void
CglClique::generateCuts(const OsiSolverInterface& si, OsiCuts & cs,
const CglTreeInfo info)
{
int i;
bool has_petol_set = petol != -1.0;
if (! has_petol_set)
si.getDblParam(OsiPrimalTolerance, petol);
int numberOriginalRows = si.getNumRows();
if (info.inTree&&justOriginalRows_)
numberOriginalRows = info.formulation_rows;
int numberRowCutsBefore = cs.sizeRowCuts();
// First select which rows/columns we are interested in.
if (!setPacking_) {
selectFractionalBinaries(si);
if (!sp_orig_row_ind) {
selectRowCliques(si,numberOriginalRows);
}
} else {
selectFractionals(si);
delete[] sp_orig_row_ind;
sp_numrows = numberOriginalRows;
//sp_numcols = si.getNumCols();
sp_orig_row_ind = new int[sp_numrows];
for (i = 0; i < sp_numrows; ++i)
sp_orig_row_ind[i] = i;
}
// Just original rows
if (justOriginalRows_&&info.inTree)
sp_numrows = CoinMin(info.formulation_rows,sp_numrows);
createSetPackingSubMatrix(si);
fgraph.edgenum = createNodeNode();
createFractionalGraph();
cl_indices = new int[sp_numcols];
cl_del_indices = new int[sp_numcols];
if (do_row_clique)
find_rcl(cs);
if (do_star_clique)
find_scl(cs);
if (!info.inTree&&((info.options&4)==4||((info.options&8)&&!info.pass))) {
int numberRowCutsAfter = cs.sizeRowCuts();
for (int i=numberRowCutsBefore;i<numberRowCutsAfter;i++)
cs.rowCutPtr(i)->setGloballyValid();
}
delete[] cl_indices; cl_indices = 0;
delete[] cl_del_indices; cl_del_indices = 0;
deleteFractionalGraph();
delete[] node_node; node_node = 0;
deleteSetPackingSubMatrix();
if (! has_petol_set)
petol = -1;
}
// Add cuts
void
CglStored::addCut(const OsiCuts & cs)
{
int numberRowCuts = cs.sizeRowCuts();
for (int i=0;i<numberRowCuts;i++) {
cuts_.insert(*cs.rowCutPtr(i));
}
}
//-------------------------------------------------------------------
void OsiCuts::gutsOfCopy(const OsiCuts& source)
{
assert( sizeRowCuts()==0 );
assert( sizeColCuts()==0 );
assert( sizeCuts()==0 );
int i;
int ne = source.sizeRowCuts();
for (i=0; i<ne; i++) insert( source.rowCut(i) );
ne = source.sizeColCuts();
for (i=0; i<ne; i++) insert( source.colCut(i) );
}
// LANNEZ SEBASTIEN added Thu May 25 01:22:51 EDT 2006
void OsiCuts::insert(const OsiCuts & cs)
{
for (OsiCuts::const_iterator it = cs.begin (); it != cs.end (); it++)
{
const OsiRowCut * rCut = dynamic_cast <const OsiRowCut * >(*it);
const OsiColCut * cCut = dynamic_cast <const OsiColCut * >(*it);
assert (rCut || cCut);
if (rCut)
insert (*rCut);
else
insert (*cCut);
}
}
int CPXPUBLIC CPX_CutCallback(CPXCENVptr xenv, void *cbdata,
int wherefrom, void *cbhandle, int *useraction_p) {
// cout << "Entering CPX Callback\n" << flush;
CPXLPptr nodelp;
CPXgetcallbacknodelp(xenv, cbdata, wherefrom, &nodelp);
CoinCallbacks* ccc = (CoinCallbacks*)cbhandle;
int length = CPXgetnumcols(xenv,nodelp) - 1; //hey, don't ask me! some VERY WIERD PHENOMENON... crap
double objVal;
double* solution = new double[length];
CPXgetcallbacknodeobjval(xenv, cbdata, wherefrom, &objVal);
CPXgetcallbacknodex(xenv, cbdata, wherefrom, solution, 0, length-1);
OsiCuts* cuts = new OsiCuts();
CoinCallbacks::CutReturn ret = ccc->cutCallback(objVal, solution, cuts);
if(ret == CoinCallbacks::CR_AddCuts) {
for(int i = cuts->sizeRowCuts(); i-->0;) {
const OsiRowCut& c = cuts->rowCut(i);
const CoinPackedVector& vec = c.row();
if(c.globallyValid())
/* Old Cplex-Versions did NOT have the last parameter (now set to "false").
* If you compile agains an older CPLEX version, simple *REMOVE*
* ", false"
* from the calls to CPXcutscallbackadd
*/
CPXcutcallbackadd(xenv, cbdata, wherefrom,
vec.getNumElements(), c.rhs(), c.sense(), vec.getIndices(), vec.getElements(), false); //default to non-purgable cuts
else
CPXcutcallbackaddlocal(xenv, cbdata, wherefrom,
vec.getNumElements(), c.rhs(), c.sense(), vec.getIndices(), vec.getElements());
cuts->eraseRowCut(i);
}
if(cuts->sizeColCuts() > 0) {
cerr << "ColCuts currently not supported...\n";
OGDF_THROW_PARAM(LibraryNotSupportedException, lnscFunctionNotImplemented);
}
}
*useraction_p = ( ret == CoinCallbacks::CR_Error) ? CPX_CALLBACK_FAIL :
( ret == CoinCallbacks::CR_AddCuts ) ? CPX_CALLBACK_SET :
CPX_CALLBACK_DEFAULT;
delete cuts;
delete[] solution;
// cout << "Leaving CPX Callback\n" << flush;
return 0; // success
}
//-------------------------------------------------------------------
// Generate Stored cuts
//-------------------------------------------------------------------
void
CglStoredUser::generateCuts(const OsiSolverInterface & si, OsiCuts & cs,
const CglTreeInfo info) const
{
// Get basic problem information
const double * solution = si.getColSolution();
if (info.inTree&&info.pass>numberPasses_) {
// only continue if integer feasible
int numberColumns=si.getNumCols();
int i;
const double * colUpper = si.getColUpper();
const double * colLower = si.getColLower();
int numberAway=0;
for (i=0;i<numberColumns;i++) {
double value = solution[i];
// In case slightly away from bounds
value = CoinMax(colLower[i],value);
value = CoinMin(colUpper[i],value);
if (si.isInteger(i)&&fabs(value-fabs(value+0.5))>1.0e-5)
numberAway++;
}
if (numberAway)
return; // let code branch
}
int numberRowCuts = cuts_.sizeRowCuts();
for (int i=0;i<numberRowCuts;i++) {
const OsiRowCut * rowCutPointer = cuts_.rowCutPtr(i);
double violation = rowCutPointer->violated(solution);
if (violation>=requiredViolation_)
cs.insert(*rowCutPointer);
}
}
/*
Append cuts to the cuts_ array in a nodeInfo. The initial reference count
is set to numberToBranchOn, which will normally be the number of arms
defined for the CbcBranchingObject attached to the CbcNode that owns this
CbcNodeInfo.
*/
void
CbcNodeInfo::addCuts (OsiCuts & cuts, int numberToBranchOn,
/*int * whichGenerator,*/int numberPointingToThis)
{
int numberCuts = cuts.sizeRowCuts();
if (numberCuts) {
int i;
if (!numberCuts_) {
cuts_ = new CbcCountRowCut * [numberCuts];
} else {
CbcCountRowCut ** temp = new CbcCountRowCut * [numberCuts+numberCuts_];
memcpy(temp, cuts_, numberCuts_*sizeof(CbcCountRowCut *));
delete [] cuts_;
cuts_ = temp;
}
for (i = 0; i < numberCuts; i++) {
CbcCountRowCut * thisCut = new CbcCountRowCut(*cuts.rowCutPtr(i),
this, numberCuts_,
-1, numberPointingToThis);
thisCut->increment(numberToBranchOn);
cuts_[numberCuts_++] = thisCut;
#ifdef CBC_DEBUG
#if CBC_DEBUG>1
int n = thisCut->row().getNumElements();
printf("Cut %d has %d entries, rhs %g %g =>", i, n, thisCut->lb(),
thisCut->ub());
int j;
const int * index = thisCut->row().getIndices();
const double * element = thisCut->row().getElements();
for (j = 0; j < n; j++) {
printf(" (%d,%g)", index[j], element[j]);
assert(fabs(element[j]) > 1.00e-12);
}
printf("\n");
#else
int n = thisCut->row().getNumElements();
int j;
const double * element = thisCut->row().getElements();
for (j = 0; j < n; j++) {
assert(fabs(element[j]) > 1.00e-12);
}
#endif
#endif
}
}
}
bool isWiped (OsiCuts &cs) {
if (cs.sizeColCuts () == 0)
//(cs.sizeColCuts () != 1))
return false;
CoinPackedVector
lbs = cs.colCutPtr (cs.sizeColCuts () - 1) -> lbs (),
ubs = cs.colCutPtr (cs.sizeColCuts () - 1) -> ubs ();
return ((lbs.getNumElements () == 1) &&
(ubs.getNumElements () == 1) &&
(*(lbs.getIndices ()) == 0) &&
(*(lbs.getElements ()) == 1.) &&
(*(ubs.getIndices ()) == 0) &&
(*(ubs.getElements ()) == -1.));
}
int
Cuts::insertAll(OsiCuts & cs, CoinRelFltEq& eq)
{
int r_val = 0;
for (unsigned int i = 0 ; i < cuts_.size() ; i++)
{
if (cuts_[i] != NULL)
{
cs.insertIfNotDuplicate(*cuts_[i], eq);
delete cuts_[i];
cuts_[i] = NULL;
r_val++;
}
}
return r_val;
}
void WipeMakeInfeas (OsiCuts &cs) {
//for (int i=cs.sizeRowCuts(); i--;) cs. eraseRowCut (i);
//for (int i=cs.sizeColCuts(); i--;) cs. eraseColCut (i);
OsiColCut *infeascut = new OsiColCut;
if (infeascut) {
int i=0;
double upper = -1., lower = +1.;
infeascut -> setLbs (1, &i, &lower);
infeascut -> setUbs (1, &i, &upper);
cs.insert (infeascut);
delete infeascut;
}
}
void
CglClique::recordClique(const int len, int* indices, OsiCuts& cs)
{
/* transform relative indices into user indices and order them */
for (int j = len - 1; j >= 0; j--)
indices[j] = sp_orig_col_ind[indices[j]];
std::sort(indices, indices + len);
OsiRowCut rowcut;
double* coef = new double[len];
std::fill(coef, coef + len, 1.0);
rowcut.setRow(len, indices, coef);
rowcut.setUb(1.0);
CoinAbsFltEq equal(1.0e-12);
cs.insertIfNotDuplicate(rowcut,equal);
delete[] coef;
}
void
CglLandP::scanExtraCuts(OsiCuts& cs, const double * colsol) const
{
int numAdded = 0;
for (int i = extraCuts_.sizeRowCuts() - 1; i > -1 ; i--)
{
double violation = extraCuts_.rowCut(i).violated(colsol);
if (violation > 0.)
{
cs.insert(extraCuts_.rowCut(i));
numAdded++;
// std::cout<<"A cut computed in a previous iteration is violated by "<<violation<<"."<<std::endl;
//extraCuts_.eraseRowCut(i);
}
}
// std::cout<<"Added "<<numAdded<<" previously generated cuts."<<std::endl;
}
void
OaDecompositionBase::OaDebug::printEndOfProcedureDebugMessage(const OsiCuts &cs,
bool foundSolution,
double solValue,
double milpBound,
bool isInteger,
bool feasible,
std::ostream & os) const{
std::cout<<"------------------------------------------------------------------"
<<std::endl;
std::cout<<"OA procedure finished"<<std::endl;
std::cout<<"Generated "<<cs.sizeRowCuts()<<std::endl;
if (foundSolution)
std::cout <<"Found NLP-integer feasible solution of value : "<<solValue<<std::endl;
std::cout<<"Current MILP lower bound is : "<<milpBound<<std::endl;
std::cout<<"-------------------------------------------------------------------"<<std::endl;
std::cout<<"Stopped because : isInteger "<<isInteger<<", feasible "<<feasible<<std::endl<<std::endl;
}
void
LinearCutsGenerator::generateCuts(const OsiSolverInterface &solver, OsiCuts &cs,
const CglTreeInfo info) const {
//const OsiTMINLPInterface * tmp = dynamic_cast<const OsiTMINLPInterface *>(&solver);
OsiTMINLPInterface * nlp = dynamic_cast<OsiTMINLPInterface *>(solver.clone());//const_cast<OsiTMINLPInterface *>(tmp);
assert(nlp);
OuterApprox oa;
//si.writeMps("toto");
int numberRows = nlp->getNumRows();
for(int i = 0 ; i < 5 ; i++){
nlp->resolve();
OsiClpSolverInterface si;
oa(*nlp, &si, solver.getColSolution(), true);
si.resolve();
OsiCuts cuts;
for(std::list<Coin::SmartPtr<CuttingMethod> >::const_iterator i = methods_.begin() ;
i != methods_.end() ; i++){
(*i)->cgl->generateCuts(si, cuts, info);
}
std::vector<OsiRowCut *> mycuts(cuts.sizeRowCuts());
for(int i = 0 ; i < cuts.sizeRowCuts() ; i++){
mycuts[i] = cuts.rowCutPtr(i);
cs.insert(*mycuts[i]);
}
nlp->applyRowCuts(mycuts.size(), const_cast<const OsiRowCut **> (&mycuts[0]));
}
// Take off slack cuts
std::vector<int> kept;
int numberRowsNow = nlp->getNumRows();
int * del = new int [numberRowsNow-numberRows];
nlp->resolve();
const double * activity = nlp->getRowActivity();
const double * lb = nlp->getRowLower();
const double * ub = nlp->getRowUpper();
CoinRelFltEq eq(1e-06);
//int nDelete=0;
for (int i=numberRowsNow -1;i>=numberRows;i--) {
if ( !(eq(activity[i], lb[i]) || eq(activity[i], ub[i])) )
cs.eraseRowCut(i - numberRows);
}
delete [] del;
delete nlp;
}
bool
BlisConGenerator::generateCons(OsiCuts & coinCuts , bool fullScan)
{
bool status = false;
if (strategy_ == -2) {
// This con generator has been disabled.
return false;
}
OsiSolverInterface * solver = model_->solver();
#if defined(BLIS_DEBUG_MORE)
std::cout << "model_->getNodeCount() = " << model_->getNodeCount()
<< std::endl;
#endif
if ( fullScan ||
((strategy_ > 0) && (model_->getNumNodes() % strategy_) == 0) ) {
//--------------------------------------------------
// Start to generate cons ...
//--------------------------------------------------
int j;
double start = CoinCpuTime();
int numConsBefore = coinCuts.sizeCuts();
int numRowsBefore = coinCuts.sizeRowCuts();
assert(generator_ != NULL);
CglProbing* generator = dynamic_cast<CglProbing *>(generator_);
if (!generator) {
generator_->generateCuts(*solver, coinCuts);
}
else {
// It is probing - return tight column bound
CglTreeInfo info;
generator->generateCutsAndModify(*solver, coinCuts, &info);
const double * tightLower = generator->tightLower();
const double * lower = solver->getColLower();
const double * tightUpper = generator->tightUpper();
const double * upper = solver->getColUpper();
const double * solution = solver->getColSolution();
int numberColumns = solver->getNumCols();
double primalTolerance = 1.0e-8;
for (j = 0; j < numberColumns; ++j) {
if ( (tightUpper[j] == tightLower[j]) &&
(upper[j] > lower[j]) ) {
// fix column j
solver->setColLower(j, tightLower[j]);
solver->setColUpper(j, tightUpper[j]);
if ( (tightLower[j] > solution[j] + primalTolerance) ||
(tightUpper[j] < solution[j] - primalTolerance) ) {
status = true;
}
}
}
} // EOF probing.
//--------------------------------------------------
// Remove zero length row cuts.
//--------------------------------------------------
int numRowCons = coinCuts.sizeRowCuts();
for (j = numRowsBefore; j < numRowCons; ++j) {
OsiRowCut & rCut = coinCuts.rowCut(j);
int len = rCut.row().getNumElements();
#ifdef BLIS_DEBUG_MORE
std::cout << "Cut " << j<<": length = " << len << std::endl;
#endif
if (len == 0) {
// Empty cuts
coinCuts.eraseRowCut(j);
--j;
--numRowCons;
#ifdef BLIS_DEBUG
std::cout << "WARNING: Empty cut from " << name_ << std::endl;
#endif
}
else if (len < 0) {
#ifdef BLIS_DEBUG
std::cout << "ERROR: Cut length = " << len << std::endl;
#endif
// Error
assert(0);
}
}
//--------------------------------------------------
// Update statistics.
//--------------------------------------------------
++calls_;
numConsGenerated_ += (coinCuts.sizeCuts() - numConsBefore);
time_ += (CoinCpuTime() - start);
if (numConsGenerated_ == 0) {
++noConsCalls_;
}
}
return status;
}
/** Perform a branch-and-bound on given setup.*/
void CouenneBab::branchAndBound (Bonmin::BabSetupBase & s) {
double remaining_time = s.getDoubleParameter(Bonmin::BabSetupBase::MaxTime) + CoinCpuTime();
/* Put a link to this into solver.*/
OsiBabSolver * babInfo = dynamic_cast<OsiBabSolver *>(s.continuousSolver()->getAuxiliaryInfo());
assert(babInfo);
Bonmin::BabInfo * bonBabInfoPtr = dynamic_cast<Bonmin::BabInfo*>(babInfo);
if (bonBabInfoPtr == NULL) { //Replace with a Bonmin::babInfo
bonBabInfoPtr = new Bonmin::BabInfo(*babInfo);
s.continuousSolver()->setAuxiliaryInfo(bonBabInfoPtr);
delete bonBabInfoPtr;
bonBabInfoPtr = dynamic_cast<Bonmin::BabInfo*>(s.continuousSolver()->getAuxiliaryInfo());
}
bonBabInfoPtr->setBabPtr(this);
s.nonlinearSolver()->solver()->setup_global_time_limit(s.getDoubleParameter(Bonmin::BabSetupBase::MaxTime));
OsiSolverInterface * solver = s.continuousSolver()->clone();
delete modelHandler_;
modelHandler_ = s.continuousSolver()->messageHandler()->clone();
model_.passInMessageHandler(modelHandler_);
model_.assignSolver(solver, true);
// s.continuousSolver() = model_.solver();
// if(s.continuousSolver()->objects()!=NULL){
// model_.addObjects(s.continuousSolver()->numberObjects(),s.continuousSolver()->objects());
// }
int specOpt = s.getIntParameter(Bonmin::BabSetupBase::SpecialOption);
if (specOpt) {
model_.setSpecialOptions(specOpt);
if (specOpt==16) {
Bonmin::CbcNlpStrategy strat(s.getIntParameter(Bonmin::BabSetupBase::MaxFailures),
s.getIntParameter(Bonmin::BabSetupBase::MaxInfeasible),
s.getIntParameter(Bonmin::BabSetupBase::FailureBehavior));
model_.setStrategy(strat);
}
}
model_.setMaximumCutPasses(s.getIntParameter(Bonmin::BabSetupBase::NumCutPasses));
model_.setMaximumCutPassesAtRoot(s.getIntParameter(Bonmin::BabSetupBase::NumCutPassesAtRoot));
//Setup cutting plane methods
for (Bonmin::BabSetupBase::CuttingMethods::iterator i = s.cutGenerators().begin() ;
i != s.cutGenerators().end() ; i++) {
Bonmin::OaDecompositionBase * oa = dynamic_cast<Bonmin::OaDecompositionBase *>(i->cgl);
if (oa && oa->reassignLpsolver())
oa->assignLpInterface(model_.solver());
model_.addCutGenerator(i->cgl,i->frequency,i->id.c_str(), i->normal,
i->atSolution);
if(i->always){
model_.cutGenerators()[model_.numberCutGenerators()-1]
->setMustCallAgain(true);
}
}
for (Bonmin::BabSetupBase::HeuristicMethods::iterator i = s.heuristics().begin() ;
i != s.heuristics().end() ; i++) {
CbcHeuristic * heu = i->heuristic;
heu->setModel(&model_);
model_.addHeuristic(heu, i->id.c_str());
}
//need to record solver logLevel here
int logLevel = s.continuousSolver()->messageHandler()->logLevel();
//Set true branch-and-bound parameters
model_.setLogLevel(s.getIntParameter(Bonmin::BabSetupBase::BabLogLevel));
// Put back solver logLevel
model_.solver()->messageHandler()->setLogLevel(logLevel);
model_.setPrintFrequency(s.getIntParameter(Bonmin::BabSetupBase::BabLogInterval));
bool ChangedObject = false;
//Pass over user set branching priorities to Cbc
if (s.continuousSolver()->objects()==NULL) {
//assert (s.branchingMethod() == NULL);
const OsiTMINLPInterface * nlpSolver = s.nonlinearSolver();
//set priorities, prefered directions...
const int * priorities = nlpSolver->getPriorities();
const double * upPsCosts = nlpSolver->getUpPsCosts();
const double * downPsCosts = nlpSolver->getDownPsCosts();
const int * directions = nlpSolver->getBranchingDirections();
bool hasPseudo = (upPsCosts!=NULL);
model_.findIntegers(true,hasPseudo);
OsiObject ** simpleIntegerObjects = model_.objects();
int numberObjects = model_.numberObjects();
if (priorities != NULL || directions != NULL || hasPseudo) {
ChangedObject = true;
for (int i = 0 ; i < numberObjects ; i++) {
CbcObject * object = dynamic_cast<CbcObject *>
(simpleIntegerObjects[i]);
int iCol = object->columnNumber();
if (priorities)
object->setPriority(priorities[iCol]);
if (directions)
object->setPreferredWay(directions[iCol]);
if (upPsCosts) {
CbcSimpleIntegerPseudoCost * pscObject =
dynamic_cast<CbcSimpleIntegerPseudoCost*> (object);
pscObject->setUpPseudoCost(upPsCosts[iCol]);
pscObject->setDownPseudoCost(downPsCosts[iCol]);
}
}
}
#if 1
// Now pass user set Sos constraints (code inspired from CoinSolve.cpp)
const TMINLP::SosInfo * sos = s.nonlinearSolver()->model()->sosConstraints();
if (!s.getIntParameter(Bonmin::BabSetupBase::DisableSos) && sos && sos->num > 0) {
// we have some sos constraints
const OsiTMINLPInterface * nlpSolver = s.nonlinearSolver();
const int & numSos = sos->num;
(*nlpSolver->messageHandler())<<"Adding "<<sos->num<<" sos constraints."
