int main (int argc, const char *argv[])
{
// Define your favorite OsiSolver
OsiClpSolverInterface solver1;
// Read in model using argv[1]
// and assert that it is a clean model
std::string mpsFileName;
#if defined(SAMPLEDIR)
mpsFileName = SAMPLEDIR "/p0033.mps";
#else
if (argc < 2) {
fprintf(stderr, "Do not know where to find sample MPS files.\n");
exit(1);
}
#endif
if (argc>=2) mpsFileName = argv[1];
int numMpsReadErrors = solver1.readMps(mpsFileName.c_str(),"");
assert(numMpsReadErrors==0);
double time1 = CoinCpuTime();
OsiClpSolverInterface solverSave = solver1;
/* Options are:
preprocess to do preprocessing
time in minutes
if 2 parameters and numeric taken as time
*/
bool preProcess=false;
double minutes=-1.0;
int nGoodParam=0;
for (int iParam=2; iParam<argc;iParam++) {
if (!strcmp(argv[iParam],"preprocess")) {
preProcess=true;
nGoodParam++;
} else if (!strcmp(argv[iParam],"time")) {
if (iParam+1<argc&&isdigit(argv[iParam+1][0])) {
minutes=atof(argv[iParam+1]);
if (minutes>=0.0) {
nGoodParam+=2;
iParam++; // skip time
}
}
}
}
if (nGoodParam==0&&argc==3&&isdigit(argv[2][0])) {
// If time is given then stop after that number of minutes
minutes = atof(argv[2]);
if (minutes>=0.0)
nGoodParam=1;
}
if (nGoodParam!=argc-2&&argc>=2) {
printf("Usage <file> [preprocess] [time <minutes>] or <file> <minutes>\n");
exit(1);
}
// Reduce printout
solver1.setHintParam(OsiDoReducePrint,true,OsiHintTry);
// See if we want preprocessing
OsiSolverInterface * solver2=&solver1;
CglPreProcess process;
// Never do preprocessing until dual tests out as can fix incorrectly
preProcess=false;
if (preProcess) {
/* Do not try and produce equality cliques and
do up to 5 passes */
solver2 = process.preProcess(solver1,false,5);
if (!solver2) {
printf("Pre-processing says infeasible\n");
exit(2);
}
solver2->resolve();
}
// Turn L rows into cuts
CglStoredUser stored;
{
int numberRows = solver2->getNumRows();
int * whichRow = new int[numberRows];
// get row copy
const CoinPackedMatrix * rowCopy = solver2->getMatrixByRow();
const int * column = rowCopy->getIndices();
const int * rowLength = rowCopy->getVectorLengths();
const CoinBigIndex * rowStart = rowCopy->getVectorStarts();
const double * rowLower = solver2->getRowLower();
const double * rowUpper = solver2->getRowUpper();
const double * element = rowCopy->getElements();
int iRow,nDelete=0;
for (iRow=0;iRow<numberRows;iRow++) {
if (rowLower[iRow]<-1.0e20||rowUpper[iRow]>1.0e20) {
// take out
whichRow[nDelete++]=iRow;
}
}
// leave some rows to avoid empty problem (Gomory does not like)
nDelete = CoinMax(CoinMin(nDelete,numberRows-5),0);
for (int jRow=0;jRow<nDelete;jRow++) {
iRow=whichRow[jRow];
int start = rowStart[iRow];
stored.addCut(rowLower[iRow],rowUpper[iRow],rowLength[iRow],
column+start,element+start);
}
/* The following is problem specific.
Normally cuts are deleted if slack on cut basic.
