/*
Install the name information from a CoinModel object. CoinModel does not
maintain a name for the objective function (in fact, it has no concept of
objective function).
*/
void OsiSolverInterface::setRowColNames (CoinModel &mod)
{ int nameDiscipline,m,n ;
/*
Determine how we're handling names. It's possible that the underlying solver
has overridden getIntParam, but doesn't recognise OsiNameDiscipline. In that
case, we want to default to auto names
*/
bool recognisesOsiNames = getIntParam(OsiNameDiscipline,nameDiscipline) ;
if (recognisesOsiNames == false)
{ nameDiscipline = 0 ; }
/*
Whatever happens, we're about to clean out the current name vectors. Decide
on an appropriate size and call reallocRowColNames to adjust capacity.
*/
if (nameDiscipline == 0)
{ m = 0 ;
n = 0 ; }
else
{ m = mod.rowNames()->numberItems() ;
n = mod.columnNames()->numberItems() ; }
reallocRowColNames(rowNames_,m,colNames_,n) ;
/*
If name discipline is auto, we're done already. Otherwise, load 'em
up. As best I can see, there's no guarantee that we'll have names for all
rows and columns, so we need to pay attention.
*/
if (nameDiscipline != 0)
{ int maxRowNdx=-1, maxColNdx=-1 ;
const char *const *names = mod.rowNames()->names() ;
rowNames_.resize(m) ;
for (int i = 0 ; i < m ; i++)
{ std::string nme = names[i] ;
if (nme.length() == 0)
{ if (nameDiscipline == 2)
{ nme = dfltRowColName('r',i) ; } }
if (nme.length() > 0)
{ maxRowNdx = i ; }
rowNames_[i] = nme ; }
rowNames_.resize(maxRowNdx+1) ;
names = mod.columnNames()->names() ;
colNames_.resize(n) ;
for (int j = 0 ; j < n ; j++)
{ std::string nme = names[j] ;
if (nme.length() == 0)
{ if (nameDiscipline == 2)
{ nme = dfltRowColName('c',j) ; } }
if (nme.length() > 0)
{ maxColNdx = j ; }
colNames_[j] = nme ; }
colNames_.resize(maxColNdx+1) ; }
/*
And we're done.
*/
return ; }
// nothing to inherit from GC really
ColoredGraph solve(const Graph& gr) override {
CoinModel coinModel;
for (auto i = 0; i < gr.nodeCount(); ++i) {
coinModel.addCol(0, nullptr, nullptr, 0, gr.nodeCount()-1, 1, nullptr, true);
}
OsiClpSolverInterface solver;
solver.loadFromCoinModel(coinModel);
CbcModel model(solver);
model.setLogLevel(0);
model.passInEventHandler(make_unique<GC_LP_EventHandler>(recoveryPath).get());
if (use_heuristic) {
GC_LP_Heuristic heuristic;
model.addHeuristic(&heuristic);
}
AddRules(model, gr);
if (use_parallel) {
model.setNumberThreads(std::thread::hardware_concurrency());
}
if (max_seconds != 0) model.setMaximumSeconds(max_seconds);
model.initialSolve();
model.branchAndBound();
if (model.maximumSecondsReached()) Println(cout, "max seconds reached");
if (model.isSecondsLimitReached()) Println(cout, "seconds limit reached");
seconds_passed_ = model.getCurrentSeconds();
iterations_passed_ = model.getIterationCount();
const double *solution = model.bestSolution();
if (solution == nullptr) {
vector<Color> colors(gr.nodeCount());
iota(colors.begin(), colors.end(), 0);
return {gr, colors};
}
return ColoredGraph(gr, {solution, solution+gr.nodeCount()});
}
int main(int argc, const char *argv[])
{
try {
// Empty model
ClpSimplex model;
// Objective - just nonzeros
int objIndex[] = {0, 2};
double objValue[] = {1.0, 4.0};
// Upper bounds - as dense vector
double upper[] = {2.0, COIN_DBL_MAX, 4.0};
// Create space for 3 columns
model.resize(0, 3);
// Fill in
int i;
// Virtuous way
// First objective
for (i = 0; i < 2; i++)
model.setObjectiveCoefficient(objIndex[i], objValue[i]);
// Now bounds (lower will be zero by default but do again)
for (i = 0; i < 3; i++) {
model.setColumnLower(i, 0.0);
model.setColumnUpper(i, upper[i]);
}
/*
We could also have done in non-virtuous way e.g.