<<CoinMessageEol;
CbcObject ** objects = new CbcObject*[numSos];
const int * starts = sos->starts;
const int * indices = sos->indices;
const char * types = sos->types;
const double * weights = sos->weights;
//verify if model has user set priorities
bool hasPriorities = false;
const int * varPriorities = nlpSolver->getPriorities();
int numberObjects = model_.numberObjects();
if (varPriorities)
{
for (int i = 0 ; i < numberObjects ; i++) {
if (varPriorities[i]) {
hasPriorities = true;
break;
}
}
}
const int * sosPriorities = sos->priorities;
if (sosPriorities)
{
for (int i = 0 ; i < numSos ; i++) {
if (sosPriorities[i]) {
hasPriorities = true;
break;
}
}
}
for (int i = 0 ; i < numSos ; i++)
{
int start = starts[i];
int length = starts[i + 1] - start;
#ifdef DO_IT_NWAY
printf("setting nway object\n"),
objects[i] = new CbcNWay(&model_, length, &indices[start],
i);
objects[i]->setPriority(1);
#else
objects[i] = new CbcSOS(&model_, length, &indices[start],
&weights[start], i, types[i]);
objects[i]->setPriority(10);
#endif
if (hasPriorities && sosPriorities && sosPriorities[i]) {
objects[i]->setPriority(sosPriorities[i]);
}
}
model_.addObjects (numSos, objects);
for (int i = 0 ; i < numSos ; i++)
delete objects[i];
delete [] objects;
}
#endif
//If Setup contains more objects add them to Cbc
if (s.objects().size()) {
CbcObject ** objects = new CbcObject *[s.objects().size()];
for (unsigned int i = 0 ; i < s.objects().size() ; i++) {
objects[i] = dynamic_cast<CbcObject *> (s.objects()[i]);
assert(objects[i]);
objects[i]->setModel(&model_);
}
model_.addObjects ((int) s.objects().size(), objects);
delete [] objects;
}
replaceIntegers(model_.objects(), model_.numberObjects());
} else { // Pass in objects to Cbc
// Redundant definition of default branching (as Default == User)
assert (s.branchingMethod() != NULL);
// Add nonlinear and integer objects (need to add OsiSOS)
model_.addObjects (s.continuousSolver () -> numberObjects (), s.continuousSolver () -> objects ());
// Now model_ has only CouenneObjects and SOS objects
// for (int i=0; i<nco; i++)
// if (!(dynamic_cast <CbcSimpleInteger *> (s.continuousSolver () -> objects () [i])))
// model_ . objects () [nRealObj++] = s.continuousSolver () -> objects () [i] -> clone ();
CbcBranchDefaultDecision branch;
s.branchingMethod()->setSolver(model_.solver());
BonChooseVariable * strong2 = dynamic_cast<BonChooseVariable *>(s.branchingMethod());
if (strong2)
strong2->setCbcModel(&model_);
branch.setChooseMethod(*s.branchingMethod());
model_.setBranchingMethod(&branch);
// prevent duplicating object when copying in CbcModel.cpp
model_.solver()->deleteObjects();
}
model_.setDblParam(CbcModel::CbcCutoffIncrement, s.getDoubleParameter(Bonmin::BabSetupBase::CutoffDecr));
model_.setCutoff(s.getDoubleParameter(Bonmin::BabSetupBase::Cutoff) + CUTOFF_TOL);
model_.setDblParam(CbcModel::CbcAllowableGap, s.getDoubleParameter(Bonmin::BabSetupBase::AllowableGap));
model_.setDblParam(CbcModel::CbcAllowableFractionGap, s.getDoubleParameter(Bonmin::BabSetupBase::AllowableFractionGap));
// Definition of node selection strategy
if (s.nodeComparisonMethod()==Bonmin::BabSetupBase::bestBound) {
CbcCompareObjective compare;
model_.setNodeComparison(compare);
}
else if (s.nodeComparisonMethod()==Bonmin::BabSetupBase::DFS) {
CbcCompareDepth compare;
model_.setNodeComparison(compare);
}
else if (s.nodeComparisonMethod()==Bonmin::BabSetupBase::BFS) {
CbcCompareDefault compare;
compare.setWeight(0.0);
model_.setNodeComparison(compare);
}
else if (s.nodeComparisonMethod()==Bonmin::BabSetupBase::dynamic) {
CbcCompareDefault compare;
model_.setNodeComparison(compare);
}
else if (s.nodeComparisonMethod()==Bonmin::BabSetupBase::bestGuess) {
// Right now, this is a mess. We need a separation of the
// pseudo costs from the ChooseVariable method
CbcCompareEstimate compare;
model_.setNodeComparison(compare);
GuessHeuristic * guessHeu = new GuessHeuristic(model_);
model_.addHeuristic(guessHeu);
delete guessHeu;
}
if (s.treeTraversalMethod() == Bonmin::BabSetupBase::HeapOnly) {
//Do nothing this is the default of Cbc.
}
else if (s.treeTraversalMethod() == Bonmin::BabSetupBase::DiveFromBest) {
CbcDiver treeTraversal;
treeTraversal.initialize(s);
model_.passInTreeHandler(treeTraversal);
}
else if (s.treeTraversalMethod() == Bonmin::BabSetupBase::ProbedDive) {
CbcProbedDiver treeTraversal;
treeTraversal.initialize(s);
model_.passInTreeHandler(treeTraversal);
}
else if (s.treeTraversalMethod() == Bonmin::BabSetupBase::DfsDiveFromBest) {
CbcDfsDiver treeTraversal;
treeTraversal.initialize(s);
model_.passInTreeHandler(treeTraversal);
}
else if (s.treeTraversalMethod() == Bonmin::BabSetupBase::DfsDiveDynamic) {
CbcDfsDiver treeTraversal;
treeTraversal.initialize(s);
model_.passInTreeHandler(treeTraversal);
DiverCompare compare;
compare.setComparisonDive(*model_.nodeComparison());
compare.setComparisonBound(CbcCompareObjective());
CbcDfsDiver * dfs = dynamic_cast<CbcDfsDiver *> (model_.tree());
assert(dfs);
compare.setDiver(dfs);
model_.setNodeComparison(compare);
}
model_.setNumberStrong(s.getIntParameter(Bonmin::BabSetupBase::NumberStrong));
model_.setNumberBeforeTrust(s.getIntParameter(Bonmin::BabSetupBase::MinReliability));
model_.setNumberPenalties(8);
model_.setDblParam(CbcModel::CbcMaximumSeconds, s.getDoubleParameter(Bonmin::BabSetupBase::MaxTime));
model_.setMaximumNodes(s.getIntParameter(Bonmin::BabSetupBase::MaxNodes));
model_.setMaximumNumberIterations(s.getIntParameter(Bonmin::BabSetupBase::MaxIterations));
model_.setMaximumSolutions(s.getIntParameter(Bonmin::BabSetupBase::MaxSolutions));
model_.setIntegerTolerance(s.getDoubleParameter(Bonmin::BabSetupBase::IntTol));
//Get objects from model_ if it is not null means there are some sos constraints or non-integer branching object
// pass them to cut generators.
OsiObject ** objects = model_.objects();
if (specOpt!=16 && objects) {
int numberObjects = model_.numberObjects();
if (objects_ != NULL) {
for (int i = 0 ; i < nObjects_; i++)
delete objects_[i];
}
delete [] objects_;
objects_ = new OsiObject*[numberObjects];
nObjects_ = numberObjects;
for (int i = 0 ; i < numberObjects; i++) {
OsiObject * obj = objects[i];
CbcSimpleInteger * intObj = dynamic_cast<CbcSimpleInteger *> (obj);
if (intObj) {
objects_[i] = intObj->osiObject();
}
else {
CbcSOS * sosObj = dynamic_cast<CbcSOS *>(obj);
if (sosObj) objects_[i] = sosObj->osiObject(model_.solver());
else {//Maybe an unsupported CbcObject
CbcObject * cbcObj = dynamic_cast<CbcObject *>(obj);
if (cbcObj) {
std::cerr<<"Unsupported CbcObject appears in the code"<<std::endl;
throw UNSUPPORTED_CBC_OBJECT;
}
else {//It has to be an OsiObject.
objects_[i]=obj->clone();
}
}
}
}
CbcCutGenerator ** gen = model_.cutGenerators();
int numGen = model_.numberCutGenerators();
for (int i = 0 ; i < numGen ; i++) {
Bonmin::OaDecompositionBase * oa = dynamic_cast<Bonmin::OaDecompositionBase * >(gen[i]->generator());
// if (oa)
// printf ("\n\n\nat least one OADecompBase\n\n\n");
if (oa) // pass objects
oa->setObjects(objects_,nObjects_);
}
}
// if (objects_) {
// for (int i = 0 ; i < nObjects_; i++)
// delete objects_ [i];
// delete [] objects_;
// }
// OsiObject ** objects = model_.objects();
// int numObjects = model_.numberObjects();
// nObjects_ = 0;
// objects_ = new OsiObject* [numObjects];
// for (int i=0; i < numObjects; ++i)
// if (objects [i])
// objects_ [nObjects_++] = objects [i] -> clone ();
try {
//Get the time and start.
{
OsiTMINLPInterface * tmpOsi = NULL;
if(s.nonlinearSolver() == s.continuousSolver()){
tmpOsi = dynamic_cast<OsiTMINLPInterface *> (model_.solver());
tmpOsi->forceSolverOutput(s.getIntParameter(Bonmin::BabSetupBase::RootLogLevel));
}
model_.initialSolve();
if(tmpOsi != NULL){
tmpOsi->setSolverOutputToDefault();
}
}
int ival;
s.options()->GetEnumValue("enable_dynamic_nlp", ival, "bonmin.");
if(s.nonlinearSolver() == s.continuousSolver() && ival) {
if(!model_.solver()->isProvenOptimal() ){//Something went wrong check if objective is linear and alternate model
// can be solved
OsiTMINLPInterface * tmpOsi = dynamic_cast<OsiTMINLPInterface *> (model_.solver());
TMINLPLinObj * tmp_tminlp = dynamic_cast<TMINLPLinObj *> (tmpOsi->model());
tmpOsi->setModel(tmp_tminlp->tminlp());
model_.initialSolve();
}
else {
LinearCutsGenerator cgl;
cgl.initialize(s);
OsiCuts cuts;
cgl.generateCuts(*model_.solver(), cuts);
std::vector<const OsiRowCut *> mycuts(cuts.sizeRowCuts());
for(int i = 0 ; i < cuts.sizeRowCuts() ; i++){
mycuts[i] = cuts.rowCutPtr(i);
}
model_. solver () -> applyRowCuts ((int) mycuts.size(), (const OsiRowCut **) &mycuts[0]);
}
//Added by Claudia
OsiTMINLPInterface * nlpSolver = dynamic_cast<OsiTMINLPInterface *>(model_.solver());
if(nlpSolver && nlpSolver->getNewCutoffDecr()!=COIN_DBL_MAX)
model_.setDblParam(CbcModel::CbcCutoffIncrement, nlpSolver->getNewCutoffDecr());
model_.solver()->resolve();
}
// for Couenne
model_.passInSolverCharacteristics (bonBabInfoPtr);
continuousRelaxation_ =model_.solver()->getObjValue();
if (specOpt==16)//Set warm start point for Ipopt
{
#if 1
const double * colsol = model_.solver()->getColSolution();
const double * duals = model_.solver()->getRowPrice();
OsiTMINLPInterface * tnlpSolver = dynamic_cast<OsiTMINLPInterface *>(model_.solver());
// Primal dual point is not copied if one (supposedly a better one) has already been put into the solver.
if(tnlpSolver->problem()->has_x_init() != 2){
model_.solver()->setColSolution(colsol);
model_.solver()->setRowPrice(duals);
}
#else
OsiTMINLPInterface * tnlpSolver = dynamic_cast<OsiTMINLPInterface *>(model_.solver());
CoinWarmStart * warm = tnlpSolver->solver()->getWarmStart(tnlpSolver->problem());
tnlpSolver->solver()->setWarmStart(warm, tnlpSolver->problem());
delete warm;
#endif
#if 0 // Sometimes primal dual point is problematic in the context of Cut-and-branch
model_.solver()->resolve();
if(!model_.solver()->isProvenOptimal())
model_.solver()->setColSolution(NULL);
#endif
}
#ifdef SIGNAL
CoinSighandler_t saveSignal = SIG_DFL;
// register signal handler
saveSignal = signal (SIGINT,couenne_signal_handler);
currentBranchModel = &model_;
#endif
// to get node parent info in Cbc, pass parameter 3.
//model_.branchAndBound(3);
remaining_time -= CoinCpuTime();
model_.setDblParam(CbcModel::CbcMaximumSeconds, remaining_time);
if(remaining_time > 0.)
model_.branchAndBound();
}
catch(TNLPSolver::UnsolvedError *E){
s.nonlinearSolver()->model()->finalize_solution
(TMINLP::MINLP_ERROR, 0, NULL, DBL_MAX);
throw E;
}
numNodes_ = model_.getNodeCount();
bestObj_ = model_.getObjValue();
bestBound_ = model_.getBestPossibleObjValue();
mipIterationCount_ = model_.getIterationCount();
bool hasFailed = false;
if (specOpt==16)//Did we continue branching on a failure
{
CbcNlpStrategy * nlpStrategy = dynamic_cast<CbcNlpStrategy *>(model_.strategy());
if (nlpStrategy)
hasFailed = nlpStrategy->hasFailed();
else
throw -1;
}
else
hasFailed = s.nonlinearSolver()->hasContinuedOnAFailure();
// Output summarizing cut generators (taken from CbcSolver.cpp)
// ToDo put into proper print level
int numberGenerators = model_.numberCutGenerators();
for (int iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
CbcCutGenerator * generator = model_.cutGenerator(iGenerator);
//CglStored * stored = dynamic_cast<CglStored*>(generator->generator());
if (true&&!(generator->numberCutsInTotal() || generator->numberColumnCuts()))
continue;
if(modelHandler_->logLevel() >= 1) {
*modelHandler_ << generator->cutGeneratorName()
<< "was tried" << generator->numberTimesEntered()
<< "times and created" << generator->numberCutsInTotal()+generator->numberColumnCuts()
<< "cuts of which" << generator->numberCutsActive()
<< "were active after adding rounds of cuts";
// if (generator->timing()) {
// char timebuf[20];
// sprintf(timebuf, "(%.3fs)", generator->timeInCutGenerator());
// *modelHandler_ << timebuf << CoinMessageEol;
// }
// else {
// *modelHandler_ << CoinMessageEol;
// }
}
}
TMINLP::SolverReturn status = TMINLP::MINLP_ERROR;
if (model_.numberObjects()==0) {
if (bestSolution_)
delete [] bestSolution_;
OsiSolverInterface * solver =
(s.nonlinearSolver() == s.continuousSolver())?
model_.solver() : s.nonlinearSolver();
bestSolution_ = new double[solver->getNumCols()];
CoinCopyN(solver->getColSolution(), solver->getNumCols(),
bestSolution_);
bestObj_ = bestBound_ = solver->getObjValue();
}
if (bonBabInfoPtr->bestSolution2().size() > 0) {
assert((int) bonBabInfoPtr->bestSolution2().size() == s.nonlinearSolver()->getNumCols());
if (bestSolution_)
delete [] bestSolution_;
bestSolution_ = new double[s.nonlinearSolver()->getNumCols()];
std::copy(bonBabInfoPtr->bestSolution2().begin(), bonBabInfoPtr->bestSolution2().end(),
bestSolution_);
bestObj_ = (bonBabInfoPtr->bestObj2());
(*s.nonlinearSolver()->messageHandler())<<"\nReal objective function: "
<<bestObj_<<CoinMessageEol;
}
else if (model_.bestSolution()) {
if (bestSolution_)
delete [] bestSolution_;
bestSolution_ = new double[s.nonlinearSolver()->getNumCols()];
CoinCopyN(model_.bestSolution(), s.nonlinearSolver()->getNumCols(), bestSolution_);
}
if(remaining_time <= 0.){
status = TMINLP::LIMIT_EXCEEDED;
if (bestSolution_) {
mipStatus_ = Feasible;
}
else {
mipStatus_ = NoSolutionKnown;
}
}
else if (model_.status() == 0) {
if(model_.isContinuousUnbounded()){
status = TMINLP::CONTINUOUS_UNBOUNDED;
mipStatus_ = UnboundedOrInfeasible;
}
else
if (bestSolution_) {
status = TMINLP::SUCCESS;
mipStatus_ = FeasibleOptimal;
}
else {
status = TMINLP::INFEASIBLE;
mipStatus_ = ProvenInfeasible;
}
}
else if (model_.status() == 1 || model_.status() == 5) {
#if (BONMIN_VERSION_MAJOR > 1) || (BONMIN_VERSION_MINOR > 6)
status = model_.status() == 1 ? TMINLP::LIMIT_EXCEEDED : TMINLP::USER_INTERRUPT;
#else
status = TMINLP::LIMIT_EXCEEDED;
#endif
if (bestSolution_) {
mipStatus_ = Feasible;
}
else {
mipStatus_ = NoSolutionKnown;
}
}
else if (model_.status()==2) {
status = TMINLP::MINLP_ERROR;
}
// Which solution should we use? false if RBS's, true if Cbc's
bool use_RBS_Cbc =
!problem_ ||
!(problem_ -> getRecordBestSol ()) ||
!(problem_ -> getRecordBestSol () -> getHasSol()) ||
(((fabs (bestObj_) < COUENNE_INFINITY / 1e4) &&
(problem_ -> getRecordBestSol () -> getVal () > bestObj_)));
/* if we do not pass the cbc solution and problem_ -> getRecordBestSol () -> getHasSol() is true, then there should be a solution vector in problem_ -> getRecordBestSol () */
assert(use_RBS_Cbc || problem_ -> getRecordBestSol () -> getSol() != NULL);
s.nonlinearSolver () -> model () -> finalize_solution
(status,
s.nonlinearSolver () -> getNumCols (),
use_RBS_Cbc ? bestSolution_ : problem_ -> getRecordBestSol () -> getSol (),
use_RBS_Cbc ? bestObj_ : problem_ -> getRecordBestSol () -> getVal ());
}
// Generate cuts
void
CglFakeClique::generateCuts(const OsiSolverInterface& si, OsiCuts & cs,
const CglTreeInfo info)
{
if (fakeSolver_) {
assert (si.getNumCols()==fakeSolver_->getNumCols());
fakeSolver_->setColLower(si.getColLower());
const double * solution = si.getColSolution();
fakeSolver_->setColSolution(solution);
fakeSolver_->setColUpper(si.getColUpper());
// get and set branch and bound cutoff
double cutoff;
si.getDblParam(OsiDualObjectiveLimit,cutoff);
fakeSolver_->setDblParam(OsiDualObjectiveLimit,COIN_DBL_MAX);
#ifdef COIN_HAS_CLP
OsiClpSolverInterface * clpSolver
= dynamic_cast<OsiClpSolverInterface *> (fakeSolver_);
if (clpSolver) {
// fix up fake solver
const ClpSimplex * siSimplex = clpSolver->getModelPtr();
// need to set djs
memcpy(siSimplex->primalColumnSolution(),
si.getReducedCost(),si.getNumCols()*sizeof(double));
fakeSolver_->setDblParam(OsiDualObjectiveLimit,cutoff);
}
#endif
const CoinPackedMatrix * matrixByRow = si.getMatrixByRow();
const double * elementByRow = matrixByRow->getElements();
const int * column = matrixByRow->getIndices();
const CoinBigIndex * rowStart = matrixByRow->getVectorStarts();
const int * rowLength = matrixByRow->getVectorLengths();
const double * rowUpper = si.getRowUpper();
const double * rowLower = si.getRowLower();
// Scan all rows looking for possibles
int numberRows = si.getNumRows();
double tolerance = 1.0e-3;
for (int iRow=0;iRow<numberRows;iRow++) {
CoinBigIndex start = rowStart[iRow];
CoinBigIndex end = start + rowLength[iRow];
double upRhs = rowUpper[iRow];
double loRhs = rowLower[iRow];
double sum = 0.0;
for (CoinBigIndex j=start;j<end;j++) {
int iColumn=column[j];
double value = elementByRow[j];
sum += solution[iColumn]*value;
}
if (sum<loRhs-tolerance||sum>upRhs+tolerance) {
// add as cut
OsiRowCut rc;
rc.setLb(loRhs);
rc.setUb(upRhs);
rc.setRow(end-start,column+start,elementByRow+start,false);
CoinAbsFltEq equal(1.0e-12);
cs.insertIfNotDuplicate(rc,equal);
}
}
CglClique::generateCuts(*fakeSolver_,cs,info);
if (probing_) {
probing_->generateCuts(*fakeSolver_,cs,info);
}
} else {
// just use real solver
CglClique::generateCuts(si,cs,info);
}
}
//--------------------------------------------------------------------------
// test solution methods.