On some problems you may wish to leave cuts in as long
as slack value zero
*/
int numberCuts=stored.sizeRowCuts();
for (int iCut=0;iCut<numberCuts;iCut++) {
//stored.mutableRowCutPointer(iCut)->setEffectiveness(1.0e50);
}
solver2->deleteRows(nDelete,whichRow);
delete [] whichRow;
}
CbcModel model(*solver2);
model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
// Set up some cut generators and defaults
// Probing first as gets tight bounds on continuous
CglProbing generator1;
generator1.setUsingObjective(true);
generator1.setMaxPass(1);
generator1.setMaxPassRoot(5);
// Number of unsatisfied variables to look at
generator1.setMaxProbe(10);
generator1.setMaxProbeRoot(1000);
// How far to follow the consequences
generator1.setMaxLook(50);
generator1.setMaxLookRoot(500);
// Only look at rows with fewer than this number of elements
generator1.setMaxElements(200);
generator1.setRowCuts(3);
CglGomory generator2;
// try larger limit
generator2.setLimit(300);
CglKnapsackCover generator3;
CglRedSplit generator4;
// try larger limit
generator4.setLimit(200);
CglClique generator5;
generator5.setStarCliqueReport(false);
generator5.setRowCliqueReport(false);
CglMixedIntegerRounding2 mixedGen;
CglFlowCover flowGen;
// Add in generators
// Experiment with -1 and -99 etc
// This is just for one particular model
model.addCutGenerator(&generator1,-1,"Probing");
//model.addCutGenerator(&generator2,-1,"Gomory");
model.addCutGenerator(&generator2,1,"Gomory");
model.addCutGenerator(&generator3,-1,"Knapsack");
// model.addCutGenerator(&generator4,-1,"RedSplit");
//model.addCutGenerator(&generator5,-1,"Clique");
model.addCutGenerator(&generator5,1,"Clique");
model.addCutGenerator(&flowGen,-1,"FlowCover");
model.addCutGenerator(&mixedGen,-1,"MixedIntegerRounding");
// Add stored cuts (making sure at all depths)
model.addCutGenerator(&stored,1,"Stored",true,false,false,-100,1,-1);
int numberGenerators = model.numberCutGenerators();
int iGenerator;
// Say we want timings
for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
CbcCutGenerator * generator = model.cutGenerator(iGenerator);
generator->setTiming(true);
}
OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (model.solver());
// go faster stripes
if (osiclp) {
if(osiclp->getNumRows()<300&&osiclp->getNumCols()<500) {
//osiclp->setupForRepeatedUse(2,0);
osiclp->setupForRepeatedUse(0,0);
}
// Don't allow dual stuff
osiclp->setSpecialOptions(osiclp->specialOptions()|262144);
}
// Uncommenting this should switch off all CBC messages
// model.messagesPointer()->setDetailMessages(10,10000,NULL);
// No heuristics
// Do initial solve to continuous
model.initialSolve();
/* You need the next few lines -
a) so that cut generator will always be called again if it generated cuts
b) it is known that matrix is not enough to define problem so do cuts even
if it looks integer feasible at continuous optimum.
c) a solution found by strong branching will be ignored.
d) don't recompute a solution once found
*/
// Make sure cut generator called correctly (a)
iGenerator=numberGenerators-1;
model.cutGenerator(iGenerator)->setMustCallAgain(true);
// Say cuts needed at continuous (b)
OsiBabSolver oddCuts;
oddCuts.setSolverType(4);
// owing to bug must set after initialSolve
model.passInSolverCharacteristics(&oddCuts);
// Say no to all solutions by strong branching (c)
CbcFeasibilityNoStrong noStrong;
model.setProblemFeasibility(noStrong);
// Say don't recompute solution d)
model.setSpecialOptions(4);
// Could tune more
double objValue = model.solver()->getObjSense()*model.solver()->getObjValue();
