseyStrengthening::strengthenModelWithResourceCut(int method)
{
// build basic model with all 2-const set inequalities
min_model = new OptModel(*model_p);
ResourceCutGenerator cutGen(min_model);
cutGen.addAllScenarioCuts();
LHS lhs = model_p->getObjective();
RHS rhs = model_p->LP_optimal_value;
CUT cut(lhs,rhs);
string cutName = "objcut";
min_model->addAConstToCPXModel(cut, cutName, 0);
int num_rows = model_p->getNumRows();
int surplus;
CPXENVptr& cpxenv =model_p->getCPXEnv();
CPXLPptr& cpxlp = model_p->getCPXLP();
double lp_optimal = model_p->LP_optimal_value;
int num_cols = CPXgetnumcols(cpxenv, cpxlp);
vector< double > gs;
vector< int > list_i;
vector< int > list_j;
vector<double> list_rhs;
int status = CPXgetrowname (cpxenv, cpxlp, NULL, NULL, 0, &surplus, 0,num_rows-1);
vector<string> rowsToDelete;
vector<string> varsToDelete;
int cur_rownamespace = - surplus;
if ( cur_rownamespace > 0 )
{
char **cur_rowname = (char **) malloc (sizeof(char *)*(num_rows));
char *cur_rownamestore = (char *) malloc (cur_rownamespace);
if ( cur_rowname == NULL ||
cur_rownamestore == NULL ) {
fprintf (stderr, "Failed to get memory for column names.\n");
status = -1;
cout<< endl <<" error in reading column names"<<endl;
return;
}
status = CPXgetrowname (cpxenv, cpxlp, cur_rowname, cur_rownamestore,
cur_rownamespace, &surplus, 0, num_rows-1);
// map name with column index
for (int r = 0; r <num_rows ; r ++)
{
string rowName = cur_rowname[r];
string cpyRowName = rowName;
size_t t =rowName.find_first_of("0123456789");
if (t != string::npos)
rowName.erase(t);
if (rowName != "SN")
continue;
int nzcnt;
int * rmatbeg = new int(0);
int * rmatind = new int[num_cols]();
double * rmatval = new double[num_cols]();
int rmatspace = num_cols;
int surplus;
double rhs;
CPXgetrows(cpxenv, cpxlp, &nzcnt, rmatbeg, rmatind, rmatval, rmatspace, &surplus, r, r);
CPXgetrhs(cpxenv, cpxlp, &rhs, r, r);
int index_z = 0;
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
{
index_z = rmatind[j];
break;
}
}
double g_i ;
if (method == 0)
g_i = calculateBetaBySolvingMIP(nzcnt, rmatind, rmatval, lp_optimal); //
else if(method == 1)
g_i = calculateBetaBySolvingMIP_rev1(nzcnt, rmatind, rmatval, lp_optimal);
// else if(method == 2)
// g_i = calculateBetaBySolvingMIP_2ConstSet(nzcnt, rmatind, rmatval, lp_optimal);
gs.push_back(g_i);
list_i.push_back(r);
list_j.push_back(index_z);
list_rhs.push_back(rhs);
if(rhs - g_i < 0)
{
rowsToDelete.push_back(cpyRowName);
map<int, string>::iterator itr = model_p->idx_var_name_table.find(index_z);
if (itr!= model_p->idx_var_name_table.end())
{
varsToDelete.push_back(itr->second);
}
}
delete rmatbeg;
delete []rmatind;
delete []rmatval;
}
free_and_null( (char **)&cur_rowname);
free_and_null((char **)&cur_rownamestore);
}
// change the coeffients
int * rowlist = new int[list_i.size()];
int * collist = new int[list_j.size()];
double * vallist = new double[gs.size()];
for (int k = 0 ; k < gs.size(); k++)
{
rowlist[k] = list_i[k];
collist[k] = list_j[k];
vallist[k] = (list_rhs[k] - gs[k])<=0 ? list_rhs[k] : list_rhs[k] - gs[k];
}
CPXchgcoeflist(cpxenv, cpxlp, gs.size(), rowlist, collist, vallist);
delete [] rowlist;
delete []collist;
delete []vallist;
for (map<int, OptModel*>::iterator itr = LBmodels.begin(); itr != LBmodels.end(); ++itr)
{
OptModel* p = itr->second;
delete p;
}
delete min_model;
}