double * objective = model.objective();
and then set directly
*/
// Faster to add rows all at once - but this is easier to show
// Now add row 1 as >= 2.0
int row1Index[] = {0, 2};
double row1Value[] = {1.0, 1.0};
model.addRow(2, row1Index, row1Value,
2.0, COIN_DBL_MAX);
// Now add row 2 as == 1.0
int row2Index[] = {0, 1, 2};
double row2Value[] = {1.0, -5.0, 1.0};
model.addRow(3, row2Index, row2Value,
1.0, 1.0);
// solve
model.dual();
/*
Adding one row at a time has a significant overhead so let's
try a more complicated but faster way
First time adding in 10000 rows one by one
*/
model.allSlackBasis();
ClpSimplex modelSave = model;
double time1 = CoinCpuTime();
int k;
for (k = 0; k < 10000; k++) {
int row2Index[] = {0, 1, 2};
double row2Value[] = {1.0, -5.0, 1.0};
model.addRow(3, row2Index, row2Value,
1.0, 1.0);
}
printf("Time for 10000 addRow is %g\n", CoinCpuTime() - time1);
model.dual();
model = modelSave;
// Now use build
CoinBuild buildObject;
time1 = CoinCpuTime();
for (k = 0; k < 10000; k++) {
int row2Index[] = {0, 1, 2};
double row2Value[] = {1.0, -5.0, 1.0};
buildObject.addRow(3, row2Index, row2Value,
1.0, 1.0);
}
model.addRows(buildObject);
printf("Time for 10000 addRow using CoinBuild is %g\n", CoinCpuTime() - time1);
model.dual();
model = modelSave;
int del[] = {0, 1, 2};
model.deleteRows(2, del);
// Now use build +-1
CoinBuild buildObject2;
time1 = CoinCpuTime();
for (k = 0; k < 10000; k++) {
int row2Index[] = {0, 1, 2};
double row2Value[] = {1.0, -1.0, 1.0};
buildObject2.addRow(3, row2Index, row2Value,
1.0, 1.0);
}
model.addRows(buildObject2, true);
printf("Time for 10000 addRow using CoinBuild+-1 is %g\n", CoinCpuTime() - time1);
model.dual();
model = modelSave;
model.deleteRows(2, del);
// Now use build +-1
CoinModel modelObject2;
time1 = CoinCpuTime();
for (k = 0; k < 10000; k++) {
int row2Index[] = {0, 1, 2};
double row2Value[] = {1.0, -1.0, 1.0};
modelObject2.addRow(3, row2Index, row2Value,
1.0, 1.0);
}
model.addRows(modelObject2, true);
printf("Time for 10000 addRow using CoinModel+-1 is %g\n", CoinCpuTime() - time1);
model.dual();
model = ClpSimplex();
// Now use build +-1
CoinModel modelObject3;
time1 = CoinCpuTime();
for (k = 0; k < 10000; k++) {
int row2Index[] = {0, 1, 2};
double row2Value[] = {1.0, -1.0, 1.0};
modelObject3.addRow(3, row2Index, row2Value,
1.0, 1.0);
}
model.loadProblem(modelObject3, true);
printf("Time for 10000 addRow using CoinModel load +-1 is %g\n", CoinCpuTime() - time1);
model.writeMps("xx.mps");
model.dual();
model = modelSave;
// Now use model
CoinModel modelObject;
time1 = CoinCpuTime();
for (k = 0; k < 10000; k++) {
int row2Index[] = {0, 1, 2};
double row2Value[] = {1.0, -5.0, 1.0};
modelObject.addRow(3, row2Index, row2Value,
1.0, 1.0);
}
model.addRows(modelObject);
printf("Time for 10000 addRow using CoinModel is %g\n", CoinCpuTime() - time1);
model.dual();
model.writeMps("b.mps");
// Method using least memory - but most complicated
time1 = CoinCpuTime();
// Assumes we know exact size of model and matrix
// Empty model
ClpSimplex model2;
{
// Create space for 3 columns and 10000 rows
int numberRows = 10000;
int numberColumns = 3;
// This is fully dense - but would not normally be so
int numberElements = numberRows * numberColumns;
// Arrays will be set to default values
model2.resize(numberRows, numberColumns);
double * elements = new double [numberElements];
CoinBigIndex * starts = new CoinBigIndex [numberColumns+1];
int * rows = new int [numberElements];;
int * lengths = new int[numberColumns];
// Now fill in - totally unsafe but ....