double minimumDropA=CoinMin(1.0,fabs(objValue)*1.0e-3+1.0e-4);
double minimumDrop= fabs(objValue)*1.0e-4+1.0e-4;
printf("min drop %g (A %g)\n",minimumDrop,minimumDropA);
model.setMinimumDrop(minimumDrop);
if (model.getNumCols()<500)
model.setMaximumCutPassesAtRoot(-100); // always do 100 if possible
else if (model.getNumCols()<5000)
model.setMaximumCutPassesAtRoot(100); // use minimum drop
else
model.setMaximumCutPassesAtRoot(20);
model.setMaximumCutPasses(10);
//model.setMaximumCutPasses(2);
// Switch off strong branching if wanted
// model.setNumberStrong(0);
// Do more strong branching if small
if (model.getNumCols()<5000)
model.setNumberStrong(10);
model.setNumberStrong(20);
//model.setNumberStrong(5);
model.setNumberBeforeTrust(5);
model.solver()->setIntParam(OsiMaxNumIterationHotStart,100);
// If time is given then stop after that number of minutes
if (minutes>=0.0) {
std::cout<<"Stopping after "<<minutes<<" minutes"<<std::endl;
model.setDblParam(CbcModel::CbcMaximumSeconds,60.0*minutes);
}
// Switch off most output
if (model.getNumCols()<30000) {
model.messageHandler()->setLogLevel(1);
//model.solver()->messageHandler()->setLogLevel(0);
} else {
model.messageHandler()->setLogLevel(2);
model.solver()->messageHandler()->setLogLevel(1);
}
//model.messageHandler()->setLogLevel(2);
//model.solver()->messageHandler()->setLogLevel(2);
//model.setPrintFrequency(50);
//#define DEBUG_CUTS
#ifdef DEBUG_CUTS
// Set up debugger by name (only if no preprocesing)
if (!preProcess) {
std::string problemName ;
model.solver()->getStrParam(OsiProbName,problemName) ;
model.solver()->activateRowCutDebugger(problemName.c_str()) ;
}
#endif
// Do complete search
model.branchAndBound();
std::cout<<mpsFileName<<" took "<<CoinCpuTime()-time1<<" seconds, "
<<model.getNodeCount()<<" nodes with objective "
<<model.getObjValue()
<<(!model.status() ? " Finished" : " Not finished")
<<std::endl;
// Print more statistics
std::cout<<"Cuts at root node changed objective from "<<model.getContinuousObjective()
<<" to "<<model.rootObjectiveAfterCuts()<<std::endl;
for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
CbcCutGenerator * generator = model.cutGenerator(iGenerator);
std::cout<<generator->cutGeneratorName()<<" was tried "
<<generator->numberTimesEntered()<<" times and created "
<<generator->numberCutsInTotal()<<" cuts of which "
<<generator->numberCutsActive()<<" were active after adding rounds of cuts";
if (generator->timing())
std::cout<<" ( "<<generator->timeInCutGenerator()<<" seconds)"<<std::endl;
else
std::cout<<std::endl;
}
// Print solution if finished - we can't get names from Osi! - so get from OsiClp
if (model.getMinimizationObjValue()<1.0e50) {
// post process
OsiSolverInterface * solver;
if (preProcess) {
process.postProcess(*model.solver());
// Solution now back in solver1
solver = & solver1;
} else {
solver = model.solver();
}
int numberColumns = solver->getNumCols();
const double * solution = solver->getColSolution();
// Get names from solver1 (as OsiSolverInterface may lose)
std::vector<std::string> columnNames = *solver1.getModelPtr()->columnNames();
int iColumn;
std::cout<<std::setiosflags(std::ios::fixed|std::ios::showpoint)<<std::setw(14);
std::cout<<"--------------------------------------"<<std::endl;
for (iColumn=0;iColumn<numberColumns;iColumn++) {
double value=solution[iColumn];
if (fabs(value)>1.0e-7&&solver->isInteger(iColumn)) {
std::cout<<std::setw(6)<<iColumn<<" "
<<columnNames[iColumn]<<" "
<<value<<std::endl;
solverSave.setColLower(iColumn,value);