void WolseyStrengthening::strengthenModelWithResourceCut2SetCut(int method)
{
// build basic model with all 2-const set inequalities
min_model = new OptModel(*model_p);
ResourceCutGenerator cutGen(min_model);
cutGen.addAllScenarioCuts();
TwoConstrainSetCutGenerator twoConstSetGen(min_model);
twoConstSetGen.addAllPairFacets(OptModel::CUT_AS_FORMULATION);
LHS lhs = model_p->getObjective();
RHS rhs = model_p->LP_optimal_value;
CUT cut(lhs,rhs);
string cutName = "objcut";
min_model->addAConstToCPXModel(cut, cutName, 0);
int num_rows = model_p->getNumRows();
int surplus;
CPXENVptr& cpxenv =model_p->getCPXEnv();
CPXLPptr& cpxlp = model_p->getCPXLP();
double lp_optimal = model_p->LP_optimal_value;
int num_cols = CPXgetnumcols(cpxenv, cpxlp);
vector< double > gs;
vector< int > list_i;
vector< int > list_j;
vector<double> list_rhs;
int status = CPXgetrowname (cpxenv, cpxlp, NULL, NULL, 0, &surplus, 0,num_rows-1);
vector<string> rowsToDelete;
vector<string> varsToDelete;
int cur_rownamespace = - surplus;
if ( cur_rownamespace > 0 )
{
char **cur_rowname = (char **) malloc (sizeof(char *)*(num_rows));
char *cur_rownamestore = (char *) malloc (cur_rownamespace);
if ( cur_rowname == NULL ||
cur_rownamestore == NULL ) {
fprintf (stderr, "Failed to get memory for column names.\n");
status = -1;
cout<< endl <<" error in reading column names"<<endl;
return;
}
status = CPXgetrowname (cpxenv, cpxlp, cur_rowname, cur_rownamestore,
cur_rownamespace, &surplus, 0, num_rows-1);
// map name with column index
for (int r = 0; r <num_rows ; r ++)
{
string rowName = cur_rowname[r];
string cpyRowName = rowName;
size_t t =rowName.find_first_of("0123456789");
if (t != string::npos)
rowName.erase(t);
if (rowName != "SN")
continue;
int nzcnt;
int * rmatbeg = new int(0);
int * rmatind = new int[num_cols]();
double * rmatval = new double[num_cols]();
int rmatspace = num_cols;
int surplus;
double rhs;
CPXgetrows(cpxenv, cpxlp, &nzcnt, rmatbeg, rmatind, rmatval, rmatspace, &surplus, r, r);
CPXgetrhs(cpxenv, cpxlp, &rhs, r, r);
int index_z = 0;
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
{
index_z = rmatind[j];
break;
}
}
double g_i ;
if (method == 0)
g_i = calculateBetaBySolvingMIP(nzcnt, rmatind, rmatval, lp_optimal); //
else if(method == 1)
g_i = calculateBetaBySolvingMIP_rev1(nzcnt, rmatind, rmatval, lp_optimal);
// else if(method == 2)
// g_i = calculateBetaBySolvingMIP_2ConstSet(nzcnt, rmatind, rmatval, lp_optimal);
gs.push_back(g_i);
list_i.push_back(r);
list_j.push_back(index_z);
list_rhs.push_back(rhs);
if(rhs - g_i < 0)
{
rowsToDelete.push_back(cpyRowName);
map<int, string>::iterator itr = model_p->idx_var_name_table.find(index_z);
if (itr!= model_p->idx_var_name_table.end())
{
varsToDelete.push_back(itr->second);
}
}
delete rmatbeg;
delete []rmatind;
delete []rmatval;
}
free_and_null( (char **)&cur_rowname);
free_and_null((char **)&cur_rownamestore);
}
// change the coeffients
int * rowlist = new int[list_i.size()];
int * collist = new int[list_j.size()];
double * vallist = new double[gs.size()];
for (int k = 0 ; k < gs.size(); k++)
{
rowlist[k] = list_i[k];
collist[k] = list_j[k];
vallist[k] = (list_rhs[k] - gs[k])<=0 ? list_rhs[k] : list_rhs[k] - gs[k];
}
CPXchgcoeflist(cpxenv, cpxlp, gs.size(), rowlist, collist, vallist);
delete [] rowlist;
delete []collist;
delete []vallist;