// no need as defaults to 0.0 double * columnLower = model2.columnLower();
double * columnUpper = model2.columnUpper();
double * objective = model2.objective();
double * rowLower = model2.rowLower();
double * rowUpper = model2.rowUpper();
// Columns - objective was packed
for (k = 0; k < 2; k++) {
int iColumn = objIndex[k];
objective[iColumn] = objValue[k];
}
for (k = 0; k < numberColumns; k++)
columnUpper[k] = upper[k];
// Rows
for (k = 0; k < numberRows; k++) {
rowLower[k] = 1.0;
rowUpper[k] = 1.0;
}
// Now elements
double row2Value[] = {1.0, -5.0, 1.0};
CoinBigIndex put = 0;
for (k = 0; k < numberColumns; k++) {
starts[k] = put;
lengths[k] = numberRows;
double value = row2Value[k];
for (int i = 0; i < numberRows; i++) {
rows[put] = i;
elements[put] = value;
put++;
}
}
starts[numberColumns] = put;
// assign to matrix
CoinPackedMatrix * matrix = new CoinPackedMatrix(true, 0.0, 0.0);
matrix->assignMatrix(true, numberRows, numberColumns, numberElements,
elements, rows, starts, lengths);
ClpPackedMatrix * clpMatrix = new ClpPackedMatrix(matrix);
model2.replaceMatrix(clpMatrix, true);
printf("Time for 10000 addRow using hand written code is %g\n", CoinCpuTime() - time1);
// If matrix is really big could switch off creation of row copy
// model2.setSpecialOptions(256);
}
model2.dual();
model2.writeMps("a.mps");
// Print column solution
int numberColumns = model.numberColumns();
// Alternatively getColSolution()
double * columnPrimal = model.primalColumnSolution();
// Alternatively getReducedCost()
double * columnDual = model.dualColumnSolution();
// Alternatively getColLower()
double * columnLower = model.columnLower();
// Alternatively getColUpper()
double * columnUpper = model.columnUpper();
// Alternatively getObjCoefficients()
double * columnObjective = model.objective();
int iColumn;
std::cout << " Primal Dual Lower Upper Cost"
<< std::endl;
for (iColumn = 0; iColumn < numberColumns; iColumn++) {
double value;
std::cout << std::setw(6) << iColumn << " ";
value = columnPrimal[iColumn];
if (fabs(value) < 1.0e5)
std::cout << setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << setiosflags(std::ios::scientific) << std::setw(14) << value;
value = columnDual[iColumn];
if (fabs(value) < 1.0e5)
std::cout << setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << setiosflags(std::ios::scientific) << std::setw(14) << value;
value = columnLower[iColumn];
if (fabs(value) < 1.0e5)
std::cout << setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << setiosflags(std::ios::scientific) << std::setw(14) << value;
value = columnUpper[iColumn];
if (fabs(value) < 1.0e5)
std::cout << setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << setiosflags(std::ios::scientific) << std::setw(14) << value;
value = columnObjective[iColumn];
if (fabs(value) < 1.0e5)
std::cout << setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << setiosflags(std::ios::scientific) << std::setw(14) << value;
std::cout << std::endl;
}
std::cout << "--------------------------------------" << std::endl;
// Test CoinAssert
std::cout << "If Clp compiled with -g below should give assert, if with -O1 or COIN_ASSERT CoinError" << std::endl;
model = modelSave;
model.deleteRows(2, del);
// Deliberate error
model.deleteColumns(1, del + 2);
// Now use build +-1
CoinBuild buildObject3;
time1 = CoinCpuTime();
for (k = 0; k < 10000; k++) {
int row2Index[] = {0, 1, 2};
double row2Value[] = {1.0, -1.0, 1.0};
buildObject3.addRow(3, row2Index, row2Value,
1.0, 1.0);
}
model.addRows(buildObject3, true);
} catch (CoinError e) {
e.print();
if (e.lineNumber() >= 0)
std::cout << "This was from a CoinAssert" << std::endl;
}
return 0;
}
//--------------------------------------------------------------------------
// 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);
}
}
//--------------------------------------------------------------------------