solverSave.setColUpper(iColumn,value);
}
}
std::cout<<"--------------------------------------"<<std::endl;
std::cout<<std::resetiosflags(std::ios::fixed|std::ios::showpoint|std::ios::scientific);
solverSave.initialSolve();
}
return 0;
}
int main (int argc, const char *argv[])
{
// Define your favorite OsiSolver
OsiClpSolverInterface solver1;
// Read in model using argv[1]
// and assert that it is a clean model
std::string dirsep(1,CoinFindDirSeparator());
std::string mpsFileName;
# if defined(SAMPLEDIR)
mpsFileName = SAMPLEDIR ;
mpsFileName += dirsep+"p0033.mps";
# else
if (argc < 2) {
fprintf(stderr, "Do not know where to find sample MPS files.\n");
exit(1);
}
# endif
if (argc>=2) mpsFileName = argv[1];
int numMpsReadErrors = solver1.readMps(mpsFileName.c_str(),"");
if( numMpsReadErrors != 0 )
{
printf("%d errors reading MPS file\n", numMpsReadErrors);
return numMpsReadErrors;
}
double time1 = CoinCpuTime();
/* Options are:
preprocess to do preprocessing
time in minutes
if 2 parameters and numeric taken as time
*/
bool preProcess=false;
double minutes=-1.0;
int nGoodParam=0;
for (int iParam=2; iParam<argc;iParam++) {
if (!strcmp(argv[iParam],"preprocess")) {
preProcess=true;
nGoodParam++;
} else if (!strcmp(argv[iParam],"time")) {
if (iParam+1<argc&&isdigit(argv[iParam+1][0])) {
minutes=atof(argv[iParam+1]);
if (minutes>=0.0) {
nGoodParam+=2;
iParam++; // skip time
}
}
}
}
if (nGoodParam==0&&argc==3&&isdigit(argv[2][0])) {
// If time is given then stop after that number of minutes
minutes = atof(argv[2]);
if (minutes>=0.0)
nGoodParam=1;
}
if (nGoodParam!=argc-2&&argc>=2) {
printf("Usage <file> [preprocess] [time <minutes>] or <file> <minutes>\n");
exit(1);
}
solver1.initialSolve();
// Reduce printout
solver1.setHintParam(OsiDoReducePrint,true,OsiHintTry);
// See if we want preprocessing
OsiSolverInterface * solver2=&solver1;
#if PREPROCESS==1
CglPreProcess process;
if (preProcess) {
/* Do not try and produce equality cliques and
do up to 5 passes */
solver2 = process.preProcess(solver1,false,5);
if (!solver2) {
printf("Pre-processing says infeasible\n");
exit(2);
}
solver2->resolve();
}
#endif
CbcModel model(*solver2);
model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
// Set up some cut generators and defaults
// Probing first as gets tight bounds on continuous
CglProbing generator1;
generator1.setUsingObjective(true);
generator1.setMaxPass(1);
generator1.setMaxPassRoot(5);
// Number of unsatisfied variables to look at
generator1.setMaxProbe(10);
generator1.setMaxProbeRoot(1000);
// How far to follow the consequences
generator1.setMaxLook(50);
generator1.setMaxLookRoot(500);
// Only look at rows with fewer than this number of elements
generator1.setMaxElements(200);
generator1.setRowCuts(3);
CglGomory generator2;
// try larger limit
generator2.setLimit(300);
CglKnapsackCover generator3;
CglRedSplit generator4;
// try larger limit
generator4.setLimit(200);
CglClique generator5;
generator5.setStarCliqueReport(false);
generator5.setRowCliqueReport(false);
CglMixedIntegerRounding2 mixedGen;
CglFlowCover flowGen;
// Add in generators
// Experiment with -1 and -99 etc
model.addCutGenerator(&generator1,-1,"Probing");
model.addCutGenerator(&generator2,-1,"Gomory");
model.addCutGenerator(&generator3,-1,"Knapsack");
// model.addCutGenerator(&generator4,-1,"RedSplit");
model.addCutGenerator(&generator5,-1,"Clique");
model.addCutGenerator(&flowGen,-1,"FlowCover");
model.addCutGenerator(&mixedGen,-1,"MixedIntegerRounding");
// Say we want timings