void OsiCbcSolverInterfaceUnitTest(const std::string & mpsDir, const std::string & netlibDir)
{
{
CoinRelFltEq eq;
OsiCbcSolverInterface m;
std::string fn = mpsDir+"exmip1";
m.readMps(fn.c_str(),"mps");
{
OsiCbcSolverInterface im;
OSIUNITTEST_ASSERT_ERROR(im.getNumCols() == 0, {}, "cbc", "default constructor");
OSIUNITTEST_ASSERT_ERROR(im.getModelPtr() != NULL, {}, "cbc", "default constructor");
}
// Test copy constructor and assignment operator
{
OsiCbcSolverInterface lhs;
{
OsiCbcSolverInterface im(m);
OsiCbcSolverInterface imC1(im);
OSIUNITTEST_ASSERT_ERROR(imC1.getModelPtr() != im.getModelPtr(), {}, "cbc", "copy constructor");
OSIUNITTEST_ASSERT_ERROR(imC1.getNumCols() == im.getNumCols(), {}, "cbc", "copy constructor");
OSIUNITTEST_ASSERT_ERROR(imC1.getNumRows() == im.getNumRows(), {}, "cbc", "copy constructor");
OsiCbcSolverInterface imC2(im);
OSIUNITTEST_ASSERT_ERROR(imC2.getModelPtr() != im.getModelPtr(), {}, "cbc", "copy constructor");
OSIUNITTEST_ASSERT_ERROR(imC2.getNumCols() == im.getNumCols(), {}, "cbc", "copy constructor");
OSIUNITTEST_ASSERT_ERROR(imC2.getNumRows() == im.getNumRows(), {}, "cbc", "copy constructor");
OSIUNITTEST_ASSERT_ERROR(imC1.getModelPtr() != imC2.getModelPtr(), {}, "cbc", "copy constructor");
lhs = imC2;
}
// Test that lhs has correct values even though rhs has gone out of scope
OSIUNITTEST_ASSERT_ERROR(lhs.getModelPtr() != m.getModelPtr(), {}, "cbc", "assignment operator");
OSIUNITTEST_ASSERT_ERROR(lhs.getNumCols() == m.getNumCols(), {}, "cbc", "copy constructor");
OSIUNITTEST_ASSERT_ERROR(lhs.getNumRows() == m.getNumRows(), {}, "cbc", "copy constructor");
}
// Test clone
{
OsiCbcSolverInterface cbcSi(m);
OsiSolverInterface * siPtr = &cbcSi;
OsiSolverInterface * siClone = siPtr->clone();
OsiCbcSolverInterface * cbcClone = dynamic_cast<OsiCbcSolverInterface*>(siClone);
OSIUNITTEST_ASSERT_ERROR(cbcClone != NULL, {}, "cbc", "clone");
OSIUNITTEST_ASSERT_ERROR(cbcClone->getModelPtr() != cbcSi.getModelPtr(), {}, "cbc", "clone");
OSIUNITTEST_ASSERT_ERROR(cbcClone->getNumRows() == cbcSi.getNumRows(), {}, "cbc", "clone");
OSIUNITTEST_ASSERT_ERROR(cbcClone->getNumCols() == m.getNumCols(), {}, "cbc", "clone");
delete siClone;
}
// test infinity
{
OsiCbcSolverInterface si;
OSIUNITTEST_ASSERT_ERROR(si.getInfinity() == OsiCbcInfinity, {}, "cbc", "infinity");
}
// Test some catches
if (!OsiCbcHasNDEBUG())
{
OsiCbcSolverInterface solver;
try {
solver.setObjCoeff(0,0.0);
OSIUNITTEST_ADD_OUTCOME("cbc", "setObjCoeff on empty model", "should throw exception", OsiUnitTest::TestOutcome::ERROR, false);
}
catch (CoinError e) {
if (OsiUnitTest::verbosity >= 1)
std::cout<<"Correct throw from setObjCoeff on empty model"<<std::endl;
}
std::string fn = mpsDir+"exmip1";
solver.readMps(fn.c_str(),"mps");
OSIUNITTEST_CATCH_ERROR(solver.setObjCoeff(0,0.0), {}, "cbc", "setObjCoeff on nonempty model");
try {
int index[]={0,20};
double value[]={0.0,0.0,0.0,0.0};
solver.setColSetBounds(index,index+2,value);
OSIUNITTEST_ADD_OUTCOME("cbc", "setColSetBounds on cols not in model", "should throw exception", OsiUnitTest::TestOutcome::ERROR, false);
}
catch (CoinError e) {
if (OsiUnitTest::verbosity >= 1)
std::cout<<"Correct throw from setObjCoeff on empty model"<<std::endl;
}
}
{
OsiCbcSolverInterface cbcSi(m);
int nc = cbcSi.getNumCols();
int nr = cbcSi.getNumRows();
const double * cl = cbcSi.getColLower();
const double * cu = cbcSi.getColUpper();
const double * rl = cbcSi.getRowLower();
const double * ru = cbcSi.getRowUpper();
OSIUNITTEST_ASSERT_ERROR(nc == 8, return, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(nr == 5, return, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cl[0],2.5), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cl[1],0.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cu[1],4.1), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cu[2],1.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(rl[0],2.5), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(rl[4],3.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(ru[1],2.1), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(ru[4],15.), {}, "cbc", "read and copy exmip1");
const double * cs = cbcSi.getColSolution();
OSIUNITTEST_ASSERT_ERROR(eq(cs[0],2.5), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cs[7],0.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(!eq(cl[3],1.2345), {}, "cbc", "set col lower");
cbcSi.setColLower( 3, 1.2345 );
OSIUNITTEST_ASSERT_ERROR( eq(cbcSi.getColLower()[3],1.2345), {}, "cbc", "set col lower");
OSIUNITTEST_ASSERT_ERROR(!eq(cbcSi.getColUpper()[4],10.2345), {}, "cbc", "set col upper");
cbcSi.setColUpper( 4, 10.2345 );
OSIUNITTEST_ASSERT_ERROR( eq(cbcSi.getColUpper()[4],10.2345), {}, "cbc", "set col upper");
// LH: Objective will depend on how underlying solver constructs and maintains initial solution
double objValue = cbcSi.getObjValue();
OSIUNITTEST_ASSERT_ERROR(eq(objValue,3.5) || eq(objValue,10.5), {}, "cbc", "getObjValue() before solve");
OSIUNITTEST_ASSERT_ERROR(eq(cbcSi.getObjCoefficients()[0], 1.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cbcSi.getObjCoefficients()[1], 0.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cbcSi.getObjCoefficients()[2], 0.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cbcSi.getObjCoefficients()[3], 0.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cbcSi.getObjCoefficients()[4], 2.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cbcSi.getObjCoefficients()[5], 0.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cbcSi.getObjCoefficients()[6], 0.0), {}, "cbc", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cbcSi.getObjCoefficients()[7],-1.0), {}, "cbc", "read and copy exmip1");
}
// Test matrixByRow method
{
const OsiCbcSolverInterface si(m);
const CoinPackedMatrix * smP = si.getMatrixByRow();
OSIUNITTEST_ASSERT_ERROR(smP->getMajorDim() == 5, return, "cbc", "getMatrixByRow: major dim");
OSIUNITTEST_ASSERT_ERROR(smP->getMinorDim() == 8, return, "cbc", "getMatrixByRow: major dim");
OSIUNITTEST_ASSERT_ERROR(smP->getNumElements() == 14, return, "cbc", "getMatrixByRow: num elements");
OSIUNITTEST_ASSERT_ERROR(smP->getSizeVectorStarts() == 6, return, "cbc", "getMatrixByRow: num elements");
#ifdef OSICBC_TEST_MTX_STRUCTURE
CoinRelFltEq eq;
const double * ev = smP->getElements();
OSIUNITTEST_ASSERT_ERROR(eq(ev[0], 3.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[1], 1.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[2], -2.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[3], -1.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[4], -1.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[5], 2.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[6], 1.1), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[7], 1.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[8], 1.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[9], 2.8), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[10], -1.2), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[11], 5.6), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[12], 1.0), {}, "cbc", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[13], 1.9), {}, "cbc", "getMatrixByRow: elements");
const int * mi = smP->getVectorStarts();
OSIUNITTEST_ASSERT_ERROR(mi[0] == 0, {}, "cbc", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[1] == 5, {}, "cbc", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[2] == 7, {}, "cbc", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[3] == 9, {}, "cbc", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[4] == 11, {}, "cbc", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[5] == 14, {}, "cbc", "getMatrixByRow: vector starts");
const int * ei = smP->getIndices();
OSIUNITTEST_ASSERT_ERROR(ei[ 0] == 0, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 1] == 1, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 2] == 3, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 3] == 4, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 4] == 7, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 5] == 1, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 6] == 2, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 7] == 2, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 8] == 5, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 9] == 3, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[10] == 6, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[11] == 0, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[12] == 4, {}, "cbc", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[13] == 7, {}, "cbc", "getMatrixByRow: indices");
#else // OSICBC_TEST_MTX_STRUCTURE
CoinPackedMatrix exmip1Mtx ;
exmip1Mtx.reverseOrderedCopyOf(BuildExmip1Mtx()) ;
OSIUNITTEST_ASSERT_ERROR(exmip1Mtx.isEquivalent(*smP), {}, "cbc", "getMatrixByRow") ;
#endif // OSICBC_TEST_MTX_STRUCTURE
}
// Test adding several cuts, and handling of a coefficient of infinity
// in the constraint matrix.
{
OsiCbcSolverInterface fim;
std::string fn = mpsDir+"exmip1";
fim.readMps(fn.c_str(),"mps");
// exmip1.mps has 2 integer variables with index 2 & 3
fim.initialSolve();
OsiRowCut cuts[3];
// Generate one ineffective cut plus two trivial cuts
int c;
int nc = fim.getNumCols();
int *inx = new int[nc];
for (c=0;c<nc;c++) inx[c]=c;
double *el = new double[nc];
for (c=0;c<nc;c++) el[c]=1.0e-50+((double)c)*((double)c);
cuts[0].setRow(nc,inx,el);
cuts[0].setLb(-100.);
cuts[0].setUb(500.);
cuts[0].setEffectiveness(22);
el[4]=0.0; // to get inf later
for (c=2;c<4;c++) {
el[0]=1.0;
inx[0]=c;
cuts[c-1].setRow(1,inx,el);
cuts[c-1].setLb(1.);
cuts[c-1].setUb(100.);
cuts[c-1].setEffectiveness(c);
}
fim.writeMps("x1.mps");
fim.applyRowCuts(3,cuts);
fim.writeMps("x2.mps");
// resolve - should get message about zero elements
fim.resolve();
fim.writeMps("x3.mps");
// check integer solution
const double * cs = fim.getColSolution();
CoinRelFltEq eq;
OSIUNITTEST_ASSERT_ERROR(eq(cs[2], 1.0), {}, "cbc", "add cuts");
OSIUNITTEST_ASSERT_ERROR(eq(cs[3], 1.0), {}, "cbc", "add cuts");
// check will find invalid matrix
el[0]=1.0/el[4];
inx[0]=0;
cuts[0].setRow(nc,inx,el);
cuts[0].setLb(-100.);
cuts[0].setUb(500.);
cuts[0].setEffectiveness(22);
fim.applyRowCut(cuts[0]);
// resolve - should get message about zero elements
fim.resolve();
OSIUNITTEST_ASSERT_WARNING(fim.isAbandoned(), {}, "cbc", "add cuts");
delete[]el;
delete[]inx;
}
// Test matrixByCol method
{
const OsiCbcSolverInterface si(m);
const CoinPackedMatrix * smP = si.getMatrixByCol();
OSIUNITTEST_ASSERT_ERROR(smP->getMajorDim() == 8, return, "cbc", "getMatrixByCol: major dim");
OSIUNITTEST_ASSERT_ERROR(smP->getMinorDim() == 5, return, "cbc", "getMatrixByCol: minor dim");
OSIUNITTEST_ASSERT_ERROR(smP->getNumElements() == 14, return, "cbc", "getMatrixByCol: number of elements");
OSIUNITTEST_ASSERT_ERROR(smP->getSizeVectorStarts() == 9, return, "cbc", "getMatrixByCol: vector starts size");
#ifdef OSICBC_TEST_MTX_STRUCTURE
CoinRelFltEq eq;
const double * ev = smP->getElements();
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 0], 3.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 1], 5.6), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 2], 1.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 3], 2.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 4], 1.1), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 5], 1.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 6],-2.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 7], 2.8), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 8],-1.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 9], 1.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[10], 1.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[11],-1.2), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[12],-1.0), {}, "cbc", "getMatrixByCol: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[13], 1.9), {}, "cbc", "getMatrixByCol: elements");
const CoinBigIndex * mi = smP->getVectorStarts();
OSIUNITTEST_ASSERT_ERROR(mi[0] == 0, {}, "cbc", "getMatrixByCol: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[1] == 2, {}, "cbc", "getMatrixByCol: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[2] == 4, {}, "cbc", "getMatrixByCol: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[3] == 6, {}, "cbc", "getMatrixByCol: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[4] == 8, {}, "cbc", "getMatrixByCol: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[5] == 10, {}, "cbc", "getMatrixByCol: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[6] == 11, {}, "cbc", "getMatrixByCol: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[7] == 12, {}, "cbc", "getMatrixByCol: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[8] == 14, {}, "cbc", "getMatrixByCol: vector starts");
const int * ei = smP->getIndices();
OSIUNITTEST_ASSERT_ERROR(ei[ 0] == 0, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 1] == 4, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 2] == 0, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 3] == 1, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 4] == 1, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 5] == 2, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 6] == 0, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 7] == 3, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 8] == 0, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 9] == 4, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[10] == 2, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[11] == 3, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[12] == 0, {}, "cbc", "getMatrixByCol: indices");
OSIUNITTEST_ASSERT_ERROR(ei[13] == 4, {}, "cbc", "getMatrixByCol: indices");
#else // OSICBC_TEST_MTX_STRUCTURE
CoinPackedMatrix &exmip1Mtx = BuildExmip1Mtx() ;
OSIUNITTEST_ASSERT_ERROR(exmip1Mtx.isEquivalent(*smP), {}, "cbc", "getMatrixByCol");
#endif // OSICBC_TEST_MTX_STRUCTURE
}
//--------------
// Test rowsense, rhs, rowrange, matrixByRow, solver assignment
{
OsiCbcSolverInterface lhs;
{
OsiCbcSolverInterface siC1(m);
const char * siC1rs = siC1.getRowSense();
OSIUNITTEST_ASSERT_ERROR(siC1rs[0] == 'G', {}, "cbc", "row sense");
OSIUNITTEST_ASSERT_ERROR(siC1rs[1] == 'L', {}, "cbc", "row sense");
OSIUNITTEST_ASSERT_ERROR(siC1rs[2] == 'E', {}, "cbc", "row sense");
OSIUNITTEST_ASSERT_ERROR(siC1rs[3] == 'R', {}, "cbc", "row sense");
OSIUNITTEST_ASSERT_ERROR(siC1rs[4] == 'R', {}, "cbc", "row sense");
const double * siC1rhs = siC1.getRightHandSide();
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[0],2.5), {}, "cbc", "right hand side");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[1],2.1), {}, "cbc", "right hand side");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[2],4.0), {}, "cbc", "right hand side");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[3],5.0), {}, "cbc", "right hand side");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[4],15.), {}, "cbc", "right hand side");
const double * siC1rr = siC1.getRowRange();
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[0],0.0), {}, "cbc", "row range");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[1],0.0), {}, "cbc", "row range");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[2],0.0), {}, "cbc", "row range");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[3],5.0-1.8), {}, "cbc", "row range");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[4],15.0-3.0), {}, "cbc", "row range");
const CoinPackedMatrix * siC1mbr = siC1.getMatrixByRow();
OSIUNITTEST_ASSERT_ERROR(siC1mbr != NULL, {}, "cbc", "matrix by row");
OSIUNITTEST_ASSERT_ERROR(siC1mbr->getMajorDim() == 5, return, "cbc", "matrix by row: major dim");
OSIUNITTEST_ASSERT_ERROR(siC1mbr->getMinorDim() == 8, return, "cbc", "matrix by row: major dim");
OSIUNITTEST_ASSERT_ERROR(siC1mbr->getNumElements() == 14, return, "cbc", "matrix by row: num elements");
OSIUNITTEST_ASSERT_ERROR(siC1mbr->getSizeVectorStarts() == 6, return, "cbc", "matrix by row: num elements");
#ifdef OSICBC_TEST_MTX_STRUCTURE
const double * ev = siC1mbr->getElements();
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 0], 3.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 1], 1.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 2],-2.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 3],-1.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 4],-1.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 5], 2.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 6], 1.1), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 7], 1.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 8], 1.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 9], 2.8), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[10],-1.2), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[11], 5.6), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[12], 1.0), {}, "cbc", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[13], 1.9), {}, "cbc", "matrix by row: elements");
const CoinBigIndex * mi = siC1mbr->getVectorStarts();
OSIUNITTEST_ASSERT_ERROR(mi[0] == 0, {}, "cbc", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[1] == 5, {}, "cbc", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[2] == 7, {}, "cbc", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[3] == 9, {}, "cbc", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[4] == 11, {}, "cbc", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[5] == 14, {}, "cbc", "matrix by row: vector starts");
const int * ei = siC1mbr->getIndices();
OSIUNITTEST_ASSERT_ERROR(ei[ 0] == 0, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 1] == 1, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 2] == 3, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 3] == 4, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 4] == 7, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 5] == 1, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 6] == 2, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 7] == 2, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 8] == 5, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 9] == 3, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[10] == 6, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[11] == 0, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[12] == 4, {}, "cbc", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[13] == 7, {}, "cbc", "matrix by row: indices");
#else // OSICBC_TEST_MTX_STRUCTURE
CoinPackedMatrix exmip1Mtx ;
exmip1Mtx.reverseOrderedCopyOf(BuildExmip1Mtx()) ;
OSIUNITTEST_ASSERT_ERROR(exmip1Mtx.isEquivalent(*siC1mbr), {}, "cbc", "matrix by row");
#endif // OSICBC_TEST_MTX_STRUCTURE
OSIUNITTEST_ASSERT_WARNING(siC1rs == siC1.getRowSense(), {}, "cbc", "row sense");
OSIUNITTEST_ASSERT_WARNING(siC1rhs == siC1.getRightHandSide(), {}, "cbc", "right hand side");
OSIUNITTEST_ASSERT_WARNING(siC1rr == siC1.getRowRange(), {}, "cbc", "row range");
// Change CBC Model by adding free row
OsiRowCut rc;
rc.setLb(-COIN_DBL_MAX);
rc.setUb( COIN_DBL_MAX);
OsiCuts cuts;
cuts.insert(rc);
siC1.applyCuts(cuts);
siC1rs = siC1.getRowSense();
OSIUNITTEST_ASSERT_ERROR(siC1rs[0] == 'G', {}, "cbc", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[1] == 'L', {}, "cbc", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[2] == 'E', {}, "cbc", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[3] == 'R', {}, "cbc", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[4] == 'R', {}, "cbc", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[5] == 'N', {}, "cbc", "row sense after adding row");
siC1rhs = siC1.getRightHandSide();
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[0],2.5), {}, "cbc", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[1],2.1), {}, "cbc", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[2],4.0), {}, "cbc", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[3],5.0), {}, "cbc", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[4],15.), {}, "cbc", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[5],0.0), {}, "cbc", "right hand side after adding row");
siC1rr = siC1.getRowRange();
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[0],0.0), {}, "cbc", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[1],0.0), {}, "cbc", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[2],0.0), {}, "cbc", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[3],5.0-1.8), {}, "cbc", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[4],15.0-3.0), {}, "cbc", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[5],0.0), {}, "cbc", "row range after adding row");
lhs = siC1;
}
// Test that lhs has correct values even though siC1 has gone out of scope
const char * lhsrs = lhs.getRowSense();
OSIUNITTEST_ASSERT_ERROR(lhsrs[0] == 'G', {}, "cbc", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[1] == 'L', {}, "cbc", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[2] == 'E', {}, "cbc", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[3] == 'R', {}, "cbc", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[4] == 'R', {}, "cbc", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[5] == 'N', {}, "cbc", "row sense after assignment");
const double * lhsrhs = lhs.getRightHandSide();
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[0],2.5), {}, "cbc", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[1],2.1), {}, "cbc", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[2],4.0), {}, "cbc", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[3],5.0), {}, "cbc", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[4],15.), {}, "cbc", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[5],0.0), {}, "cbc", "right hand side after assignment");
const double *lhsrr = lhs.getRowRange();
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[0],0.0), {}, "cbc", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[1],0.0), {}, "cbc", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[2],0.0), {}, "cbc", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[3],5.0-1.8), {}, "cbc", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[4],15.0-3.0), {}, "cbc", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[5],0.0), {}, "cbc", "row range after assignment");
const CoinPackedMatrix * lhsmbr = lhs.getMatrixByRow();
OSIUNITTEST_ASSERT_ERROR(lhsmbr != NULL, {}, "cbc", "matrix by row after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsmbr->getMajorDim() == 6, return, "cbc", "matrix by row after assignment: major dim");
OSIUNITTEST_ASSERT_ERROR(lhsmbr->getNumElements() == 14, return, "cbc", "matrix by row after assignment: num elements");
#ifdef OSICBC_TEST_MTX_STRUCTURE
const double * ev = lhsmbr->getElements();
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 0], 3.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 1], 1.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 2],-2.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 3],-1.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 4],-1.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 5], 2.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 6], 1.1), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 7], 1.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 8], 1.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 9], 2.8), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[10],-1.2), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[11], 5.6), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[12], 1.0), {}, "cbc", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[13], 1.9), {}, "cbc", "matrix by row after assignment: elements");
const CoinBigIndex * mi = lhsmbr->getVectorStarts();
OSIUNITTEST_ASSERT_ERROR(mi[0] == 0, {}, "cbc", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[1] == 5, {}, "cbc", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[2] == 7, {}, "cbc", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[3] == 9, {}, "cbc", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[4] == 11, {}, "cbc", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[5] == 14, {}, "cbc", "matrix by row after assignment: vector starts");
const int * ei = lhsmbr->getIndices();
OSIUNITTEST_ASSERT_ERROR(ei[ 0] == 0, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 1] == 1, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 2] == 3, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 3] == 4, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 4] == 7, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 5] == 1, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 6] == 2, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 7] == 2, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 8] == 5, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 9] == 3, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[10] == 6, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[11] == 0, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[12] == 4, {}, "cbc", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[13] == 7, {}, "cbc", "matrix by row after assignment: indices");
#else // OSICBC_TEST_MTX_STRUCTURE
/*
This admittedly looks bogus, but it's the equivalent operation on the matrix
for inserting a cut of the form -Inf <= +Inf (i.e., a cut with no
coefficients).