for (map<int, OptModel*>::iterator itr = LBmodels.begin(); itr != LBmodels.end(); ++itr)
{
OptModel* p = itr->second;
delete p;
}
delete min_model;
}
void WolseyStrengthening::strengthenModelNew( int method)
{
// build basic model with all 2-const set inequalities
min_model = new OptModel(*model_p);
ResourceCutGenerator cutGen(min_model);
cutGen.addAllScenarioCuts();
if (method == 1)
{
TwoConstrainSetCutGenerator twoConstSetGen(min_model);
for (int i =0; i < 10; i++)
{
if(twoConstSetGen.addViolatedFacets())
break;
}
}
TwoConstrainSetCutGenerator twoConstSetGen(min_model);
twoConstSetGen.addAllPairFacets(OptModel::CUT_AS_FORMULATION);
LHS lhs = model_p->getObjective();
RHS rhs = model_p->LP_optimal_value;
CUT cut(lhs,rhs);
string cutName = "objcut";
min_model->addAConstToCPXModel(cut, cutName, 0);
int num_rows = model_p->getNumRows();
int surplus;
CPXENVptr& cpxenv =model_p->getCPXEnv();
CPXLPptr& cpxlp = model_p->getCPXLP();
double lp_optimal = model_p->LP_optimal_value;
int num_cols = CPXgetnumcols(cpxenv, cpxlp);
vector< double > gs;
vector< int > list_i;
vector< int > list_j;
vector<double> list_rhs;
int status = CPXgetrowname (cpxenv, cpxlp, NULL, NULL, 0, &surplus, 0,num_rows-1);
vector<string> rowsToDelete;
vector<string> varsToDelete;
int cur_rownamespace = - surplus;
if ( cur_rownamespace > 0 )
{
char **cur_rowname = (char **) malloc (sizeof(char *)*(num_rows));
char *cur_rownamestore = (char *) malloc (cur_rownamespace);
if ( cur_rowname == NULL ||
cur_rownamestore == NULL ) {
fprintf (stderr, "Failed to get memory for column names.\n");
status = -1;
cout<< endl <<" error in reading column names"<<endl;
return;
}
status = CPXgetrowname (cpxenv, cpxlp, cur_rowname, cur_rownamestore,
cur_rownamespace, &surplus, 0, num_rows-1);
// map name with column index
for (int r = 0; r <num_rows ; r ++)
{
string rowName = cur_rowname[r];
string cpyRowName = rowName;
size_t t =rowName.find_first_of("0123456789");
if (t != string::npos)
rowName.erase(t);
if (rowName != "SN")
continue;
int nzcnt;
int * rmatbeg = new int(0);
int * rmatind = new int[num_cols]();
double * rmatval = new double[num_cols]();
int rmatspace = num_cols;
int surplus;
double rhs;
CPXgetrows(cpxenv, cpxlp, &nzcnt, rmatbeg, rmatind, rmatval, rmatspace, &surplus, r, r);
CPXgetrhs(cpxenv, cpxlp, &rhs, r, r);
int index_z = 0;
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
{
index_z = rmatind[j];
break;
}
}
double g_i ;
if (method == 0)
g_i = calculateBetaBySolvingMIP(nzcnt, rmatind, rmatval, lp_optimal); //
else if(method == 1)
g_i = calculateBetaBySolvingMIP_rev1(nzcnt, rmatind, rmatval, lp_optimal);
// else if(method == 2)
// g_i = calculateBetaBySolvingMIP_2ConstSet(nzcnt, rmatind, rmatval, lp_optimal);
gs.push_back(g_i);
list_i.push_back(r);
list_j.push_back(index_z);
list_rhs.push_back(rhs);
if(rhs - g_i < 0)
{
rowsToDelete.push_back(cpyRowName);
map<int, string>::iterator itr = model_p->idx_var_name_table.find(index_z);
if (itr!= model_p->idx_var_name_table.end())
{
varsToDelete.push_back(itr->second);
}
}
delete rmatbeg;
delete []rmatind;
delete []rmatval;
}
free_and_null( (char **)&cur_rowname);
free_and_null((char **)&cur_rownamestore);
}
// change the coeffients
int * rowlist = new int[list_i.size()];
int * collist = new int[list_j.size()];
double * vallist = new double[gs.size()];
for (int k = 0 ; k < gs.size(); k++)
{
rowlist[k] = list_i[k];