int numberGenerators = model.numberCutGenerators();
int iGenerator;
for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
CbcCutGenerator * generator = model.cutGenerator(iGenerator);
generator->setTiming(true);
}
OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (model.solver());
// go faster stripes
if (osiclp) {
// Turn this off if you get problems
// Used to be automatically set
osiclp->setSpecialOptions(128);
if(osiclp->getNumRows()<300&&osiclp->getNumCols()<500) {
//osiclp->setupForRepeatedUse(2,0);
osiclp->setupForRepeatedUse(0,0);
}
}
// Uncommenting this should switch off all CBC messages
// model.messagesPointer()->setDetailMessages(10,10000,NULL);
// Allow rounding heuristic
CbcRounding heuristic1(model);
model.addHeuristic(&heuristic1);
// And local search when new solution found
CbcHeuristicLocal heuristic2(model);
model.addHeuristic(&heuristic2);
// Redundant definition of default branching (as Default == User)
CbcBranchUserDecision branch;
model.setBranchingMethod(&branch);
// Definition of node choice
CbcCompareUser compare;
model.setNodeComparison(compare);
// Do initial solve to continuous
model.initialSolve();
// Could tune more
double objValue = model.solver()->getObjSense()*model.solver()->getObjValue();
double minimumDropA=CoinMin(1.0,fabs(objValue)*1.0e-3+1.0e-4);
double minimumDrop= fabs(objValue)*1.0e-4+1.0e-4;
printf("min drop %g (A %g)\n",minimumDrop,minimumDropA);
model.setMinimumDrop(minimumDrop);
if (model.getNumCols()<500)
model.setMaximumCutPassesAtRoot(-100); // always do 100 if possible
else if (model.getNumCols()<5000)
model.setMaximumCutPassesAtRoot(100); // use minimum drop
else
model.setMaximumCutPassesAtRoot(20);
model.setMaximumCutPasses(10);
//model.setMaximumCutPasses(2);
// Switch off strong branching if wanted
// model.setNumberStrong(0);
// Do more strong branching if small
if (model.getNumCols()<5000)
model.setNumberStrong(10);
model.setNumberStrong(20);
//model.setNumberStrong(5);
model.setNumberBeforeTrust(5);
model.solver()->setIntParam(OsiMaxNumIterationHotStart,100);
// If time is given then stop after that number of minutes
if (minutes>=0.0) {
std::cout<<"Stopping after "<<minutes<<" minutes"<<std::endl;
model.setDblParam(CbcModel::CbcMaximumSeconds,60.0*minutes);
}
// Switch off most output
if (model.getNumCols()<3000) {
model.messageHandler()->setLogLevel(1);
//model.solver()->messageHandler()->setLogLevel(0);
} else {
model.messageHandler()->setLogLevel(2);
model.solver()->messageHandler()->setLogLevel(1);
}
//model.messageHandler()->setLogLevel(2);
//model.solver()->messageHandler()->setLogLevel(2);
//model.setPrintFrequency(50);
//#define DEBUG_CUTS
#ifdef DEBUG_CUTS
// Set up debugger by name (only if no preprocesing)
if (!preProcess) {
std::string problemName ;
model.solver()->getStrParam(OsiProbName,problemName) ;
model.solver()->activateRowCutDebugger(problemName.c_str()) ;
}
#endif
#if PREPROCESS==2
// Default strategy will leave cut generators as they exist already
// so cutsOnlyAtRoot (1) ignored
// numberStrong (2) is 5 (default)
// numberBeforeTrust (3) is 5 (default is 0)
// printLevel (4) defaults (0)
CbcStrategyDefault strategy(true,5,5);
// Set up pre-processing to find sos if wanted
if (preProcess)
strategy.setupPreProcessing(2);
model.setStrategy(strategy);
#endif
// Do complete search
model.branchAndBound();
std::cout<<mpsFileName<<" took "<<CoinCpuTime()-time1<<" seconds, "
<<model.getNodeCount()<<" nodes with objective "
<<model.getObjValue()
<<(!model.status() ? " Finished" : " Not finished")
<<std::endl;
// Print more statistics