*/
CoinPackedMatrix exmip1Mtx ;
exmip1Mtx.reverseOrderedCopyOf(BuildExmip1Mtx()) ;
CoinPackedVector freeRow ;
exmip1Mtx.appendRow(freeRow) ;
OSIUNITTEST_ASSERT_ERROR(exmip1Mtx.isEquivalent(*lhsmbr), {}, "cbc", "matrix by row after assignment");
#endif // OSICBC_TEST_MTX_STRUCTURE
}
}
// Test add/delete columns
{
OsiCbcSolverInterface m;
std::string fn = mpsDir+"p0033";
m.readMps(fn.c_str(),"mps");
double inf = m.getInfinity();
CoinPackedVector c0;
c0.insert(0, 4);
c0.insert(1, 1);
m.addCol(c0, 0, inf, 3);
m.initialSolve();
double objValue = m.getObjValue();
CoinRelFltEq eq(1.0e-2);
OSIUNITTEST_ASSERT_ERROR(eq(objValue,2520.57), {}, "cbc", "objvalue after adding col");
// Try deleting first column that's nonbasic at lower bound (0).
int * d = new int[1];
CoinWarmStartBasis *cwsb = dynamic_cast<CoinWarmStartBasis *>(m.getWarmStart()) ;
OSIUNITTEST_ASSERT_ERROR(cwsb != NULL, {}, "cbc", "get warmstart basis");
CoinWarmStartBasis::Status stati ;
int iCol ;
for (iCol = 0 ; iCol < cwsb->getNumStructural() ; iCol++)
{ stati = cwsb->getStructStatus(iCol) ;
if (stati == CoinWarmStartBasis::atLowerBound) break ; }
d[0]=iCol;
m.deleteCols(1,d);
delete [] d;
delete cwsb;
d=NULL;
m.resolve();
objValue = m.getObjValue();
OSIUNITTEST_ASSERT_ERROR(eq(objValue,2520.57), {}, "clp", "objvalue after deleting first col");
// Try deleting column we added. If basic, go to initialSolve as deleting
// basic variable trashes basis required for warm start.
iCol = m.getNumCols()-1;
cwsb = dynamic_cast<CoinWarmStartBasis *>(m.getWarmStart()) ;
stati = cwsb->getStructStatus(iCol) ;
delete cwsb;
m.deleteCols(1,&iCol);
if (stati == CoinWarmStartBasis::basic)
{ m.initialSolve() ; }
else
{ m.resolve(); }
objValue = m.getObjValue();
OSIUNITTEST_ASSERT_ERROR(eq(objValue,2520.57), {}, "clp", "objvalue after deleting added col");
}
// Build a model
{
OsiCbcSolverInterface model;
std::string fn = mpsDir+"p0033";
model.readMps(fn.c_str(),"mps");
// Point to data
int numberRows = model.getNumRows();
const double * rowLower = model.getRowLower();
const double * rowUpper = model.getRowUpper();
int numberColumns = model.getNumCols();
const double * columnLower = model.getColLower();
const double * columnUpper = model.getColUpper();
const double * columnObjective = model.getObjCoefficients();
// get row copy
CoinPackedMatrix rowCopy = *model.getMatrixByRow();
const int * column = rowCopy.getIndices();
const int * rowLength = rowCopy.getVectorLengths();
const CoinBigIndex * rowStart = rowCopy.getVectorStarts();
const double * element = rowCopy.getElements();
// solve
model.initialSolve();
// Now build new model
CoinModel build;
// Row bounds
int iRow;
for (iRow=0;iRow<numberRows;iRow++) {
build.setRowBounds(iRow,rowLower[iRow],rowUpper[iRow]);
}
// Column bounds and objective
int iColumn;
for (iColumn=0;iColumn<numberColumns;iColumn++) {
build.setColumnLower(iColumn,columnLower[iColumn]);
build.setColumnUpper(iColumn,columnUpper[iColumn]);
build.setObjective(iColumn,columnObjective[iColumn]);
}
// Adds elements one by one by row (backwards by row)
for (iRow=numberRows-1;iRow>=0;iRow--) {
int start = rowStart[iRow];
for (int j=start;j<start+rowLength[iRow];j++)
build(iRow,column[j],element[j]);
}
// Now create Model
OsiCbcSolverInterface model2;
model2.loadFromCoinModel(build);
model2.initialSolve();
// Save - should be continuous
model2.writeMps("continuous");
int * whichInteger = new int[numberColumns];
for (iColumn=0;iColumn<numberColumns;iColumn++)
whichInteger[iColumn]=iColumn;
// mark as integer
model2.setInteger(whichInteger,numberColumns);
delete [] whichInteger;
// save - should be integer
model2.writeMps("integer");
// Now do with strings attached
// Save build to show how to go over rows
CoinModel saveBuild = build;
build = CoinModel();
// Column bounds
for (iColumn=0;iColumn<numberColumns;iColumn++) {
build.setColumnLower(iColumn,columnLower[iColumn]);
build.setColumnUpper(iColumn,columnUpper[iColumn]);
}
// Objective - half the columns as is and half with multiplier of "1.0+multiplier"
// Pick up from saveBuild (for no reason at all)
for (iColumn=0;iColumn<numberColumns;iColumn++) {
double value = saveBuild.objective(iColumn);
if (iColumn*2<numberColumns) {
build.setObjective(iColumn,columnObjective[iColumn]);
} else {
// create as string
char temp[100];
sprintf(temp,"%g + abs(%g*multiplier)",value,value);
build.setObjective(iColumn,temp);
}
}
// It then adds rows one by one but for half the rows sets their values
// with multiplier of "1.0+1.5*multiplier"
for (iRow=0;iRow<numberRows;iRow++) {
if (iRow*2<numberRows) {
// add row in simple way
int start = rowStart[iRow];
build.addRow(rowLength[iRow],column+start,element+start,
rowLower[iRow],rowUpper[iRow]);
} else {
// As we have to add one by one let's get from saveBuild
CoinModelLink triple=saveBuild.firstInRow(iRow);
while (triple.column()>=0) {
int iColumn = triple.column();
if (iColumn*2<numberColumns) {
// just value as normal
build(iRow,triple.column(),triple.value());
} else {
// create as string
char temp[100];
sprintf(temp,"%g + (1.5*%g*multiplier)",triple.value(), triple.value());
build(iRow,iColumn,temp);
}
triple=saveBuild.next(triple);
}
// but remember to do rhs
build.setRowLower(iRow,rowLower[iRow]);
build.setRowUpper(iRow,rowUpper[iRow]);
}
}
// If small switch on error printing
if (numberColumns<50)
build.setLogLevel(1);
// should fail as we never set multiplier
OSIUNITTEST_ASSERT_ERROR(model2.loadFromCoinModel(build) != 0, {}, "cbc", "build model with missing multipliers");
build.associateElement("multiplier",0.0);
OSIUNITTEST_ASSERT_ERROR(model2.loadFromCoinModel(build) == 0, {}, "cbc", "build model");
model2.initialSolve();
// It then loops with multiplier going from 0.0 to 2.0 in increments of 0.1
for (double multiplier=0.0;multiplier<2.0;multiplier+= 0.1) {
build.associateElement("multiplier",multiplier);
OSIUNITTEST_ASSERT_ERROR(model2.loadFromCoinModel(build,true) == 0, {}, "cbc", "build model with increasing multiplier");
model2.resolve();
}
}
// branch and bound
{
OsiCbcSolverInterface m;
std::string fn = mpsDir+"p0033";
m.readMps(fn.c_str(),"mps");
m.initialSolve();
//m.messageHandler()->setLogLevel(0);
m.getModelPtr()->messageHandler()->setLogLevel(0);
m.branchAndBound();
}
// branch and bound using CbcModel!!!!!!!
{
OsiCbcSolverInterface mm;
OsiCbcSolverInterface m(&mm);
std::string fn = mpsDir+"p0033";
m.readMps(fn.c_str(),"mps");
m.initialSolve();
m.branchAndBound();
}
// Do common solverInterface testing
{
OsiCbcSolverInterface m;
OsiSolverInterfaceCommonUnitTest(&m, mpsDir,netlibDir);
}
{
OsiCbcSolverInterface mm;
OsiCbcSolverInterface m(&mm);
OsiSolverInterfaceCommonUnitTest(&m, mpsDir,netlibDir);
}
}
int main( int argc, char **argv )
{
if ( argc < 2 )
{
printf("Invalid number of parameters!\n");
exit( EXIT_FAILURE );
}
char problemName[ 256 ];
getFileName( problemName, argv[1] );
clock_t start = clock();
OsiClpSolverInterface *realSolver = new OsiClpSolverInterface();
realSolver->getModelPtr()->setPerturbation(50); /* makes CLP faster for hard instances */
OsiSolverInterface *solver = (OsiSolverInterface*) realSolver;
parseParameters( argc, argv );
readLP( solver, argv[1] );
FILE *log = NULL;
if(!output.empty())
{
log = fopen(output.c_str(), "a");
if(!log)
{
printf("Could not open the file!\n");
exit(EXIT_FAILURE);
}
}
const int numCols = solver->getNumCols(), numRows = solver->getNumRows();
int pass = 0, newCuts = 0, totalCuts = 0;
double pTime, opt, cgTime;
CGraph *cgraph = NULL;
if(sepMethod == Npsep)
cgraph = build_cgraph_osi( solver );
if(!optFile.empty())
{
getOptimals();
if(optimals.find(problemName) == optimals.end())
{
fprintf(stderr, "ERROR: optimal value not found!\n");
exit(EXIT_FAILURE);
}
opt = optimals[problemName];
}
solver->initialSolve();
if (!solver->isProvenOptimal())
{
if (solver->isAbandoned())
{
fprintf( stderr, "LP solver abandoned due to numerical dificulties.\n" );
exit( EXIT_FAILURE );
}
if (solver->isProvenPrimalInfeasible())
{
fprintf( stderr, "LP solver says PRIMAL INFEASIBLE.\n" );
exit( EXIT_FAILURE );
}
if (solver->isProvenDualInfeasible())
{
fprintf( stderr, "LP solver says DUAL INFEASIBLE.\n" );
exit( EXIT_FAILURE );
}
if (solver->isPrimalObjectiveLimitReached())
{
fprintf( stderr, "LP solver says isPrimalObjectiveLimitReached.\n" );
exit( EXIT_FAILURE );
}
if (solver->isDualObjectiveLimitReached())
{
fprintf( stderr, "LP solver says isDualObjectiveLimitReached.\n" );
exit( EXIT_FAILURE );
}
if (solver->isIterationLimitReached())
{
fprintf( stderr, "LP solver says isIterationLimitReached.\n" );
exit( EXIT_FAILURE );
}
fprintf( stderr, "ERROR: Could not solve LP relaxation to optimality. Checking status...\n" );
exit( EXIT_FAILURE );
}
double initialBound = solver->getObjValue();
printf("%.2lf %d %d %.7lf", ((double)(clock()-start)) / ((double)CLOCKS_PER_SEC), pass, 0, solver->getObjValue());
if(!optFile.empty())
{
printf(" %.7lf %.7lf", opt, abs_mip_gap(solver->getObjValue(), opt));
}
printf("\n");
do
{
clock_t startSep = clock();
newCuts = 0;
switch (sepMethod)
{
case Npsep:
{
CglEClique cliqueGen;
OsiCuts cuts;
CglTreeInfo info;
info.level = 0;
info.pass = 1;
vector<string> varNames = getVarNames(solver->getColNames(), numCols);
cliqueGen.parseParameters( argc, (const char**)argv );
cliqueGen.setCGraph( cgraph );
cliqueGen.setGenOddHoles( true ); //allow (or not) inserting odd hole cuts
cliqueGen.colNames = &varNames;
cliqueGen.generateCuts( *solver, cuts, info );
newCuts = cuts.sizeCuts();
solver->applyCuts( cuts );
}
break;
case CglSepM:
{
CglClique cliqueGen;
OsiCuts cuts;
CglTreeInfo info;
info.level = 0;
info.pass = 1;
cliqueGen.setMinViolation( MIN_VIOLATION );
cliqueGen.setStarCliqueReport(false);
cliqueGen.setRowCliqueReport(false);
cliqueGen.generateCuts( *solver, cuts, info );
newCuts = cuts.sizeCuts();
solver->applyCuts( cuts );
}
break;
Default:
{
fprintf( stderr, "Separation Method does not recognized!\n" );
exit( EXIT_FAILURE );
}
}
pTime = ((double)(clock()-start)) / ((double)CLOCKS_PER_SEC);
if(pTime > MAX_TIME) break;
totalCuts += newCuts;
++pass;
if (newCuts)
{
solver->resolve();
if (!solver->isProvenOptimal())
{
if (solver->isAbandoned())
{
fprintf( stderr, "LP solver abandoned due to numerical dificulties.\n" );
exit( EXIT_FAILURE );
}
if (solver->isProvenPrimalInfeasible())
{
fprintf( stderr, "LP solver says PRIMAL INFEASIBLE.\n" );
exit( EXIT_FAILURE );
}
if (solver->isProvenDualInfeasible())
{
fprintf( stderr, "LP solver says DUAL INFEASIBLE.\n" );
exit( EXIT_FAILURE );
}
if (solver->isPrimalObjectiveLimitReached())
{
fprintf( stderr, "LP solver says isPrimalObjectiveLimitReached.\n" );
exit( EXIT_FAILURE );
}
if (solver->isDualObjectiveLimitReached())
{
fprintf( stderr, "LP solver says isDualObjectiveLimitReached.\n" );
exit( EXIT_FAILURE );
}
if (solver->isIterationLimitReached())
{
fprintf( stderr, "LP solver says isIterationLimitReached.\n" );
exit( EXIT_FAILURE );
}
fprintf( stderr, "ERROR: Could not solve LP relaxation. Exiting.\n" );
exit( EXIT_FAILURE );
}
pTime = ((double)(clock()-start)) / ((double)CLOCKS_PER_SEC);
if(pTime > MAX_TIME) break;
double sepTime = ((double)(clock()-startSep)) / ((double)CLOCKS_PER_SEC);
printf("%.2lf %d %d %.7lf", sepTime, pass, newCuts, solver->getObjValue());
if(!optFile.empty())
printf(" %.7lf %.7lf", opt, abs_mip_gap(solver->getObjValue(), opt));
printf("\n");
}
}
while ( (newCuts>0) && (pass<MAX_PASSES) ) ;
if(log)
{
double totalTime = ((double)(clock()-start)) / ((double)CLOCKS_PER_SEC);
fprintf(log, "%s %.2lf %d %d %.7lf", problemName, totalTime, pass - 1, totalCuts, solver->getObjValue());
if(!optFile.empty())
fprintf(log, " %.7lf", abs_mip_gap(solver->getObjValue(), opt));
fprintf(log, "\n");
}
if(cgraph)
cgraph_free( &cgraph );
delete realSolver;
return EXIT_SUCCESS;
}
//-------------------------------------------------------------------
// Generate Stored cuts
//-------------------------------------------------------------------
void
CglStored::generateCuts(const OsiSolverInterface & si, OsiCuts & cs,
const CglTreeInfo /*info*/) const
{
// Get basic problem information
const double * solution = si.getColSolution();
int numberRowCuts = cuts_.sizeRowCuts();
for (int i=0;i<numberRowCuts;i++) {
const OsiRowCut * rowCutPointer = cuts_.rowCutPtr(i);
double violation = rowCutPointer->violated(solution);
if (violation>=requiredViolation_)
cs.insert(*rowCutPointer);
}
if (probingInfo_) {
int number01 = probingInfo_->numberIntegers();
const cliqueEntry * entry = probingInfo_->fixEntries();
const int * toZero = probingInfo_->toZero();
const int * toOne = probingInfo_->toOne();
const int * integerVariable = probingInfo_->integerVariable();
const double * lower = si.getColLower();
const double * upper = si.getColUpper();
OsiRowCut cut;
int column[2];
double element[2];
for (int i=0;i<number01;i++) {
int iColumn=integerVariable[i];
if (upper[iColumn]==lower[iColumn])
continue;
double value1 = solution[iColumn];
for (int j=toZero[i];j<toOne[i];j++) {
int jColumn=sequenceInCliqueEntry(entry[j]);
if (jColumn<number01) {
jColumn=integerVariable[jColumn];
assert (jColumn>=0);
double value2 = solution[jColumn];
if (oneFixesInCliqueEntry(entry[j])) {
double violation = 1.0-value1-value2;
if (violation>requiredViolation_) {
//printf("XXX can do %d + %d >=1\n",iColumn,jColumn);
cut.setLb(1.0);
cut.setUb(COIN_DBL_MAX);
column[0]=iColumn;
element[0]=1.0;
column[1]=jColumn;
element[1]= 1.0;
cut.setEffectiveness(violation);
cut.setRow(2,column,element,false);
cs.insert(cut);
}
} else {
double violation = value2-value1;
if (violation>requiredViolation_) {
//printf("XXX can do %d >= %d\n",iColumn,jColumn);
cut.setLb(0.0);
cut.setUb(COIN_DBL_MAX);
column[0]=iColumn;
element[0]=1.0;
column[1]=jColumn;
element[1]= -1.0;
cut.setEffectiveness(violation);
cut.setRow(2,column,element,false);
cs.insert(cut);
}
}
} else {
jColumn -= number01; // not 0-1
double value2 = solution[jColumn];
double lowerValue = lower[jColumn];
double upperValue = upper[jColumn];
if (oneFixesInCliqueEntry(entry[j])) {
double violation = upperValue-value1*(upperValue-lowerValue)-value2;
if (violation>requiredViolation_) {
//printf("XXX can do %g*%d + %d >=%g\n",(upperValue-lowerValue),iColumn,jColumn,upperValue);
cut.setLb(upperValue);
cut.setUb(COIN_DBL_MAX);
column[0]=iColumn;
element[0]=upperValue-lowerValue;
column[1]=jColumn;
element[1]= 1.0;
cut.setEffectiveness(violation);
cut.setRow(2,column,element,false);
cs.insert(cut);
}
} else {
double violation = value2-value1*(upperValue-lowerValue)-lowerValue;
if (violation>requiredViolation_) {
//printf("XXX can do %g*%d >= %d -%g\n",(upperValue-lowerValue),iColumn,jColumn,lowerValue);
cut.setLb(-lowerValue);
cut.setUb(COIN_DBL_MAX);
column[0]=iColumn;
element[0]=upperValue-lowerValue;
column[1]=jColumn;
element[1]= -1.0;
cut.setEffectiveness(violation);
cut.setRow(2,column,element,false);
cs.insert(cut);
}
}
}
}
for (int j=toOne[i];j<toZero[i+1];j++) {
int jColumn=sequenceInCliqueEntry(entry[j]);
if (jColumn<number01) {
jColumn=integerVariable[jColumn];
assert (jColumn>=0);
double value2 = solution[jColumn];
if (oneFixesInCliqueEntry(entry[j])) {
double violation = value1-value2;
if (violation>requiredViolation_) {
//printf("XXX can do %d <= %d\n",iColumn,jColumn);
cut.setLb(-COIN_DBL_MAX);
cut.setUb(0.0);
column[0]=iColumn;
element[0]=1.0;
column[1]=jColumn;
element[1]= -1.0;
cut.setEffectiveness(violation);
cut.setRow(2,column,element,false);
cs.insert(cut);
}
} else {
double violation = value1+value2-1.0;
if (violation>requiredViolation_) {
//printf("XXX can do %d + %d <=1\n",iColumn,jColumn);
cut.setLb(-COIN_DBL_MAX);
cut.setUb(1.0);
column[0]=iColumn;
element[0]=1.0;
column[1]=jColumn;
element[1]= 1.0;
cut.setEffectiveness(violation);
cut.setRow(2,column,element,false);
cs.insert(cut);
}
}
} else {
jColumn -= number01; // not 0-1
double value2 = solution[jColumn];
double lowerValue = lower[jColumn];
double upperValue = upper[jColumn];
if (oneFixesInCliqueEntry(entry[j])) {
double violation = lowerValue +(upperValue-lowerValue)*value1-value2;
if (violation>requiredViolation_) {
//printf("XXX can do %g*%d <= %d -%g\n",(upperValue-lowerValue),iColumn,jColumn,lowerValue);
cut.setLb(-COIN_DBL_MAX);
cut.setUb(-lowerValue);
column[0]=iColumn;
element[0]=upperValue-lowerValue;
column[1]=jColumn;
element[1]= -1.0;
cut.setEffectiveness(violation);
cut.setRow(2,column,element,false);
cs.insert(cut);
}
} else {
double violation = (upperValue-lowerValue)*value1+value2-upperValue;
if (violation>requiredViolation_) {
//printf("XXX can do %g*%d + %d <=%g\n",(upperValue-lowerValue),iColumn,jColumn,upperValue);
cut.setLb(-COIN_DBL_MAX);
cut.setUb(upperValue);
column[0]=iColumn;
element[0]=upperValue-lowerValue;
column[1]=jColumn;
element[1]= 1.0;
cut.setEffectiveness(violation);
cut.setRow(2,column,element,false);
cs.insert(cut);
}
}
}
}
}
}
}
/** Get an inner-approximation constraint obtained by drawing a chord linking the two given points x and x2.