collist[k] = list_j[k];
vallist[k] = (list_rhs[k] - gs[k])<=0 ? list_rhs[k] : list_rhs[k] - gs[k];
}
CPXchgcoeflist(cpxenv, cpxlp, gs.size(), rowlist, collist, vallist);
delete [] rowlist;
delete []collist;
delete []vallist;
for (map<int, OptModel*>::iterator itr = LBmodels.begin(); itr != LBmodels.end(); ++itr)
{
OptModel* p = itr->second;
delete p;
}
delete min_model;
}
void WolseyStrengthening::strengthenModelWithResourceCut2SetCutSeparation(int method)
{
// first add all resource cuts, then solve each LP with violated 2-const cuts
min_model = new OptModel(*model_p);
ResourceCutGenerator cutGen(min_model);
cutGen.addAllScenarioCuts();
TwoConstrainSetCutGenerator twoConstSetGen(min_model);
twoConstSetGen.addAllPairFacets(OptModel::CUT_AS_FORMULATION);
LHS lhs = model_p->getObjective();
RHS rhs = model_p->LP_optimal_value;
CUT cut(lhs,rhs);
string cutName = "objcut";
min_model->addAConstToCPXModel(cut, cutName, 0);
int num_rows = model_p->getNumRows();
int surplus;
CPXENVptr& cpxenv =model_p->getCPXEnv();
CPXLPptr& cpxlp = model_p->getCPXLP();
double lp_optimal = model_p->LP_optimal_value;
int num_cols = CPXgetnumcols(cpxenv, cpxlp);
vector< double > gs;
vector< int > list_i;
vector< int > list_j;
vector<double> list_rhs;
int status = CPXgetrowname (cpxenv, cpxlp, NULL, NULL, 0, &surplus, 0,num_rows-1);
vector<string> rowsToDelete;
vector<string> varsToDelete;
int cur_rownamespace = - surplus;
if ( cur_rownamespace > 0 )
{
char **cur_rowname = (char **) malloc (sizeof(char *)*(num_rows));
char *cur_rownamestore = (char *) malloc (cur_rownamespace);
if ( cur_rowname == NULL ||
cur_rownamestore == NULL ) {
fprintf (stderr, "Failed to get memory for column names.\n");
status = -1;
cout<< endl <<" error in reading column names"<<endl;
return;
}
status = CPXgetrowname (cpxenv, cpxlp, cur_rowname, cur_rownamestore,
cur_rownamespace, &surplus, 0, num_rows-1);
// map name with column index
for (int r = 0; r <num_rows ; r ++)
{
string rowName = cur_rowname[r];
string cpyRowName = rowName;
size_t t =rowName.find_first_of("0123456789");
if (t != string::npos)
rowName.erase(t);
if (rowName != "SN")
continue;
int nzcnt;
int * rmatbeg = new int(0);
int * rmatind = new int[num_cols]();
double * rmatval = new double[num_cols]();
int rmatspace = num_cols;
int surplus;
double rhs;
CPXgetrows(cpxenv, cpxlp, &nzcnt, rmatbeg, rmatind, rmatval, rmatspace, &surplus, r, r);
CPXgetrhs(cpxenv, cpxlp, &rhs, r, r);
int index_z = 0;
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
{
index_z = rmatind[j];
break;
}
}
double g_i ;
if (method == 0)
g_i = calculateBetaBySolvingMIP(nzcnt, rmatind, rmatval, lp_optimal); //
else if(method == 1)
g_i = calculateBetaBySolvingMIP_rev2_addingViolated2ConstCuts(nzcnt, rmatind, rmatval, lp_optimal);
// else if(method == 2)
// g_i = calculateBetaBySolvingMIP_2ConstSet(nzcnt, rmatind, rmatval, lp_optimal);
gs.push_back(g_i);
list_i.push_back(r);
list_j.push_back(index_z);
list_rhs.push_back(rhs);
if(rhs - g_i < 0)
{
rowsToDelete.push_back(cpyRowName);
map<int, string>::iterator itr = model_p->idx_var_name_table.find(index_z);
if (itr!= model_p->idx_var_name_table.end())
{
varsToDelete.push_back(itr->second);
}
}
delete rmatbeg;
delete []rmatind;
delete []rmatval;
}
free_and_null( (char **)&cur_rowname);
free_and_null((char **)&cur_rownamestore);
}
// change the coeffients