std::cout<<"Cuts at root node changed objective from "<<model.getContinuousObjective()
<<" to "<<model.rootObjectiveAfterCuts()<<std::endl;
for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
CbcCutGenerator * generator = model.cutGenerator(iGenerator);
std::cout<<generator->cutGeneratorName()<<" was tried "
<<generator->numberTimesEntered()<<" times and created "
<<generator->numberCutsInTotal()<<" cuts of which "
<<generator->numberCutsActive()<<" were active after adding rounds of cuts";
if (generator->timing())
std::cout<<" ( "<<generator->timeInCutGenerator()<<" seconds)"<<std::endl;
else
std::cout<<std::endl;
}
// Print solution if finished - we can't get names from Osi! - so get from OsiClp
if (model.getMinimizationObjValue()<1.0e50) {
#if PREPROCESS==1
// post process
OsiSolverInterface * solver;
if (preProcess) {
process.postProcess(*model.solver());
// Solution now back in solver1
solver = & solver1;
} else {
solver = model.solver();
}
#else
OsiSolverInterface * solver = model.solver();
#endif
int numberColumns = solver->getNumCols();
const double * solution = solver->getColSolution();
// Get names from solver1 (as OsiSolverInterface may lose)
std::vector<std::string> columnNames = *solver1.getModelPtr()->columnNames();
int iColumn;
std::cout<<std::setiosflags(std::ios::fixed|std::ios::showpoint)<<std::setw(14);
std::cout<<"--------------------------------------"<<std::endl;
for (iColumn=0;iColumn<numberColumns;iColumn++) {
double value=solution[iColumn];
if (fabs(value)>1.0e-7&&solver->isInteger(iColumn))
std::cout<<std::setw(6)<<iColumn<<" "
<<columnNames[iColumn]<<" "
<<value<<std::endl;
}
std::cout<<"--------------------------------------"<<std::endl;
std::cout<<std::resetiosflags(std::ios::fixed|std::ios::showpoint|std::ios::scientific);
}
return 0;
}
int main (int argc, const char *argv[])
{
CbcSolver3 solver1;
// Read in model using argv[1]
// and assert that it is a clean model
std::string mpsFileName;
if (argc>=2) mpsFileName = argv[1];
int numMpsReadErrors = solver1.readMps(mpsFileName.c_str(),"");
assert(numMpsReadErrors==0);
double time1 = CoinCpuTime();
/* Options are:
preprocess to do preprocessing
time in minutes
if 2 parameters and numeric taken as time
*/
bool preProcess=false;
double minutes=-1.0;
int nGoodParam=0;
for (int iParam=2; iParam<argc;iParam++) {
if (!strcmp(argv[iParam],"preprocess")) {
preProcess=true;
nGoodParam++;
} else if (!strcmp(argv[iParam],"time")) {
if (iParam+1<argc&&isdigit(argv[iParam+1][0])) {
minutes=atof(argv[iParam+1]);
if (minutes>=0.0) {
nGoodParam+=2;
iParam++; // skip time
}
}
}
}
if (nGoodParam==0&&argc==3&&isdigit(argv[2][0])) {
// If time is given then stop after that number of minutes
minutes = atof(argv[2]);
if (minutes>=0.0)
nGoodParam=1;
}
if (nGoodParam!=argc-2) {
printf("Usage <file> [preprocess] [time <minutes>] or <file> <minutes>\n");
exit(1);
}
solver1.initialSolve();
// Reduce printout
solver1.setHintParam(OsiDoReducePrint,true,OsiHintTry);
// Say we want scaling
//solver1.setHintParam(OsiDoScale,true,OsiHintTry);
//solver1.setCleanupScaling(1);
// See if we want preprocessing
OsiSolverInterface * solver2=&solver1;
CglPreProcess process;
if (preProcess) {
/* Do not try and produce equality cliques and
do up to 5 passes */
solver2 = process.preProcess(solver1,false,5);
if (!solver2) {
printf("Pre-processing says infeasible\n");
exit(2);
}
solver2->resolve();
}
CbcModel model(*solver2);
// Point to solver
OsiSolverInterface * solver3 = model.solver();
CbcSolver3 * osiclp = dynamic_cast< CbcSolver3*> (solver3);