* This only applies to nonlinear constraints featuring univariate functions (f(x) <= y).**/
bool
HeuristicInnerApproximation::getMyInnerApproximation(Bonmin::OsiTMINLPInterface &si, OsiCuts &cs, int ind,
const double * x, const double * x2) {
int n, m, nnz_jac_g, nnz_h_lag;
Ipopt::TNLP::IndexStyleEnum index_style;
Bonmin::TMINLP2TNLP * problem = si.problem();
problem->get_nlp_info(n, m, nnz_jac_g, nnz_h_lag, index_style);
double infty = si.getInfinity();
CoinPackedVector cut;
double lb = -infty;
double ub = 0;
double g = 0;
double g2 = 0;
double diff = 0;
double a = 0;
problem->eval_gi(n, x, 1, ind, g);
problem->eval_gi(n, x2, 1, ind, g2);
Bonmin::vector<int> jCol(n);
int nnz;
problem->eval_grad_gi(n, x2, 0, ind, nnz, jCol(), NULL);
Bonmin::vector<double> jValues(nnz);
problem->eval_grad_gi(n, x2, 0, ind, nnz, NULL, jValues());
bool add = false;
//printf("const %i nnz %i\n", ind, nnz);
for (int i = 0; i < nnz; i++) {
const int &colIdx = jCol[i];
if(index_style == Ipopt::TNLP::FORTRAN_STYLE) jCol[i]--;
diff = x[colIdx] - x2[colIdx];
if (fabs(diff) >= 1e-8) {
a = (g - g2) / diff;
cut.insert(colIdx, a);
ub = (a * x[colIdx] - g) - fabs(a * x[colIdx] - g)*1e-6;
//printf("const %i col %i p[col] %g pp[col] %g g %g g2 %g diff %g\n",ind, colIdx, x[colIdx], x2[colIdx], g, g2, diff);
add = true;
} else {
cut.insert(colIdx, jValues[i]);
//printf("const %i col %i val %g\n",ind, colIdx, jValues[i]);
}
}
if (add) {
OsiRowCut newCut;
newCut.setGloballyValidAsInteger(1);
newCut.setLb(lb);
//********* Perspective Extension ********//
int binary_id = 0; // index corresponding to the binary variable activating the corresponding constraint
const int* ids = problem->get_const_xtra_id(); // vector of indices corresponding to the binary variable activating the corresponding constraint
// Get the index of the corresponding indicator binary variable
binary_id = (ids == NULL) ? -1 : ids[ind];
if(binary_id>0) {// If this hyperplane is a linearization of a disjunctive constraint, we link its righthand side to the corresponding indicator binary variable
cut.insert(binary_id, -ub); // ∂x ≤ ub => ∂x - ub*z ≤ 0
newCut.setUb(0);
}
else
newCut.setUb(ub);
//********* Perspective Extension ********//
newCut.setRow(cut);
cs.insert(newCut);
//newCut.print();
return true;
}
return false;
}
//-----------------------------------------------------------------------------
// Generate Lift-and-Project cuts
//-------------------------------------------------------------------
void CglLiftAndProject::generateCuts(const OsiSolverInterface& si, OsiCuts& cs,
const CglTreeInfo /*info*/)
{
// Assumes the mixed 0-1 problem
//
// min {cx: <Atilde,x> >= btilde}
//
// is in canonical form with all bounds,
// including x_t>=0, -x_t>=-1 for x_t binary,
// explicitly stated in the constraint matrix.
// See ~/COIN/Examples/Cgl2/cgl2.cpp
// for a general purpose "convert" function.
// Reference [BCC]: Balas, Ceria, and Corneujols,
// "A lift-and-project cutting plane algorithm
// for mixed 0-1 program", Math Prog 58, (1993)
// 295-324.
// This implementation uses Normalization 1.
// Given canonical problem and
// the lp-relaxation solution, x,
// the LAP cut generator attempts to construct
// a cut for every x_j such that 0<x_j<1
// [BCC:307]
// x_j is the strictly fractional binary variable
// the cut is generated from
int j = 0;
// Get basic problem information
// let Atilde be an m by n matrix
const int m = si.getNumRows();
const int n = si.getNumCols();
const double * x = si.getColSolution();
// Remember - Atildes may have gaps..
const CoinPackedMatrix * Atilde = si.getMatrixByRow();
const double * AtildeElements = Atilde->getElements();
const int * AtildeIndices = Atilde->getIndices();
const CoinBigIndex * AtildeStarts = Atilde->getVectorStarts();
const int * AtildeLengths = Atilde->getVectorLengths();
const int AtildeFullSize = AtildeStarts[m];
const double * btilde = si.getRowLower();
// Set up memory for system (10) [BCC:307]
// (the problem over the norm intersected
// with the polar cone)
//
// min <<x^T,Atilde^T>,u> + x_ju_0
// s.t.
// <B,w> = (0,...,0,beta_,beta)^T
// w is nonneg for all but the
// last two entries, which are free.
// where
// w = (u,v,v_0,u_0)in BCC notation
// u and v are m-vectors; u,v >=0
// v_0 and u_0 are free-scalars, and
//
// B = Atilde^T -Atilde^T -e_j e_j
// btilde^T e_0^T 0 0
// e_0^T btilde^T 1 0
// ^T indicates Transpose
// e_0 is a (AtildeNCols x 1) vector of all zeros
// e_j is e_0 with a 1 in the jth position
// Storing B in column order. B is a (n+2 x 2m+2) matrix
// But need to allow for possible gaps in Atilde.
// At each iteration, only need to change 2 cols and objfunc
// Sane design of OsiSolverInterface does not permit mucking
// with matrix.
// Because we must delete and add cols to alter matrix,
// and we can only add columns on the end of the matrix
// put the v_0 and u_0 columns on the end.
// rather than as described in [BCC]
// Initially allocating B with space for v_0 and u_O cols
// but not populating, for efficiency.
// B without u_0 and v_0 is a (n+2 x 2m) size matrix.
int twoM = 2*m;
int BNumRows = n+2;
int BNumCols = twoM+2;
int BFullSize = 2*AtildeFullSize+twoM+3;
double * BElements = new double[BFullSize];
int * BIndices = new int[BFullSize];
CoinBigIndex * BStarts = new CoinBigIndex [BNumCols+1];
int * BLengths = new int[BNumCols];
int i, ij, k=0;
int nPlus1=n+1;
int offset = AtildeStarts[m]+m;
for (i=0; i<m; i++){
for (ij=AtildeStarts[i];ij<AtildeStarts[i]+AtildeLengths[i];ij++){
BElements[k]=AtildeElements[ij];
BElements[k+offset]=-AtildeElements[ij];
BIndices[k]= AtildeIndices[ij];
BIndices[k+offset]= AtildeIndices[ij];
k++;
}
BElements[k]=btilde[i];
BElements[k+offset]=btilde[i];
BIndices[k]=n;
BIndices[k+offset]=nPlus1;
BStarts[i]= AtildeStarts[i]+i;
BStarts[i+m]=offset+BStarts[i];// = AtildeStarts[m]+m+AtildeStarts[i]+i
BLengths[i]= AtildeLengths[i]+1;
BLengths[i+m]= AtildeLengths[i]+1;
k++;
}
BStarts[twoM]=BStarts[twoM-1]+BLengths[twoM-1];
// Cols that will be deleted each iteration
int BNumColsLessOne=BNumCols-1;
int BNumColsLessTwo=BNumCols-2;
const int delCols[2] = {BNumColsLessOne, BNumColsLessTwo};
// Set lower bound on u and v
// u_0, v_0 will be reset as free
const double solverINFINITY = si.getInfinity();
double * BColLowers = new double[BNumCols];
double * BColUppers = new double[BNumCols];
CoinFillN(BColLowers,BNumCols,0.0);
CoinFillN(BColUppers,BNumCols,solverINFINITY);
// Set row lowers and uppers.
// The rhs is zero, for but the last two rows.
// For these the rhs is beta_
double * BRowLowers = new double[BNumRows];
double * BRowUppers = new double[BNumRows];
CoinFillN(BRowLowers,BNumRows,0.0);
CoinFillN(BRowUppers,BNumRows,0.0);
BRowLowers[BNumRows-2]=beta_;
BRowUppers[BNumRows-2]=beta_;
BRowLowers[BNumRows-1]=beta_;
BRowUppers[BNumRows-1]=beta_;
// Calculate base objective <<x^T,Atilde^T>,u>
// Note: at each iteration coefficient u_0
// changes to <x^T,e_j>
// w=(u,v,beta,v_0,u_0) size 2m+3
// So, BOjective[2m+2]=x[j]
double * BObjective= new double[BNumCols];
double * Atildex = new double[m];
CoinFillN(BObjective,BNumCols,0.0);
Atilde->times(x,Atildex); // Atildex is size m, x is size n
CoinDisjointCopyN(Atildex,m,BObjective);
// Number of cols and size of Elements vector
// in B without the v_0 and u_0 cols
int BFullSizeLessThree = BFullSize-3;
// Load B matrix into a column orders CoinPackedMatrix
CoinPackedMatrix * BMatrix = new CoinPackedMatrix(true, BNumRows,
BNumColsLessTwo,
BFullSizeLessThree,
BElements,BIndices,
BStarts,BLengths);
// Assign problem into a solver interface
// Note: coneSi will cleanup the memory itself
OsiSolverInterface * coneSi = si.clone(false);
coneSi->assignProblem (BMatrix, BColLowers, BColUppers,
BObjective,
BRowLowers, BRowUppers);
// Problem sense should default to "min" by default,
// but just to be virtuous...
coneSi->setObjSense(1.0);
// The plot outline from here on down:
// coneSi has been assigned B without the u_0 and v_0 columns
// Calculate base objective <<x^T,Atilde^T>,u>
// bool haveWarmStart = false;
// For (j=0; j<n, j++)
// if (!isBinary(x_j) || x_j<=0 || x_j>=1) continue;
// // IMPROVEME: if(haveWarmStart) check if j attractive
// add {-e_j,0,-1} matrix column for v_0
// add {e_j,0,0} matrix column for u_0
// objective coefficient for u_0 is x_j
// if (haveWarmStart)
// set warmstart info
// solve min{objw:Bw=0; w>=0,except v_0, u_0 free}
// if (bounded)
// get warmstart info
// haveWarmStart=true;
// ustar = optimal u solution
// ustar_0 = optimal u_0 solution
// alpha^T= <ustar^T,Atilde> -ustar_0e_j^T
// (double check <alpha^T,x> >= beta_ should be violated)
// add <alpha^T,x> >= beta_ to cutset
// endif
// delete column for u_0 // this deletes all column info.
// delete column for v_0
// endFor
// clean up memory
// return 0;
int * nVectorIndices = new int[n];
CoinIotaN(nVectorIndices, n, 0);
bool haveWarmStart = false;
bool equalObj1, equalObj2;
CoinRelFltEq eq;
double v_0Elements[2] = {-1,1};
double u_0Elements[1] = {1};
CoinWarmStart * warmStart = 0;
double * ustar = new double[m];
CoinFillN(ustar, m, 0.0);
double* alpha = new double[n];
CoinFillN(alpha, n, 0.0);
for (j=0;j<n;j++){
if (!si.isBinary(j)) continue; // Better to ask coneSi? No!
// coneSi has no binInfo.
equalObj1=eq(x[j],0);
equalObj2=eq(x[j],1);
if (equalObj1 || equalObj2) continue;
// IMPROVEME: if (haveWarmStart) check if j attractive;
// AskLL:wanted to declare u_0 and v_0 packedVec outside loop
// and setIndices, but didn't see a method to do that(?)
// (Could "insert". Seems inefficient)
int v_0Indices[2]={j,nPlus1};
int u_0Indices[1]={j};
//
CoinPackedVector v_0(2,v_0Indices,v_0Elements,false);
CoinPackedVector u_0(1,u_0Indices,u_0Elements,false);
#if CGL_DEBUG
const CoinPackedMatrix *see1 = coneSi->getMatrixByRow();
#endif
coneSi->addCol(v_0,-solverINFINITY,solverINFINITY,0);
coneSi->addCol(u_0,-solverINFINITY,solverINFINITY,x[j]);
if(haveWarmStart) {
coneSi->setWarmStart(warmStart);
coneSi->resolve();
}
else {
#if CGL_DEBUG
const CoinPackedMatrix *see2 = coneSi->getMatrixByRow();
#endif
coneSi->initialSolve();
}
if(coneSi->isProvenOptimal()){
warmStart = coneSi->getWarmStart();
haveWarmStart=true;
const double * wstar = coneSi->getColSolution();
CoinDisjointCopyN(wstar, m, ustar);
Atilde->transposeTimes(ustar,alpha);
alpha[j]+=wstar[BNumCols-1];
#if debug
int p;
double sum;
for(p=0;p<n;p++)sum+=alpha[p]*x[p];
if (sum<=beta_){
throw CoinError("Cut not violated",
"cutGeneration",
"CglLiftAndProject");
}
#endif
// add <alpha^T,x> >= beta_ to cutset
OsiRowCut rc;
rc.setRow(n,nVectorIndices,alpha);
rc.setLb(beta_);
rc.setUb(solverINFINITY);
cs.insert(rc);
}
// delete col for u_o and v_0
coneSi->deleteCols(2,delCols);
// clean up memory
}
// clean up
delete [] alpha;
delete [] ustar;
delete [] nVectorIndices;
// BMatrix, BColLowers,BColUppers, BObjective, BRowLowers, BRowUppers
// are all freed by OsiSolverInterface destructor (?)