int * rowlist = new int[list_i.size()];
int * collist = new int[list_j.size()];
double * vallist = new double[gs.size()];
for (int k = 0 ; k < gs.size(); k++)
{
rowlist[k] = list_i[k];
collist[k] = list_j[k];
vallist[k] = (list_rhs[k] - gs[k])<=0 ? list_rhs[k] : list_rhs[k] - gs[k];
}
CPXchgcoeflist(cpxenv, cpxlp, gs.size(), rowlist, collist, vallist);
delete [] rowlist;
delete []collist;
delete []vallist;
for (map<int, OptModel*>::iterator itr = LBmodels.begin(); itr != LBmodels.end(); ++itr)
{
OptModel* p = itr->second;
delete p;
}
delete min_model;
}
void WolseyStrengthening::removeRedundantConsts(vector<string>& constNames)
{
for (int i =0; i < constNames.size(); i++)
{
string rowName = constNames[i];
model_p->removeConstraintFromCPLEX(rowName);
}
}
void WolseyStrengthening::removeObsoleteVars(vector<string>& varNames)
{
for (int i =0; i < varNames.size(); i++)
{
string varName = varNames[i];
model_p->removeVariableFromCPLEX(varName);
}
model_p->mapVarIndexName();
}
double WolseyStrengthening::calculateBetaByFormula(int& nzcnt, int* rmatind, double *rmatval , double & lp_optimal)
{
map<double, int> sorted_a_j;
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] < DataModel::n)
sorted_a_j.insert(make_pair(rmatval[j], 0));
}
return lp_optimal*sorted_a_j.begin()->first;
}
double WolseyStrengthening::calculateBetaBySolvingMIP(int& nzcnt, int* rmatind, double *rmatval , double & lp_optimal, OptModel::MODEL_TYPE modelType)
{
int status;
OptModel subProblem("subproblem");
subProblem.cpxlp = CPXcloneprob( subProblem.getCPXEnv(), model_p->getCPXLP(), &status);
//add objective cut
LHS lhs = subProblem.getObjective();
RHS rhs = lp_optimal;
CUT cut(lhs,rhs);
string cutName = "objcut";
subProblem.addAConstToCPXModel(cut, cutName, 0);
subProblem.writeModel2File("subProblem.lp");
double* values = new double[DataModel::n]();
int* indices = new int[DataModel::n]();
for (int j = 0; j < DataModel::n; j++)
{
indices[j] = j;
}
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
break;
// indices[j] = rmatind[j];
// values[j] = rmatval[j];
values[ rmatind[j] ] = rmatval[j];
}
CPXchgobj(subProblem.getCPXEnv(), subProblem.getCPXLP(), DataModel::n, indices, values);
delete []values;
delete []indices;
if (modelType == OptModel::MODEL_TYPE_MIP)
{
//subProblem.mapVarNameIndex();
subProblem.mapVarIndexName();
subProblem.changeLP2MIP();
}
subProblem.writeModel2File("subproblem.lp");
subProblem.solve();
double beta =0;
if (modelType == OptModel::MODEL_TYPE_MIP)
beta = subProblem.MIP_optimal_value;
else
beta = subProblem.LP_optimal_value;
iteration_cnt++;
return beta;
}
double WolseyStrengthening::calculateBetaBySolvingMIP_rev1(int& nzcnt, int* rmatind, double *rmatval , double & lp_optimal, OptModel::MODEL_TYPE modelType)
{
int status;
// OptModel subProblem("subproblem");
// subProblem.cpxlp = CPXcloneprob( subProblem.getCPXEnv(), model_p->getCPXLP(), &status);
min_model->writeModel2File("subProblem.lp");
// change objective function
double* values = new double[DataModel::n]();
int* indices = new int[DataModel::n]();
for (int j = 0; j < DataModel::n; j++)
{
indices[j] = j;
}
for (int j = 0 ; j < nzcnt; j++)
{
if (rmatind[j] >= DataModel::n)
break;
// indices[j] = rmatind[j];
// values[j] = rmatval[j];
values[ rmatind[j] ] = rmatval[j];
}
CPXchgobj(min_model->getCPXEnv(), min_model->getCPXLP(), DataModel::n, indices, values);