assert (osiclp);
const double fractionFix=0.985;
osiclp->initialize(&model,NULL);
osiclp->setAlgorithm(2);
osiclp->setMemory(1000);
osiclp->setNested(fractionFix);
//osiclp->setNested(1.0); //off
// Set up some cut generators and defaults
// Probing first as gets tight bounds on continuous
CglProbing generator1;
generator1.setUsingObjective(true);
generator1.setMaxPass(3);
// Number of unsatisfied variables to look at
generator1.setMaxProbe(10);
// How far to follow the consequences
generator1.setMaxLook(50);
// Only look at rows with fewer than this number of elements
generator1.setMaxElements(200);
generator1.setRowCuts(3);
CglGomory generator2;
// try larger limit
generator2.setLimit(300);
CglKnapsackCover generator3;
CglOddHole generator4;
generator4.setMinimumViolation(0.005);
generator4.setMinimumViolationPer(0.00002);
// try larger limit
generator4.setMaximumEntries(200);
CglClique generator5;
generator5.setStarCliqueReport(false);
generator5.setRowCliqueReport(false);
CglMixedIntegerRounding mixedGen;
/* This is same as default constructor -
(1,true,1)
I presume if maxAggregate larger then slower but maybe better
criterion can be 1 through 3
Reference:
Hugues Marchand and Laurence A. Wolsey
Aggregation and Mixed Integer Rounding to Solve MIPs
Operations Research, 49(3), May-June 2001.
*/
int maxAggregate=1;
bool multiply=true;
int criterion=1;
CglMixedIntegerRounding2 mixedGen2(maxAggregate,multiply,criterion);
CglFlowCover flowGen;
// Add in generators
// Experiment with -1 and -99 etc
model.addCutGenerator(&generator1,-99,"Probing");
//model.addCutGenerator(&generator2,-1,"Gomory");
//model.addCutGenerator(&generator3,-1,"Knapsack");
//model.addCutGenerator(&generator4,-1,"OddHole");
//model.addCutGenerator(&generator5,-1,"Clique");
//model.addCutGenerator(&flowGen,-1,"FlowCover");
//model.addCutGenerator(&mixedGen,-1,"MixedIntegerRounding");
//model.addCutGenerator(&mixedGen2,-1,"MixedIntegerRounding2");
// Say we want timings
int numberGenerators = model.numberCutGenerators();
int iGenerator;
for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
CbcCutGenerator * generator = model.cutGenerator(iGenerator);
generator->setTiming(true);
}
// Allow rounding heuristic
CbcRounding heuristic1(model);
model.addHeuristic(&heuristic1);
// And Greedy heuristic
CbcHeuristicGreedyCover heuristic2(model);
// Use original upper and perturb more
heuristic2.setAlgorithm(11);
model.addHeuristic(&heuristic2);
// Redundant definition of default branching (as Default == User)
CbcBranchUserDecision branch;
model.setBranchingMethod(&branch);
// Definition of node choice
CbcCompareUser compare;
model.setNodeComparison(compare);
int iColumn;
int numberColumns = solver3->getNumCols();
// do pseudo costs
CbcObject ** objects = new CbcObject * [numberColumns+1];
const CoinPackedMatrix * matrix = solver3->getMatrixByCol();
// Column copy
const int * columnLength = matrix->getVectorLengths();
const double * objective = model.getObjCoefficients();
int n=0;
for (iColumn=0;iColumn<numberColumns;iColumn++) {
if (solver3->isInteger(iColumn)) {
double costPer = objective[iColumn]/ ((double) columnLength[iColumn]);
CbcSimpleIntegerPseudoCost * newObject =
new CbcSimpleIntegerPseudoCost(&model,n,iColumn,
costPer,costPer);
newObject->setMethod(3);
objects[n++]= newObject;
}
}
// and special fix lots branch
objects[n++]=new CbcBranchToFixLots(&model,-1.0e-6,fractionFix+0.01,1,0,NULL);
model.addObjects(n,objects);
for (iColumn=0;iColumn<n;iColumn++)
delete objects[iColumn];
delete [] objects;