delete [] BLengths;
delete [] BStarts;
delete [] BIndices;
delete [] BElements;
}
int main(int argc, char **argv)
{
char *f_name_lp, *last_dot_pos, f_name[256], *f_name_pos;
int i, ncol;
if((argc < 2) || (argc > 2)) {
printf("### ERROR: main(): Usage: One of the following\ncgl_data_test input_file_name.mps\ncgl_data_test input_file_name.lp\n");
exit(1);
}
f_name_lp = strdup(argv[1]);
f_name_pos = strrchr(f_name_lp, '/');
if(f_name_pos != NULL) {
strcpy(f_name, &(f_name_pos[1]));
}
else {
strcpy(f_name, f_name_lp);
}
last_dot_pos = strrchr(f_name, '.');
if(last_dot_pos != NULL) {
last_dot_pos = '\0';
}
OsiClpSolverInterface *clp = new OsiClpSolverInterface;
clp->messageHandler()->setLogLevel(0);
if(strcmp(&(f_name_lp[strlen(f_name_lp)-3]), ".lp") == 0) {
clp->readLp(f_name_lp);
}
else {
if(strcmp(&(f_name_lp[strlen(f_name_lp)-4]), ".mps") == 0) {
clp->readMps(f_name_lp);
}
else {
printf("### ERROR: unrecognized file type\n");
exit(1);
}
}
ncol = clp->getNumCols();
clp->initialSolve();
printf("LP value: %12.2f\n", clp->getObjValue());
OsiCuts cuts;
// Define parameters for CglRedSplit generator
CglParam cpar;
cpar.setMAX_SUPPORT(ncol+1);
CglRedSplitParam rspar(cpar);
// Create a cut generator with the given parameters
CglRedSplit cutGen(rspar);
char *colType = new char[ncol];
for(i=0; i<ncol; i++) {
if(clp->isContinuous(i)) {
colType[i] = 'C';
}
else {
colType[i] = 'I';
}
}
int round, max_rounds = 10;
for(round=0; round<max_rounds; round++) {
cutGen.generateCuts(*clp, cuts);
int ncuts = cuts.sizeRowCuts();
const OsiRowCut **newRowCuts = new const OsiRowCut * [ncuts];
for(i=0; i<ncuts; i++) {
newRowCuts[i] = &cuts.rowCut(i);
}
clp->applyRowCuts(ncuts, newRowCuts);
delete[] newRowCuts;
printf("round %4d: %4d generated cuts new objective value: %12.2f\n",
round, ncuts, clp->getObjValue());
clp->resolve();
if(clp->isAbandoned()) {
printf("###ERROR: Numerical difficulties in Solver\n");
exit(1);
}
if(clp->isProvenPrimalInfeasible()) {
printf("### WARNING: Problem is infeasible\n");
exit(1);
}
}
delete clp;
free(f_name_lp);
delete[] colType;
return(0);
}
void OsiSpxSolverInterfaceUnitTest( const std::string & mpsDir, const std::string & netlibDir )
{
// Test default constructor
{
OsiSpxSolverInterface m;
OSIUNITTEST_ASSERT_ERROR(m.soplex_ != NULL, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.getNumCols() == 0, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.rowsense_ == NULL, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.rhs_ == NULL, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.rowrange_ == NULL, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.colsol_ == NULL, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.rowsol_ == NULL, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.matrixByRow_ == NULL, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.matrixByCol_ == NULL, {}, "SoPlex", "default constructor");
OSIUNITTEST_ASSERT_ERROR(m.getApplicationData() == NULL, {}, "SoPlex", "default constructor");
int i=2346;
m.setApplicationData(&i);
OSIUNITTEST_ASSERT_ERROR(*((int *)(m.getApplicationData())) == i, {}, "SoPlex", "set application data");
}
{
CoinRelFltEq eq;
OsiSpxSolverInterface m;
std::string fn = mpsDir+"exmip1";
m.readMps(fn.c_str(),"mps");
// int ad = 13579;
// m.setApplicationData(&ad);
// OSIUNITTEST_ASSERT_ERROR(*((int *)(m.getApplicationData())) == ad, {}, "SoPlex", "set application data");
{
const CoinPackedMatrix * colCopy = m.getMatrixByCol();
OSIUNITTEST_ASSERT_ERROR(colCopy->getNumCols() == 8, {}, "SoPlex", "exmip1 matrix");
OSIUNITTEST_ASSERT_ERROR(colCopy->getMajorDim() == 8, {}, "SoPlex", "exmip1 matrix");
OSIUNITTEST_ASSERT_ERROR(colCopy->getNumRows() == 5, {}, "SoPlex", "exmip1 matrix");
OSIUNITTEST_ASSERT_ERROR(colCopy->getMinorDim() == 5, {}, "SoPlex", "exmip1 matrix");
OSIUNITTEST_ASSERT_ERROR(colCopy->getVectorLengths()[7] == 2, {}, "SoPlex", "exmip1 matrix");
CoinPackedMatrix revColCopy;
revColCopy.reverseOrderedCopyOf(*colCopy);
CoinPackedMatrix rev2ColCopy;
rev2ColCopy.reverseOrderedCopyOf(revColCopy);
OSIUNITTEST_ASSERT_ERROR(rev2ColCopy.getNumCols() == 8, {}, "SoPlex", "twice reverse matrix copy");
OSIUNITTEST_ASSERT_ERROR(rev2ColCopy.getMajorDim() == 8, {}, "SoPlex", "twice reverse matrix copy");
OSIUNITTEST_ASSERT_ERROR(rev2ColCopy.getNumRows() == 5, {}, "SoPlex", "twice reverse matrix copy");
OSIUNITTEST_ASSERT_ERROR(rev2ColCopy.getMinorDim() == 5, {}, "SoPlex", "twice reverse matrix copy");
OSIUNITTEST_ASSERT_ERROR(rev2ColCopy.getVectorLengths()[7] == 2, {}, "SoPlex", "twice reverse matrix copy");
}
// Test copy constructor and assignment operator
{
OsiSpxSolverInterface lhs;
{
OsiSpxSolverInterface im(m);
OsiSpxSolverInterface imC1(im);
OsiSpxSolverInterface imC2(im);
lhs = imC2;
}
// Test that lhs has correct values even though rhs has gone out of scope
OSIUNITTEST_ASSERT_ERROR(lhs.getNumCols() == m.getNumCols(), {}, "SoPlex", "copy constructor");
OSIUNITTEST_ASSERT_ERROR(lhs.getNumRows() == m.getNumRows(), {}, "SoPlex", "copy constructor");
}
// Test clone
{
OsiSpxSolverInterface soplexSi(m);
OsiSolverInterface * siPtr = &soplexSi;
OsiSolverInterface * siClone = siPtr->clone();
OsiSpxSolverInterface * soplexClone = dynamic_cast<OsiSpxSolverInterface*>(siClone);
OSIUNITTEST_ASSERT_ERROR(soplexClone != NULL, {}, "SoPlex", "clone");
OSIUNITTEST_ASSERT_ERROR(soplexClone->getNumRows() == soplexSi.getNumRows(), {}, "SoPlex", "clone");
OSIUNITTEST_ASSERT_ERROR(soplexClone->getNumCols() == m.getNumCols(), {}, "SoPlex", "clone");
delete siClone;
}
// test infinity
{
OsiSpxSolverInterface si;
OSIUNITTEST_ASSERT_ERROR(si.getInfinity() == soplex::infinity, {}, "SoPlex", "value for infinity");
}
{
OsiSpxSolverInterface soplexSi(m);
int nc = soplexSi.getNumCols();
int nr = soplexSi.getNumRows();
const double * cl = soplexSi.getColLower();
const double * cu = soplexSi.getColUpper();
const double * rl = soplexSi.getRowLower();
const double * ru = soplexSi.getRowUpper();
OSIUNITTEST_ASSERT_ERROR(nc == 8, return, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(nr == 5, return, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cl[0],2.5), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cl[1],0.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cu[1],4.1), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(cu[2],1.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(rl[0],2.5), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(rl[4],3.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(ru[1],2.1), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(ru[4],15.), {}, "SoPlex", "read and copy exmip1");
double newCs[8] = {1., 2., 3., 4., 5., 6., 7., 8.};
soplexSi.setColSolution(newCs);
const double * cs = soplexSi.getColSolution();
OSIUNITTEST_ASSERT_ERROR(eq(cs[0],1.0), {}, "SoPlex", "set col solution");
OSIUNITTEST_ASSERT_ERROR(eq(cs[7],8.0), {}, "SoPlex", "set col solution");
{
OsiSpxSolverInterface solnSi(soplexSi);
const double * cs = solnSi.getColSolution();
OSIUNITTEST_ASSERT_ERROR(eq(cs[0],1.0), {}, "SoPlex", "set col solution and copy");
OSIUNITTEST_ASSERT_ERROR(eq(cs[7],8.0), {}, "SoPlex", "set col solution and copy");
}
OSIUNITTEST_ASSERT_ERROR(!eq(cl[3],1.2345), {}, "SoPlex", "set col lower");
soplexSi.setColLower( 3, 1.2345 );
OSIUNITTEST_ASSERT_ERROR( eq(cl[3],1.2345), {}, "SoPlex", "set col lower");
OSIUNITTEST_ASSERT_ERROR(!eq(cu[4],10.2345), {}, "SoPlex", "set col upper");
soplexSi.setColUpper( 4, 10.2345 );
OSIUNITTEST_ASSERT_ERROR( eq(cu[4],10.2345), {}, "SoPlex", "set col upper");
OSIUNITTEST_ASSERT_ERROR(eq(soplexSi.getObjCoefficients()[0], 1.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(soplexSi.getObjCoefficients()[1], 0.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(soplexSi.getObjCoefficients()[2], 0.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(soplexSi.getObjCoefficients()[3], 0.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(soplexSi.getObjCoefficients()[4], 2.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(soplexSi.getObjCoefficients()[5], 0.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(soplexSi.getObjCoefficients()[6], 0.0), {}, "SoPlex", "read and copy exmip1");
OSIUNITTEST_ASSERT_ERROR(eq(soplexSi.getObjCoefficients()[7],-1.0), {}, "SoPlex", "read and copy exmip1");
}
// Test getMatrixByRow method
{
const OsiSpxSolverInterface si(m);
const CoinPackedMatrix * smP = si.getMatrixByRow();
OSIUNITTEST_ASSERT_ERROR(smP->getMajorDim() == 5, return, "SoPlex", "getMatrixByRow: major dim");
OSIUNITTEST_ASSERT_ERROR(smP->getNumElements() == 14, return, "SoPlex", "getMatrixByRow: num elements");
CoinRelFltEq eq;
const double * ev = smP->getElements();
OSIUNITTEST_ASSERT_ERROR(eq(ev[0], 3.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[1], 1.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[2], -2.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[3], -1.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[4], -1.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[5], 2.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[6], 1.1), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[7], 1.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[8], 1.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[9], 2.8), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[10], -1.2), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[11], 5.6), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[12], 1.0), {}, "SoPlex", "getMatrixByRow: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[13], 1.9), {}, "SoPlex", "getMatrixByRow: elements");
const int * mi = smP->getVectorStarts();
OSIUNITTEST_ASSERT_ERROR(mi[0] == 0, {}, "SoPlex", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[1] == 5, {}, "SoPlex", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[2] == 7, {}, "SoPlex", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[3] == 9, {}, "SoPlex", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[4] == 11, {}, "SoPlex", "getMatrixByRow: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[5] == 14, {}, "SoPlex", "getMatrixByRow: vector starts");
const int * ei = smP->getIndices();
OSIUNITTEST_ASSERT_ERROR(ei[ 0] == 0, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 1] == 1, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 2] == 3, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 3] == 4, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 4] == 7, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 5] == 1, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 6] == 2, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 7] == 2, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 8] == 5, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 9] == 3, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[10] == 6, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[11] == 0, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[12] == 4, {}, "SoPlex", "getMatrixByRow: indices");
OSIUNITTEST_ASSERT_ERROR(ei[13] == 7, {}, "SoPlex", "getMatrixByRow: indices");
}
//--------------
// Test rowsense, rhs, rowrange, getMatrixByRow
{
OsiSpxSolverInterface lhs;
{
OsiSpxSolverInterface siC1(m);
OSIUNITTEST_ASSERT_WARNING(siC1.rowrange_ == NULL, {}, "SoPlex", "row range");
OSIUNITTEST_ASSERT_WARNING(siC1.rowsense_ == NULL, {}, "SoPlex", "row sense");
OSIUNITTEST_ASSERT_WARNING(siC1.rhs_ == NULL, {}, "SoPlex", "right hand side");
OSIUNITTEST_ASSERT_WARNING(siC1.matrixByRow_ == NULL, {}, "SoPlex", "matrix by row");
OSIUNITTEST_ASSERT_WARNING(siC1.colsol_ == NULL, {}, "SoPlex", "col solution");
OSIUNITTEST_ASSERT_WARNING(siC1.rowsol_ == NULL, {}, "SoPlex", "row solution");
const char * siC1rs = siC1.getRowSense();
OSIUNITTEST_ASSERT_ERROR(siC1rs[0] == 'G', {}, "SoPlex", "row sense");
OSIUNITTEST_ASSERT_ERROR(siC1rs[1] == 'L', {}, "SoPlex", "row sense");
OSIUNITTEST_ASSERT_ERROR(siC1rs[2] == 'E', {}, "SoPlex", "row sense");
OSIUNITTEST_ASSERT_ERROR(siC1rs[3] == 'R', {}, "SoPlex", "row sense");
OSIUNITTEST_ASSERT_ERROR(siC1rs[4] == 'R', {}, "SoPlex", "row sense");
const double * siC1rhs = siC1.getRightHandSide();
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[0],2.5), {}, "SoPlex", "right hand side");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[1],2.1), {}, "SoPlex", "right hand side");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[2],4.0), {}, "SoPlex", "right hand side");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[3],5.0), {}, "SoPlex", "right hand side");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[4],15.), {}, "SoPlex", "right hand side");
const double * siC1rr = siC1.getRowRange();
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[0],0.0), {}, "SoPlex", "row range");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[1],0.0), {}, "SoPlex", "row range");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[2],0.0), {}, "SoPlex", "row range");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[3],5.0-1.8), {}, "SoPlex", "row range");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[4],15.0-3.0), {}, "SoPlex", "row range");
const CoinPackedMatrix * siC1mbr = siC1.getMatrixByRow();
OSIUNITTEST_ASSERT_ERROR(siC1mbr != NULL, {}, "SoPlex", "matrix by row");
OSIUNITTEST_ASSERT_ERROR(siC1mbr->getMajorDim() == 5, return, "SoPlex", "matrix by row: major dim");
OSIUNITTEST_ASSERT_ERROR(siC1mbr->getNumElements() == 14, return, "SoPlex", "matrix by row: num elements");
const double * ev = siC1mbr->getElements();
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 0], 3.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 1], 1.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 2],-2.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 3],-1.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 4],-1.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 5], 2.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 6], 1.1), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 7], 1.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 8], 1.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 9], 2.8), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[10],-1.2), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[11], 5.6), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[12], 1.0), {}, "SoPlex", "matrix by row: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[13], 1.9), {}, "SoPlex", "matrix by row: elements");
const CoinBigIndex * mi = siC1mbr->getVectorStarts();
OSIUNITTEST_ASSERT_ERROR(mi[0] == 0, {}, "SoPlex", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[1] == 5, {}, "SoPlex", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[2] == 7, {}, "SoPlex", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[3] == 9, {}, "SoPlex", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[4] == 11, {}, "SoPlex", "matrix by row: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[5] == 14, {}, "SoPlex", "matrix by row: vector starts");
const int * ei = siC1mbr->getIndices();
OSIUNITTEST_ASSERT_ERROR(ei[ 0] == 0, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 1] == 1, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 2] == 3, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 3] == 4, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 4] == 7, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 5] == 1, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 6] == 2, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 7] == 2, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 8] == 5, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 9] == 3, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[10] == 6, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[11] == 0, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[12] == 4, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_ERROR(ei[13] == 7, {}, "SoPlex", "matrix by row: indices");
OSIUNITTEST_ASSERT_WARNING(siC1rs == siC1.getRowSense(), {}, "SoPlex", "row sense");
OSIUNITTEST_ASSERT_WARNING(siC1rhs == siC1.getRightHandSide(), {}, "SoPlex", "right hand side");
OSIUNITTEST_ASSERT_WARNING(siC1rr == siC1.getRowRange(), {}, "SoPlex", "row range");
// Change SOPLEX Model by adding free row
OsiRowCut rc;
rc.setLb(-COIN_DBL_MAX);
rc.setUb( COIN_DBL_MAX);
OsiCuts cuts;
cuts.insert(rc);
siC1.applyCuts(cuts);
// Since model was changed, test that cached data is now freed.
OSIUNITTEST_ASSERT_ERROR(siC1.rowrange_ == NULL, {}, "SoPlex", "free cached data after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1.rowsense_ == NULL, {}, "SoPlex", "free cached data after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1.rhs_ == NULL, {}, "SoPlex", "free cached data after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1.matrixByRow_ == NULL, {}, "SoPlex", "free cached data after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1.matrixByCol_ == NULL, {}, "SoPlex", "free cached data after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1.colsol_ == NULL, {}, "SoPlex", "free cached data after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1.rowsol_ == NULL, {}, "SoPlex", "free cached data after adding row");
siC1rs = siC1.getRowSense();
OSIUNITTEST_ASSERT_ERROR(siC1rs[0] == 'G', {}, "SoPlex", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[1] == 'L', {}, "SoPlex", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[2] == 'E', {}, "SoPlex", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[3] == 'R', {}, "SoPlex", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[4] == 'R', {}, "SoPlex", "row sense after adding row");
OSIUNITTEST_ASSERT_ERROR(siC1rs[5] == 'N', {}, "SoPlex", "row sense after adding row");
siC1rhs = siC1.getRightHandSide();
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[0],2.5), {}, "SoPlex", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[1],2.1), {}, "SoPlex", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[2],4.0), {}, "SoPlex", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[3],5.0), {}, "SoPlex", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[4],15.), {}, "SoPlex", "right hand side after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rhs[5],0.0), {}, "SoPlex", "right hand side after adding row");
siC1rr = siC1.getRowRange();
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[0],0.0), {}, "SoPlex", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[1],0.0), {}, "SoPlex", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[2],0.0), {}, "SoPlex", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[3],5.0-1.8), {}, "SoPlex", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[4],15.0-3.0), {}, "SoPlex", "row range after adding row");
OSIUNITTEST_ASSERT_ERROR(eq(siC1rr[5],0.0), {}, "SoPlex", "row range after adding row");
lhs = siC1;
}
// Test that lhs has correct values even though siC1 has gone out of scope
OSIUNITTEST_ASSERT_ERROR(lhs.rowrange_ == NULL, {}, "SoPlex", "freed origin after assignment");
OSIUNITTEST_ASSERT_ERROR(lhs.rowsense_ == NULL, {}, "SoPlex", "freed origin after assignment");
OSIUNITTEST_ASSERT_ERROR(lhs.rhs_ == NULL, {}, "SoPlex", "freed origin after assignment");
OSIUNITTEST_ASSERT_ERROR(lhs.matrixByRow_ == NULL, {}, "SoPlex", "freed origin after assignment");
OSIUNITTEST_ASSERT_ERROR(lhs.matrixByCol_ == NULL, {}, "SoPlex", "freed origin after assignment");
OSIUNITTEST_ASSERT_ERROR(lhs.colsol_ == NULL, {}, "SoPlex", "freed origin after assignment");
OSIUNITTEST_ASSERT_ERROR(lhs.rowsol_ == NULL, {}, "SoPlex", "freed origin after assignment");
const char * lhsrs = lhs.getRowSense();
OSIUNITTEST_ASSERT_ERROR(lhsrs[0] == 'G', {}, "SoPlex", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[1] == 'L', {}, "SoPlex", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[2] == 'E', {}, "SoPlex", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[3] == 'R', {}, "SoPlex", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[4] == 'R', {}, "SoPlex", "row sense after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsrs[5] == 'N', {}, "SoPlex", "row sense after assignment");
const double * lhsrhs = lhs.getRightHandSide();
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[0],2.5), {}, "SoPlex", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[1],2.1), {}, "SoPlex", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[2],4.0), {}, "SoPlex", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[3],5.0), {}, "SoPlex", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[4],15.), {}, "SoPlex", "right hand side after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrhs[5],0.0), {}, "SoPlex", "right hand side after assignment");
const double *lhsrr = lhs.getRowRange();
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[0],0.0), {}, "SoPlex", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[1],0.0), {}, "SoPlex", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[2],0.0), {}, "SoPlex", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[3],5.0-1.8), {}, "SoPlex", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[4],15.0-3.0), {}, "SoPlex", "row range after assignment");
OSIUNITTEST_ASSERT_ERROR(eq(lhsrr[5],0.0), {}, "SoPlex", "row range after assignment");
const CoinPackedMatrix * lhsmbr = lhs.getMatrixByRow();
OSIUNITTEST_ASSERT_ERROR(lhsmbr != NULL, {}, "SoPlex", "matrix by row after assignment");
OSIUNITTEST_ASSERT_ERROR(lhsmbr->getMajorDim() == 6, return, "SoPlex", "matrix by row after assignment: major dim");
OSIUNITTEST_ASSERT_ERROR(lhsmbr->getNumElements() == 14, return, "SoPlex", "matrix by row after assignment: num elements");
const double * ev = lhsmbr->getElements();
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 0], 3.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 1], 1.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 2],-2.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 3],-1.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 4],-1.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 5], 2.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 6], 1.1), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 7], 1.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 8], 1.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[ 9], 2.8), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[10],-1.2), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[11], 5.6), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[12], 1.0), {}, "SoPlex", "matrix by row after assignment: elements");
OSIUNITTEST_ASSERT_ERROR(eq(ev[13], 1.9), {}, "SoPlex", "matrix by row after assignment: elements");
const CoinBigIndex * mi = lhsmbr->getVectorStarts();
OSIUNITTEST_ASSERT_ERROR(mi[0] == 0, {}, "SoPlex", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[1] == 5, {}, "SoPlex", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[2] == 7, {}, "SoPlex", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[3] == 9, {}, "SoPlex", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[4] == 11, {}, "SoPlex", "matrix by row after assignment: vector starts");
OSIUNITTEST_ASSERT_ERROR(mi[5] == 14, {}, "SoPlex", "matrix by row after assignment: vector starts");
const int * ei = lhsmbr->getIndices();
OSIUNITTEST_ASSERT_ERROR(ei[ 0] == 0, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 1] == 1, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 2] == 3, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 3] == 4, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 4] == 7, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 5] == 1, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 6] == 2, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 7] == 2, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 8] == 5, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[ 9] == 3, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[10] == 6, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[11] == 0, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[12] == 4, {}, "SoPlex", "matrix by row after assignment: indices");
OSIUNITTEST_ASSERT_ERROR(ei[13] == 7, {}, "SoPlex", "matrix by row after assignment: indices");
}
//--------------
}
// Do common solverInterface testing by calling the
// base class testing method.
{
OsiSpxSolverInterface m;
OsiSolverInterfaceCommonUnitTest(&m, mpsDir,netlibDir);
}
}
//--------------------------------------------------------------------------
// test cut debugger methods.
void
OsiRowCutDebuggerUnitTest(const OsiSolverInterface * baseSiP, const std::string & mpsDir)
{
CoinRelFltEq eq;
// Test default constructor
{
OsiRowCutDebugger r;
OSIUNITTEST_ASSERT_ERROR(r.integerVariable_ == NULL, {}, "osirowcutdebugger", "default constructor");
OSIUNITTEST_ASSERT_ERROR(r.knownSolution_ == NULL, {}, "osirowcutdebugger", "default constructor");
OSIUNITTEST_ASSERT_ERROR(r.numberColumns_ == 0, {}, "osirowcutdebugger", "default constructor");
}
{
// Get non trivial instance
OsiSolverInterface * imP = baseSiP->clone();
std::string fn = mpsDir+"exmip1";
imP->readMps(fn.c_str(),"mps");
OSIUNITTEST_ASSERT_ERROR(imP->getNumRows() == 5, {}, "osirowcutdebugger", "read exmip1");
/*
Activate the debugger. The garbled name here is deliberate; the
debugger should isolate the portion of the string between '/' and
'.' (in normal use, this would be the base file name, stripped of
the prefix and extension).
*/
imP->activateRowCutDebugger("ab cd /x/ /exmip1.asc");
int i;
// return debugger
const OsiRowCutDebugger * debugger = imP->getRowCutDebugger();
OSIUNITTEST_ASSERT_ERROR(debugger != NULL, {}, "osirowcutdebugger", "return debugger");
OSIUNITTEST_ASSERT_ERROR(debugger->numberColumns_ == 8, {}, "osirowcutdebugger", "return debugger");
const bool type[]={0,0,1,1,0,0,0,0};
const double values[]= {2.5, 0, 1, 1, 0.5, 3, 0, 0.26315789473684253};
CoinPackedVector objCoefs(8,imP->getObjCoefficients());
bool type_ok = true;
#if 0
for (i=0;i<8;i++)
type_ok &= type[i] == debugger->integerVariable_[i];
OSIUNITTEST_ASSERT_ERROR(type_ok, {}, "osirowcutdebugger", "???");
#endif
double objValue = objCoefs.dotProduct(values);
double debuggerObjValue = objCoefs.dotProduct(debugger->knownSolution_);
OSIUNITTEST_ASSERT_ERROR(eq(objValue, debuggerObjValue), {}, "osirowcutdebugger", "objective value");
OsiRowCutDebugger rhs;
{
OsiRowCutDebugger rC1(*debugger);
OSIUNITTEST_ASSERT_ERROR(rC1.numberColumns_ == 8, {}, "osirowcutdebugger", "copy constructor");
type_ok = true;
for (i=0;i<8;i++)
type_ok &= type[i] == rC1.integerVariable_[i];
OSIUNITTEST_ASSERT_ERROR(type_ok, {}, "osirowcutdebugger", "copy constructor");
OSIUNITTEST_ASSERT_ERROR(eq(objValue,objCoefs.dotProduct(rC1.knownSolution_)), {}, "osirowcutdebugger", "copy constructor");
rhs = rC1;
OSIUNITTEST_ASSERT_ERROR(rhs.numberColumns_ == 8, {}, "osirowcutdebugger", "assignment operator");
type_ok = true;
for (i=0;i<8;i++)
type_ok &= type[i] == rhs.integerVariable_[i];
OSIUNITTEST_ASSERT_ERROR(type_ok, {}, "osirowcutdebugger", "assignment operator");
OSIUNITTEST_ASSERT_ERROR(eq(objValue,objCoefs.dotProduct(rhs.knownSolution_)), {}, "osirowcutdebugger", "assignment operator");
}
// Test that rhs has correct values even though lhs has gone out of scope
OSIUNITTEST_ASSERT_ERROR(rhs.numberColumns_ == 8, {}, "osirowcutdebugger", "assignment operator");
type_ok = true;
for (i=0;i<8;i++)
type_ok &= type[i] == rhs.integerVariable_[i];
OSIUNITTEST_ASSERT_ERROR(type_ok, {}, "osirowcutdebugger", "assignment operator");
OSIUNITTEST_ASSERT_ERROR(eq(objValue,objCoefs.dotProduct(rhs.knownSolution_)), {}, "osirowcutdebugger", "assignment operator");
OsiRowCut cut[2];
const int ne = 3;
int inx[ne] = { 0, 2, 3 };
double el[ne] = { 1., 1., 1. };
cut[0].setRow(ne,inx,el);
cut[0].setUb(5.);
el[1]=5;
cut[1].setRow(ne,inx,el);
cut[1].setUb(5);
OsiCuts cs;
cs.insert(cut[0]);
cs.insert(cut[1]);
OSIUNITTEST_ASSERT_ERROR(!debugger->invalidCut(cut[0]), {}, "osirowcutdebugger", "recognize (in)valid cut");
OSIUNITTEST_ASSERT_ERROR( debugger->invalidCut(cut[1]), {}, "osirowcutdebugger", "recognize (in)valid cut");
OSIUNITTEST_ASSERT_ERROR(debugger->validateCuts(cs,0,2) == 1, {}, "osirowcutdebugger", "recognize (in)valid cut");
OSIUNITTEST_ASSERT_ERROR(debugger->validateCuts(cs,0,1) == 0, {}, "osirowcutdebugger", "recognize (in)valid cut");
delete imP;
}
}
//--------------------------------------------------------------------------
// test the simple rounding cut generators methods.
void
CglSimpleRoundingUnitTest(
const OsiSolverInterface * baseSiP,
const std::string mpsDir )
{
// Test default constructor
{
CglSimpleRounding cg;
}
// Test copy & assignment
{
CglSimpleRounding rhs;
{
CglSimpleRounding cg;
CglSimpleRounding cgC(cg);
rhs=cg;
}
}
// Test gcd and gcdn
{
CglSimpleRounding cg;
int v = cg.gcd(122,356);
assert(v==2);
v=cg.gcd(356,122);
assert(v==2);
v=cg.gcd(54,67);
assert(v==1);
v=cg.gcd(67,54);
assert(v==1);
v=cg.gcd(485,485);
assert(v==485);
v=cg.gcd(17*13,17*23);
assert( v==17);
v=cg.gcd(17*13*5,17*23);
assert( v==17);
v=cg.gcd(17*13*23,17*23);
assert(v==17*23);
int a[4] = {12, 20, 32, 400};
v= cg.gcdv(4,a);
assert(v== 4);
int b[4] = {782, 4692, 51, 2754};
v= cg.gcdv(4,b);
assert(v== 17);
int c[4] = {50, 40, 30, 10};
v= cg.gcdv(4,c);
assert(v== 10);
}
// Test generate cuts method on exmip1.5.mps
{
CglSimpleRounding cg;
OsiSolverInterface * siP = baseSiP->clone();
std::string fn = mpsDir+"exmip1.5.mps";
siP->readMps(fn.c_str(),"");
OsiCuts cuts;
cg.generateCuts(*siP,cuts);
// there should be 3 cuts
int nRowCuts = cuts.sizeRowCuts();
assert(nRowCuts==3);
// get the last "sr"=simple rounding cut that was derived
OsiRowCut srRowCut2 = cuts.rowCut(2);
CoinPackedVector srRowCutPV2 = srRowCut2.row();
// this is what the last cut should look like: i.e. the "solution"
const int solSize = 2;
int solCols[solSize]={2,3};
double solCoefs[solSize]={5.0, 4.0};
OsiRowCut solRowCut;
solRowCut.setRow(solSize,solCols,solCoefs);
solRowCut.setLb(-COIN_DBL_MAX);
solRowCut.setUb(2.0);
// Test for equality between the derived cut and the solution cut
// Note: testing two OsiRowCuts are equal invokes testing two
// CoinPackedVectors are equal which invokes testing two doubles
// are equal. Usually not a good idea to test that two doubles are equal,
// but in this cut the "doubles" represent integer values. Also allow that
// different solvers have different orderings in packed vectors, which may
// not match the ordering defined for solRowCut.
assert(srRowCut2.OsiCut::operator==(solRowCut)) ;
assert(srRowCut2.row().isEquivalent(solRowCut.row())) ;
assert(srRowCut2.lb() == solRowCut.lb()) ;
assert(srRowCut2.ub() == solRowCut.ub()) ;
delete siP;
}
// Test generate cuts method on p0033
{
CglSimpleRounding cg;
OsiSolverInterface * siP = baseSiP->clone();
std::string fn = mpsDir+"p0033";
siP->readMps(fn.c_str(),"mps");
OsiCuts cuts;
cg.generateCuts(*siP,cuts);
// p0033 is the optimal solution to p0033
int objIndices[14] = {
0, 6, 7, 9, 13, 17, 18,
22, 24, 25, 26, 27, 28, 29 };
CoinPackedVector p0033(14,objIndices,1.0);
// test that none of the generated cuts
// chops off the optimal solution
int nRowCuts = cuts.sizeRowCuts();
OsiRowCut rcut;
CoinPackedVector rpv;
int i;
for (i=0; i<nRowCuts; i++){
rcut = cuts.rowCut(i);
rpv = rcut.row();
double p0033Sum = (rpv*p0033).sum();
double rcutub = rcut.ub();
assert (p0033Sum <= rcutub);
}
// test that the cuts improve the
// lp objective function value
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("Final LP min=%f\n\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
delete siP;
}
}
/** Standard cut generation methods. */
void
OaDecompositionBase::generateCuts(const OsiSolverInterface &si, OsiCuts & cs,
const CglTreeInfo info) {
if (nlp_ == NULL) {
throw CoinError("Error in cut generator for outer approximation no NLP ipopt assigned", "generateCuts", "OaDecompositionBase");
}
// babInfo is used to communicate with the b-and-b solver (Cbc or Bcp).
BabInfo * babInfo = dynamic_cast<BabInfo *> (si.getAuxiliaryInfo());
assert(babInfo);
assert(babInfo->babPtr());
numSols_ = babInfo->babPtr()->model().getSolutionCount ();
CglTreeInfo info_copy = info;
const CbcNode * node = babInfo->babPtr()->model().currentNode();
info_copy.level = (node == NULL) ? 0 : babInfo->babPtr()->model().currentNode()->depth();
if(babInfo->hasSolution()) numSols_ ++;
if (babInfo)
if (!babInfo->mipFeasible())
return;
//Get the continuous solution
const double *colsol = si.getColSolution();
vector<double> savedColLower(nlp_->getNumCols());
CoinCopyN(nlp_->getColLower(), nlp_->getNumCols(), savedColLower());
vector<double> savedColUpper(nlp_->getNumCols());
CoinCopyN(nlp_->getColUpper(), nlp_->getNumCols(), savedColUpper());
OsiBranchingInformation brInfo(nlp_, false);
brInfo.solution_ = colsol;
//Check integer infeasibility
bool isInteger = integerFeasible(*nlp_, brInfo, parameters_.cbcIntegerTolerance_,
objects_, nObjects_);
//Check nodeNumber if it did not change scan savedCuts_ if one is violated force it and exit
int nodeNumber = babInfo->babPtr()->model().getNodeCount();
if(nodeNumber == currentNodeNumber_){
#ifdef OA_DEBUG
printf("OA decomposition recalled from the same node!\n");
#endif
int numCuts = savedCuts_.sizeRowCuts();
for(int i = 0 ; i < numCuts ; i++){
//Check if cuts off solution
if(savedCuts_.rowCut(i).violated(colsol) > 0.){
#ifdef OA_DEBUG
printf("A violated saved cut has been found\n");
#endif
savedCuts_.rowCut(i).setEffectiveness(9.99e99);
cs.insert(savedCuts_.rowCut(i));
savedCuts_.eraseRowCut(i);
return;
i--; numCuts--;
}
}
}
else {
currentNodeNumber_ = nodeNumber;
savedCuts_.dumpCuts();
}
if (!isInteger) {
if (!doLocalSearch(babInfo))//create sub mip solver.
return;
}
//get the current cutoff
double cutoff;
si.getDblParam(OsiDualObjectiveLimit, cutoff);
// Save solvers state if needed
solverManip * lpManip = NULL;
if (lp_ != NULL) {
assert(lp_ == &si);
lpManip = new solverManip(lp_, true, leaveSiUnchanged_, true, true);
}
else {
lpManip = new solverManip(si);
}
lpManip->setObjects(objects_, nObjects_);
double milpBound = performOa(cs, *lpManip, babInfo, cutoff, info_copy);
if(babInfo->hasSolution()){
babInfo->babPtr()->model().setSolutionCount (numSols_ - 1);
}
//Transmit the bound found by the milp
{
if (milpBound>-1e100)
{
// Also store into solver
if (babInfo)
babInfo->setMipBound(milpBound);
}
} //Clean everything :
// Reset the two solvers
if (leaveSiUnchanged_)
lpManip->restore();
delete lpManip;
nlp_->setColLower(savedColLower());
nlp_->setColUpper(savedColUpper());
return;
}
//-------------------------------------------------------------
void
CglZeroHalf::generateCuts(const OsiSolverInterface & si, OsiCuts & cs,
const CglTreeInfo info)
{
if (mnz_) {
int cnum=0,cnzcnt=0;
int *cbeg=NULL, *ccnt=NULL,*cind=NULL,*cval=NULL,*crhs=NULL;
char *csense=NULL;
const double * solution = si.getColSolution();
if ((flags_&1)==0) {
// redo bounds
const double * columnLower = si.getColLower();
const double * columnUpper = si.getColUpper();
int numberColumns = si.getNumCols();
for (int iColumn=0;iColumn<numberColumns;iColumn++) {
if (vlb_[iColumn]!=COIN_INT_MAX) {
int ilo,iup;
double lo = columnLower[iColumn];
if (lo<-COIN_INT_MAX)
lo=-COIN_INT_MAX;
ilo= static_cast<int> (ceil(lo));
double up = columnUpper[iColumn];
if (up>COIN_INT_MAX)
up=COIN_INT_MAX;
iup= static_cast<int> (floor(up));
vlb_[iColumn]=ilo;
vub_[iColumn]=iup;
}
}
}
if (true) {
cutInfo_.sep_012_cut(mr_,mc_,mnz_,
mtbeg_,mtcnt_, mtind_, mtval_,
vlb_, vub_,
mrhs_, msense_,
solution,
info.inTree ? false : true,
&cnum,&cnzcnt,
&cbeg,&ccnt,&cind,&cval,&crhs,&csense);
} else {
int k = 4*mr_+2*mnz_;
int * temp = new int[k];
int * mtbeg = temp;
int * mtcnt = mtbeg + mr_;
int * mtind = mtcnt+mr_;
int * mtval = mtind+mnz_;
int * mrhs = mtval+mnz_;
char * msense = reinterpret_cast<char*> (mrhs+mr_);
int i;
k=0;
int kel=0;
for (i=0;i<mr_;i++) {
int kel2=kel;
int rhs = mrhs_[i];
for (int j=mtbeg_[i];j<mtbeg_[i]+mtcnt_[i];j++) {
int iColumn=mtind_[j];
int value=mtval_[j];
if (vlb_[iColumn]<vub_[iColumn]) {
mtind[kel]=mtind_[j];
mtval[kel++]=mtval_[j];
} else {
rhs -= vlb_[iColumn]*value;
}
}
if (kel>kel2) {
mtcnt[k]=kel-kel2;
mtbeg[k]=kel2;
mrhs[k]=rhs;
msense[k++]=msense_[i];
}
}
if (kel) {
cutInfo_.sep_012_cut(k,mc_,kel,
mtbeg,mtcnt, mtind, mtval,
vlb_, vub_,
mrhs, msense,
solution,
info.inTree ? false : true,
&cnum,&cnzcnt,
&cbeg,&ccnt,&cind,&cval,&crhs,&csense);
}
delete [] temp;
}
if (cnum) {
// add cuts
double * element = new double[mc_];
for (int i=0;i<cnum;i++) {
int n = ccnt[i];
int start = cbeg[i];
for (int j=0;j<n;j++)
element[j]=cval[start+j];
OsiRowCut rc;
if (csense[i]=='L') {
rc.setLb(-COIN_DBL_MAX);
rc.setUb(crhs[i]);
} else if (csense[i]=='G') {
rc.setLb(crhs[i]);
rc.setUb(COIN_DBL_MAX);
} else {
abort();
}
rc.setRow(n,cind+start,element,false);
if ((flags_&1)!=0)
rc.setGloballyValid();
//double violation = rc.violated(solution);
//if (violation>1.0e-6)
cs.insert(rc);
//else
//printf("violation of %g\n",violation);
}
delete [] element;
free(cbeg);
free(ccnt);
free(cind);
free(cval);
free(crhs);
free(csense);
}
}
}
// Solve
int CouenneFeasPump::milpPhase (double *nSol, double *iSol, int niter, int *nsuciter) {
const int depth = (model_ && (model_ -> currentNode ())) ? model_ -> currentNode () -> depth () : 0;
double time0 = CoinCpuTime();
// INTEGER PART /////////////////////////////////////////////////////////
// Solve IP using nSol as the initial point to minimize weighted
// l-1 distance from. If nSol==NULL, the MILP is created using the
// original milp's LP solution.
double z = solveMILP (nSol, iSol, niter, nsuciter);
// if no MILP solution was found, bail out
bool try_again = false;
if (!iSol || z >= COIN_DBL_MAX/2) {
problem_ -> Jnlst () -> Printf (J_WARNING, J_NLPHEURISTIC, "FP: could not find IP solution\n");
// find non-tabu solution in the solution pool
while (!pool_ -> Set (). empty ()) {
// EXTRACT the closest (to nSol) IP solution from the pool
pool_ -> findClosestAndReplace (iSol, iSol, problem_ -> nVars ());
CouenneFPsolution newSol (problem_, iSol);
// we found a solution that is not in the tabu list
if (tabuPool_ . find (newSol) == tabuPool_ . end ()) {
try_again = true;
break;
}
}
if (!try_again) { // try moving around current solution
// SCIP could not find a MILP solution and we're somewhat
// locked. Round current solution and feed it to the NLP. This
// is better than just bailing out.
int n = problem_ -> nVars ();
if (!iSol)
iSol = new double [n];
for (int i=0; i<n; i++)
iSol [i] = (problem_ -> Var (i) -> isInteger ()) ?