// High priority for odd object
int followPriority=1;
model.passInPriorities(&followPriority,true);
// Do initial solve to continuous
model.initialSolve();
// Could tune more
model.setMinimumDrop(CoinMin(1.0,
fabs(model.getMinimizationObjValue())*1.0e-3+1.0e-4));
if (model.getNumCols()<500)
model.setMaximumCutPassesAtRoot(-100); // always do 100 if possible
else if (model.getNumCols()<5000)
model.setMaximumCutPassesAtRoot(100); // use minimum drop
else
model.setMaximumCutPassesAtRoot(20);
//model.setMaximumCutPasses(1);
// Do more strong branching if small
//if (model.getNumCols()<5000)
//model.setNumberStrong(10);
// Switch off strong branching if wanted
model.setNumberStrong(0);
model.solver()->setIntParam(OsiMaxNumIterationHotStart,100);
// If time is given then stop after that number of minutes
if (minutes>=0.0) {
std::cout<<"Stopping after "<<minutes<<" minutes"<<std::endl;
model.setDblParam(CbcModel::CbcMaximumSeconds,60.0*minutes);
}
// Switch off most output
if (model.getNumCols()<300000) {
model.messageHandler()->setLogLevel(1);
//model.solver()->messageHandler()->setLogLevel(0);
} else {
model.messageHandler()->setLogLevel(2);
model.solver()->messageHandler()->setLogLevel(1);
}
//model.messageHandler()->setLogLevel(2);
//model.solver()->messageHandler()->setLogLevel(2);
//model.setPrintFrequency(50);
#define DEBUG_CUTS
#ifdef DEBUG_CUTS
// Set up debugger by name (only if no preprocesing)
if (!preProcess) {
std::string problemName ;
//model.solver()->getStrParam(OsiProbName,problemName) ;
//model.solver()->activateRowCutDebugger(problemName.c_str()) ;
model.solver()->activateRowCutDebugger("cap6000a") ;
}
#endif
// Do complete search
try {
model.branchAndBound();
}
catch (CoinError e) {
e.print();
if (e.lineNumber()>=0)
std::cout<<"This was from a CoinAssert"<<std::endl;
exit(0);
}
//void printHowMany();
//printHowMany();
std::cout<<mpsFileName<<" took "<<CoinCpuTime()-time1<<" seconds, "
<<model.getNodeCount()<<" nodes with objective "
<<model.getObjValue()
<<(!model.status() ? " Finished" : " Not finished")
<<std::endl;
// Print more statistics
std::cout<<"Cuts at root node changed objective from "<<model.getContinuousObjective()
<<" to "<<model.rootObjectiveAfterCuts()<<std::endl;
for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
CbcCutGenerator * generator = model.cutGenerator(iGenerator);
std::cout<<generator->cutGeneratorName()<<" was tried "
<<generator->numberTimesEntered()<<" times and created "
<<generator->numberCutsInTotal()<<" cuts of which "
<<generator->numberCutsActive()<<" were active after adding rounds of cuts";
if (generator->timing())
std::cout<<" ( "<<generator->timeInCutGenerator()<<" seconds)"<<std::endl;
else
std::cout<<std::endl;
}
// Print solution if finished - we can't get names from Osi!
if (model.getMinimizationObjValue()<1.0e50) {
// post process
if (preProcess)
process.postProcess(*model.solver());
int numberColumns = model.solver()->getNumCols();
const double * solution = model.solver()->getColSolution();
int iColumn;
std::cout<<std::setiosflags(std::ios::fixed|std::ios::showpoint)<<std::setw(14);
std::cout<<"--------------------------------------"<<std::endl;
for (iColumn=0;iColumn<numberColumns;iColumn++) {
double value=solution[iColumn];
if (fabs(value)>1.0e-7&&model.solver()->isInteger(iColumn))
std::cout<<std::setw(6)<<iColumn<<" "<<value<<std::endl;
}
std::cout<<"--------------------------------------"<<std::endl;
std::cout<<std::resetiosflags(std::ios::fixed|std::ios::showpoint|std::ios::scientific);
}
return 0;
}