COUENNE_round (nSol [i]) :
nSol [i];
}
// if (!try_again) { // nothing to do, bail out
// problem_ -> Jnlst () -> Printf (J_WARNING, J_NLPHEURISTIC, "FP: could not find from pool either, bailing out\n");
// break;
// }
}
bool isChecked = false;
// If a solution was found, but is in the tabu list, two choices:
//
// 1) the pool is empty: do a round of cuts and repeat;
//
// 2) the pool is nonempty: extract the best solution from the
// pool and use it instead
CouenneFPsolution checkedSol (problem_, iSol, false); // false is for not allocating space for this
if (tabuPool_. find (checkedSol) == tabuPool_ . end ())
tabuPool_. insert (CouenneFPsolution (problem_, iSol)); // only insertion to tabu pool: we check its feasibility now
else {
problem_ -> Jnlst () -> Printf (J_WARNING, J_NLPHEURISTIC, "FP: found solution is tabu\n");
// Current solution was visited before. Replace it with another
// MILP solution from the pool, if any.
if (tabuMgt_ == FP_TABU_NONE) break;
else if ((tabuMgt_ == FP_TABU_POOL) && !(pool_ -> Set (). empty ())) {
// try to find non-tabu solution in the solution pool
do {
// retrieve the top solution from the pool
pool_ -> findClosestAndReplace (iSol, nSol, problem_ -> nVars ());
CouenneFPsolution newSol (problem_, iSol);
// we found a solution that is not in the tabu list
if (tabuPool_. find (newSol) == tabuPool_ . end ())
break;
// the pool is empty -> bail out
if (pool_ -> Set ().empty ())
{
delete[] iSol;
iSol = NULL;
}
} while( !pool_ -> Set ().empty() );
} else if (((tabuMgt_ == FP_TABU_CUT) ||
((pool_ -> Set (). empty ()) && iSol))) {
OsiCuts cs;
problem_ -> domain () -> push (problem_ -> nVars (), iSol, milp_ -> getColLower (), milp_ -> getColUpper (), false); // don't copy vectors
couenneCG_ -> genRowCuts (*milp_, cs, 0, NULL); // remaining three arguments NULL by default
problem_ -> domain () -> pop ();
if (cs.sizeRowCuts ()) {
milp_ -> applyCuts (cs);
if (nSep++ < nSepRounds_)
continue;
} else break; // nothing left to do, just bail out
} else if ((tabuMgt_ == FP_TABU_PERTURB) && iSol) {
// perturb solution
const CouNumber
*lb = milp_ -> getColLower (),
*ub = milp_ -> getColUpper ();
double
downMoves = 0.,
upMoves = 0.;
int startIndex = (int) floor (CoinDrand48 () * problem_ -> nOrigVars ());
for (int ii = problem_ -> nOrigVars (); ii--; lb++, ub++) {
if (problem_ -> Var (ii) -> Multiplicity () <= 0)
continue;
// make perturbation start from pseudo-random points
int i = (startIndex + ii) % problem_ -> nOrigVars ();
if (problem_ -> Var (i) -> isInteger ()) {
double
rnd = CoinDrand48 (),
down = 0.,
up = 1.;
// if there is room on the left (resp. right) of the
// solution, consider moving down (resp. up). Make moves
// less likely as we don't want to perturb too many
// variables
#define RND_DECR_EXPONENT .5
if (iSol [i] >= lb [i] + 1.) down = 1. / pow (1. + (downMoves += 1.), RND_DECR_EXPONENT);
if (iSol [i] <= ub [i] - 1.) up = 1. - 1. / pow (1. + (upMoves += 1.), RND_DECR_EXPONENT);
if (rnd < down) iSol [i] -= 1.;
else if (rnd > up) iSol [i] += 1.;
}
}
}
}
problem_ -> Jnlst () -> Printf (J_WARNING, J_NLPHEURISTIC, "FP: checking IP solution for feasibility\n");
isChecked = problem_ -> checkNLP0 (iSol, z, true,
false, // don't care about obj
true, // stop at first violation
true); // checkAll
// Possible improvement: if IP-infeasible or if z does not improve
// the best solution found so far, then try the following:
//
// 1) Fix integer variables to IP solution's corresponding components
// 2) Solve restriction with original obj
// 3) While not found (MI)NLP solution or
// solution MINLP infeasible or
// z not better
// 4) Get solution x* from pool
// 5) Solve with original objective
// 6) Done
// 7) If found solution, set it, otherwise keep previously found (IP-feasible) one
if ((!isChecked || // not MINLP feasible
z > problem_ -> getCutOff ())) { // not improving
problem_ -> Jnlst () -> Printf (J_WARNING, J_NLPHEURISTIC, "FP: infeasible/non-improving (feas==%d, z=%g, cutoff=%g), looping on pool\n", isChecked, z, problem_->getCutOff ());
bool try_again;
do {
try_again = false;
if (CoinCpuTime () > problem_ -> getMaxCpuTime ())
break;
// Check if fixing integers to those in iSol yields an
// infeasible problem. If so, don't optimize
if (fixIntVariables (iSol)) {
nlp_ -> setInitSol (iSol);
if (problem_ -> Jnlst () -> ProduceOutput (J_ALL, J_NLPHEURISTIC)) {
printf ("----------------------- Solving NLP:\n");
problem_ -> print ();
printf ("-----------------------\n");
}
status = app_ -> OptimizeTNLP (nlp_);
if (nlp_ -> getSolution ()) { // check if non-NULL
if (nSol) CoinCopyN (nlp_ -> getSolution (), problem_ -> nVars (), nSol);
else nSol = CoinCopyOfArray (nlp_ -> getSolution (), problem_ -> nVars ());
}
if (nlp_ -> getSolution () && (problem_ -> Jnlst () -> ProduceOutput (J_ALL, J_NLPHEURISTIC))) { // check if non-NULL
printf ("######################## NLP solution (loop through pool):\n");
for (int i=0; i< problem_ -> nVars ();) {
printf ("%+e ", nlp_ -> getSolution () [i]);
if (!(++i % 15)) printf ("\n");
}
}
z = nlp_ -> getSolValue ();
if (z < problem_ -> getCutOff ()) // don't waste time if not improving
isChecked = problem_ -> checkNLP0 (nSol, z, true,
false, // don't care about obj
true, // stop at first violation
true); // checkAll
if (isChecked && (z < problem_ -> getCutOff ()))
break;
}
// find non-tabu solution in the solution pool
while (!pool_ -> Set (). empty ()) {
// EXTRACT the closest (to nSol) IP solution from the pool
pool_ -> findClosestAndReplace (iSol, nSol, problem_ -> nVars ());
CouenneFPsolution newSol (problem_, iSol);
// we found a solution that is not in the tabu list
if (tabuPool_ . find (newSol) == tabuPool_ . end ()) {
try_again = true;
break;
}
}
} while (try_again);
}
// Whatever the previous block yielded, we are now going to check
// if we have a new solution, and if so we save it.
if (isChecked) {
problem_ -> Jnlst () -> Printf (J_WARNING, J_NLPHEURISTIC, "FP: IP solution is MINLP feasible\n");
// solution is MINLP feasible! Save it.
retval = 1;
objVal = z;
// Found a MINLP-feasible solution, but to keep diversity do NOT
// use the best available. Just use this.
//
// #ifdef FM_CHECKNLP2
// # ifdef FM_TRACE_OPTSOL
// problem_->getRecordBestSol()->update();
// best = problem_->getRecordBestSol()->getSol();
// objVal = problem_->getRecordBestSol()->getVal();
// # else /* not FM_TRACE_OPTSOL */
// best = problem_->getRecordBestSol()->getModSol(problem_->nVars());
// objVal = z;
// # endif /* not FM_TRACE_OPTSOL */
// #else /* not FM_CHECKNLP2 */
// # ifdef FM_TRACE_OPTSOL
// problem_->getRecordBestSol()->update(iSol, problem_->nVars(),
// z, problem_->getFeasTol());
// best = problem_->getRecordBestSol()->getSol();
// objVal = problem_->getRecordBestSol()->getVal();
// # else /* not FM_TRACE_OPTSOL */
best = iSol;
// objVal = z;
// # ifdef FM_TRACE_OPTSOL
// problem_->getRecordBestSol()->update();
// best = problem_->getRecordBestSol()->getSol();
// objVal = problem_->getRecordBestSol()->getVal();
// # endif /* not FM_TRACE_OPTSOL */
// #endif /* not FM_CHECKNLP2 */
if (z < problem_ -> getCutOff ()) {
problem_ -> setCutOff (objVal);
t_chg_bounds *chg_bds = NULL;
if (objInd >= 0) {
chg_bds = new t_chg_bounds [problem_ -> nVars ()];
chg_bds [objInd].setUpper (t_chg_bounds::CHANGED);
}
// If, with new cutoff, bound tightening clears the whole
// feasible set, stop
bool is_still_feas = problem_ -> btCore (chg_bds);
if (chg_bds)
delete [] chg_bds;
// don't tighten MILP if BT says it's infeasible
if (!is_still_feas)
break;
// Update lb/ub on milp and nlp here
const CouNumber
*plb = problem_ -> Lb (),
*pub = problem_ -> Ub (),
*mlb = milp_ -> getColLower (),
*mub = milp_ -> getColUpper ();
for (int i=problem_ -> nVars (), j=0; i--; ++j, ++plb, ++pub) {
bool neglect = problem_ -> Var (j) -> Multiplicity () <= 0;
if (*plb > *mlb++) milp_ -> setColLower (j, neglect ? 0. : *plb);
if (*pub < *mub++) milp_ -> setColUpper (j, neglect ? 0. : *pub);
}
}
break;
} else {
problem_ -> Jnlst () -> Printf (J_WARNING, J_NLPHEURISTIC, "FP: IP solution NOT MINLP feasible\n");
if (milpCuttingPlane_ == FP_CUT_EXTERNAL ||
milpCuttingPlane_ == FP_CUT_POST) {
// Solution is IP- but not MINLP feasible: it might get cut by
// linearization cuts. If so, add a round of cuts and repeat.
OsiCuts cs;
problem_ -> domain () -> push (milp_);
couenneCG_ -> genRowCuts (*milp_, cs, 0, NULL); // remaining three arguments NULL by default
problem_ -> domain () -> pop ();
if (cs.sizeRowCuts ()) {
// the (integer, NLP infeasible) solution could be separated
milp_ -> applyCuts (cs);
// found linearization cut, now re-solve MILP (not quite a FP)
if (milpCuttingPlane_ == FP_CUT_EXTERNAL &&
nSep++ < nSepRounds_)
continue;
}
}
}
}
void CglOddHole::generateCuts(const OsiRowCutDebugger * /*debugger*/,
const CoinPackedMatrix & rowCopy,
const double * solution,
const double * dj, OsiCuts & cs,
const int * suitableRow,
const int * fixedColumn,
const CglTreeInfo info,
bool packed)
{
CoinPackedMatrix columnCopy = rowCopy;
columnCopy.reverseOrdering();
// Get basic problem information
int nRows=columnCopy.getNumRows();
int nCols=columnCopy.getNumCols();
const int * column = rowCopy.getIndices();
const CoinBigIndex * rowStart = rowCopy.getVectorStarts();
const int * rowLength = rowCopy.getVectorLengths();
const int * row = columnCopy.getIndices();
const CoinBigIndex * columnStart = columnCopy.getVectorStarts();
const int * columnLength = columnCopy.getVectorLengths();
// we need only look at suitable rows and variables with unsatisfied 0-1
// lookup from true row to compressed matrix
int * mrow = new int[nRows];
// lookup from true column to compressed
int * lookup = new int[nCols];
// number of columns in compressed matrix
int nSmall=0;
int i;
//do lookup from true sequence to compressed
int n=0;
for (i=0;i<nRows;i++) {
if (suitableRow[i]>0) {
mrow[i]=n++;
} else {
mrow[i]=-1;
}
}
for (i=0;i<nCols;i++) {
if (!fixedColumn[i]) {
lookup[i]=nSmall++;
} else {
lookup[i]=-1;
}
}
int nSmall2=2*nSmall;
// we don't know how big matrix will be
#define MAXELS 50000
int maxels=MAXELS;
//How do I do reallocs in C++?
// 1.0 - value x(i) - value x(j) for each node pair (or reverse if cover)
double * cost = reinterpret_cast<double *> (malloc(maxels*sizeof(double)));
// arc i.e. j which can be reached from i
int * to= reinterpret_cast<int *> (malloc(maxels*sizeof(int)));
//original row for each arc
int * rowfound=reinterpret_cast<int *> (malloc(maxels*sizeof(int)));
// start of each column
int * starts=new int[2*nSmall+1];
starts[0]=0;
// useful array for marking if already connected
int * mark =new int[nSmall2];
memset(mark,0,nSmall2*sizeof(int));
n=0; //number of elements in matrix
for (i=0;i<nCols;i++) {
int icol=lookup[i];
if (icol>=0) {
// column in compressed matrix
int k;
double dd=1.0000001-solution[i];
mark[icol]=1;
// reallocate if matrix reached size limit
if (n+nCols>maxels) {
maxels*=2;
cost=reinterpret_cast<double *> (realloc(cost,maxels*sizeof(double)));
to=reinterpret_cast<int *> (realloc(to,maxels*sizeof(int)));
rowfound=reinterpret_cast<int *> (realloc(rowfound,maxels*sizeof(int)));
}
// get all other connected variables
for (k=columnStart[i];k<columnStart[i]+columnLength[i];k++) {
int irow=row[k];
int jrow=mrow[irow];
// but only if row in compressed matrix
if (jrow>=0) {
int j;
for (j=rowStart[irow];j<rowStart[irow]+rowLength[irow];j++) {
int jcol=column[j];
int kcol=lookup[jcol];
if (kcol>=0&&!mark[kcol]) {
cost[n]=dd-solution[jcol];
to[n]=kcol;
rowfound[n++]=irow;//original row
mark[kcol]=1;
}
}
}
}
starts[icol+1]=n;
// zero out markers for next column
mark[icol]=0;
for (k=starts[icol];k<starts[icol+1];k++) {
int ito=to[k];
if (ito<0||ito>=nSmall) abort();
mark[to[k]]=0;
}
}
}
//if cover then change sign - otherwise make sure positive
if (packed) {
for (i=0;i<n;i++) {
if (cost[i]<1.0e-10) {
cost[i]=1.0e-10;
}
}
} else {
for (i=0;i<n;i++) {
cost[i]=-cost[i];
if (cost[i]<1.0e-10) {
cost[i]=1.0e-10;
}
}
}
// we are going to double size
if (2*n>maxels) {
maxels=2*n;
cost=reinterpret_cast<double *> (realloc(cost,maxels*sizeof(double)));
to=reinterpret_cast<int *> (realloc(to,maxels*sizeof(int)));
rowfound=reinterpret_cast<int *> (realloc(rowfound,maxels*sizeof(int)));
}
/* copy and make bipartite*/
for (i=0;i<nSmall;i++) {
int k,j=i+nSmall;
for (k=starts[i];k<starts[i+1];k++) {
int ito=to[k];
to[n]=ito;
to[k]=ito+nSmall;
cost[n]=cost[k];
rowfound[n++]=rowfound[k];;
}
starts[j+1]=n;
}
//random numbers to winnow out duplicate cuts
double * check = new double[nCols];
if (info.randomNumberGenerator) {
const CoinThreadRandom * randomGenerator = info.randomNumberGenerator;
for (i=0;i<nCols;i++) {
check[i]=randomGenerator->randomDouble();
}
} else {
CoinSeedRandom(13579);
for (i=0;i<nCols;i++) {
check[i]=CoinDrand48(); // NOT on a thread by thread basis
}
}
// Shortest path algorithm from Dijkstra - is there a better one?
typedef struct {
double cost; //cost to starting node
int back; //previous node
} Path;
typedef struct {
double cost; //cost to starting node
int node; //node
} Item;
Item * stack = new Item [nSmall2];
Path * path = new Path [nSmall2];
// arrays below are used only if looks promising
// allocate here
// we don't know how many cuts will be generated
int ncuts=0;
int maxcuts=1000;
double * hash = reinterpret_cast<double *> (malloc(maxcuts*sizeof(double)));
// to clean (should not be needed)
int * clean = new int[nSmall2];
int * candidate = new int[CoinMax(nSmall2,nCols)];
double * element = new double[nCols];
// in case we want to sort
double_double_int_triple * sortit =
new double_double_int_triple [nCols];
memset(mark,0,nSmall2*sizeof(int));
int * countcol = new int[nCols];
memset(countcol,0,nCols*sizeof(int));
int bias = packed ? 0 : 1; //amount to add before halving
// If nSmall large then should do a randomized subset
// Improvement 1
int icol;
for (icol=0;icol<nSmall;icol++) {
int j;
int jcol=icol+nSmall;
int istack=1;
for (j=0;j<nSmall2;j++) {
path[j].cost=1.0e70;
path[j].back=nSmall2+1;
}
path[icol].cost=0.0;
path[icol].back=-1;
stack[0].cost=0.0;
stack[0].node=icol;
mark[icol]=1;
while(istack) {
Item thisItem=stack[--istack];
double thisCost=thisItem.cost;
int inode=thisItem.node;
int k;
mark[inode]=0; //say available for further work
// See if sorting every so many would help (and which way)?
// Improvement 2
for (k=starts[inode];k<starts[inode+1];k++) {
int jnode=to[k];
if (!mark[jnode]&&thisCost+cost[k]<path[jnode].cost-1.0e-12) {
path[jnode].cost=thisCost+cost[k];
path[jnode].back=inode;
// add to stack
stack[istack].cost=path[jnode].cost;
stack[istack++].node=jnode;
mark[jnode]=1;
#ifdef CGL_DEBUG
assert (istack<=nSmall2);
#endif
}
}
}
bool good=(path[jcol].cost<0.9999);
if (good) { /* try */
int ii;
int nrow2=0;
int nclean=0;
double sum=0;
#ifdef CGL_DEBUG
printf("** %d ",jcol-nSmall);
#endif
ii=1;
candidate[0]=jcol;
while(jcol!=icol) {
int jjcol;
jcol=path[jcol].back;
if (jcol>=nSmall) {
jjcol=jcol-nSmall;
} else {
jjcol=jcol;
}
#ifdef CGL_DEBUG
printf(" %d",jjcol);
#endif
if (mark[jjcol]) {
// good=false;
// probably means this is from another cycle (will have been found)
// one of cycles must be zero cost
// printf("variable already on chain!\n");
} else {
mark[jjcol]=1;
clean[nclean++]=jjcol;
candidate[ii++]=jcol;
#ifdef CGL_DEBUG
assert (ii<=nSmall2);
#endif
}
}
#ifdef CGL_DEBUG
printf("\n");
#endif
for (j=0;j<nclean;j++) {
int k=clean[j];
mark[k]=0;
}
if (good) {
int k;
for (k=ii-1;k>0;k--) {
int jk,kk=candidate[k];
int ix=0;
for (jk=starts[kk];jk<starts[kk+1];jk++) {
int ito=to[jk];
if (ito==candidate[k-1]) {
ix=1;
// back to original row
mrow[nrow2++]=rowfound[jk];
break;
}
}
if (!ix) {
good=false;
}
}
if ((nrow2&1)!=1) {
good=false;
}
if (good) {
int nincut=0;
for (k=0;k<nrow2;k++) {
int j,irow=mrow[k];
for (j=rowStart[irow];j<rowStart[irow]+rowLength[irow];j++) {
int icol=column[j];
if (!countcol[icol]) candidate[nincut++]=icol;
countcol[icol]++;
}
}
#ifdef CGL_DEBUG
printf("true constraint %d",nrow2);
#endif
nrow2=nrow2>>1;
double rhs=nrow2;
if (!packed) rhs++; // +1 for cover
ii=0;
for (k=0;k<nincut;k++) {
int jcol=candidate[k];
if (countcol[jcol]) {
#ifdef CGL_DEBUG
printf(" %d %d",jcol,countcol[jcol]);
#endif
int ihalf=(countcol[jcol]+bias)>>1;
if (ihalf) {
element[ii]=ihalf;
sum+=solution[jcol]*element[ii];
/*printf("%d %g %g\n",jcol,element[ii],sumall[jcol]);*/
candidate[ii++]=jcol;
}
countcol[jcol]=0;
}
}
#ifdef CGL_DEBUG
printf("\n");
#endif
OsiRowCut rc;
double violation=0.0;
if (packed) {
violation = sum-rhs;
rc.setLb(-COIN_DBL_MAX);
rc.setUb(rhs);
} else {
// other way for cover
violation = rhs-sum;
rc.setUb(COIN_DBL_MAX);
rc.setLb(rhs);
}
if (violation<minimumViolation_) {
#ifdef CGL_DEBUG
printf("why no cut\n");
#endif
good=false;
} else {
if (static_cast<double> (ii) * minimumViolationPer_>violation||
ii>maximumEntries_) {
#ifdef CGL_DEBUG
printf("why no cut\n");
#endif
if (packed) {
// sort and see if we can get down to length
// relax by taking out ones with solution 0.0
nincut=ii;
for (k=0;k<nincut;k++) {
int jcol=candidate[k];
double value = fabs(dj[jcol]);
if (solution[jcol])
value = -solution[jcol];
sortit[k].dj=value;
sortit[k].element=element[k];
sortit[k].sequence=jcol;
}
// sort
std::sort(sortit,sortit+nincut,double_double_int_triple_compare());
nincut = CoinMin(nincut,maximumEntries_);
sum=0.0;
for (k=0;k<nincut;k++) {
int jcol=sortit[k].sequence;
candidate[k]=jcol;
element[k]=sortit[k].element;
sum+=solution[jcol]*element[k];
}
violation = sum-rhs;
ii=nincut;
if (violation<minimumViolation_) {
good=false;
}
} else {
good=false;
}
}
}
if (good) {
//this assumes not many cuts
int j;
#if 0
double value=0.0;
for (j=0;j<ii;j++) {
int icol=candidate[j];
value += check[icol]*element[j];
}
#else
CoinPackedVector candidatePv(ii,candidate,element);
candidatePv.sortIncrIndex();
double value = candidatePv.dotProduct(check);
#endif
for (j=0;j<ncuts;j++) {
if (value==hash[j]) {
//could check equality - quicker just to assume
break;
}
}
if (j==ncuts) {
//new
if (ncuts==maxcuts) {
maxcuts *= 2;
hash = reinterpret_cast<double *> (realloc(hash,maxcuts*sizeof(double)));
}
hash[ncuts++]=value;
rc.setRow(ii,candidate,element);
#ifdef CGL_DEBUG
printf("sum %g rhs %g %d\n",sum,rhs,ii);
if (debugger)
assert(!debugger->invalidCut(rc));
#endif
cs.insert(rc);
}
}
}
/* end of adding cut */
}
}
}
delete [] countcol;
delete [] element;
delete [] candidate;
delete [] sortit;
delete [] clean;
delete [] path;
delete [] stack;
free(hash);
delete [] check;
delete [] mark;
delete [] starts;
delete [] lookup;
delete [] mrow;
free(rowfound);
free(to);
free(cost);
}