// Test building a model
void
CoinModelUnitTest(const std::string & mpsDir,
const std::string & netlibDir, const std::string & testModel)
{
// Get a model
CoinMpsIO m;
std::string fn = mpsDir+"exmip1";
int numErr = m.readMps(fn.c_str(),"mps");
assert( numErr== 0 );
int numberRows = m.getNumRows();
int numberColumns = m.getNumCols();
// Build by row from scratch
{
CoinPackedMatrix matrixByRow = * m.getMatrixByRow();
const double * element = matrixByRow.getElements();
const int * column = matrixByRow.getIndices();
const CoinBigIndex * rowStart = matrixByRow.getVectorStarts();
const int * rowLength = matrixByRow.getVectorLengths();
const double * rowLower = m.getRowLower();
const double * rowUpper = m.getRowUpper();
const double * columnLower = m.getColLower();
const double * columnUpper = m.getColUpper();
const double * objective = m.getObjCoefficients();
int i;
CoinModel temp;
for (i=0; i<numberRows; i++) {
temp.addRow(rowLength[i],column+rowStart[i],
element+rowStart[i],rowLower[i],rowUpper[i],m.rowName(i));
}
// Now do column part
for (i=0; i<numberColumns; i++) {
temp.setColumnBounds(i,columnLower[i],columnUpper[i]);
temp.setColumnObjective(i,objective[i]);
if (m.isInteger(i))
temp.setColumnIsInteger(i,true);;
}
// write out
temp.writeMps("byRow.mps");
}
// Build by column from scratch and save
CoinModel model;
{
CoinPackedMatrix matrixByColumn = * m.getMatrixByCol();
const double * element = matrixByColumn.getElements();
const int * row = matrixByColumn.getIndices();
const CoinBigIndex * columnStart = matrixByColumn.getVectorStarts();
const int * columnLength = matrixByColumn.getVectorLengths();
const double * rowLower = m.getRowLower();
const double * rowUpper = m.getRowUpper();
const double * columnLower = m.getColLower();
const double * columnUpper = m.getColUpper();
const double * objective = m.getObjCoefficients();
int i;
for (i=0; i<numberColumns; i++) {
model.addColumn(columnLength[i],row+columnStart[i],
element+columnStart[i],columnLower[i],columnUpper[i],
objective[i],m.columnName(i),m.isInteger(i));
}
// Now do row part
for (i=0; i<numberRows; i++) {
model.setRowBounds(i,rowLower[i],rowUpper[i]);
}
// write out
model.writeMps("byColumn.mps");
}
// model was created by column - play around
{
CoinModel temp;
int i;
for (i=numberRows-1; i>=0; i--)
temp.setRowLower(i,model.getRowLower(i));
for (i=0; i<numberColumns; i++) {
temp.setColumnUpper(i,model.getColumnUpper(i));
temp.setColumnName(i,model.getColumnName(i));
}
for (i=numberColumns-1; i>=0; i--) {
temp.setColumnLower(i,model.getColumnLower(i));
temp.setColumnObjective(i,model.getColumnObjective(i));
temp.setColumnIsInteger(i,model.getColumnIsInteger(i));
}
for (i=0; i<numberRows; i++) {
temp.setRowUpper(i,model.getRowUpper(i));
temp.setRowName(i,model.getRowName(i));
}
// Now elements
for (i=0; i<numberRows; i++) {
CoinModelLink triple=model.firstInRow(i);
while (triple.column()>=0) {
temp(i,triple.column(),triple.value());
triple=model.next(triple);
}
}
// and by column
for (i=numberColumns-1; i>=0; i--) {
CoinModelLink triple=model.lastInColumn(i);
while (triple.row()>=0) {
assert (triple.value()==temp(triple.row(),i));
temp(triple.row(),i,triple.value());
triple=model.previous(triple);
}
}
// check equal
model.setLogLevel(1);
assert (!model.differentModel(temp,false));
}
// Try creating model with strings
{
CoinModel temp;
int i;
for (i=numberRows-1; i>=0; i--) {
double value = model.getRowLower(i);
if (value==-1.0)
temp.setRowLower(i,"minusOne");
else if (value==1.0)
temp.setRowLower(i,"sqrt(plusOne)");
else if (value==4.0)
temp.setRowLower(i,"abs(4*plusOne)");
else
temp.setRowLower(i,value);
}
for (i=0; i<numberColumns; i++) {
double value;
value = model.getColumnUpper(i);
if (value==-1.0)
temp.setColumnUpper(i,"minusOne");
else if (value==1.0)
temp.setColumnUpper(i,"plusOne");
else
temp.setColumnUpper(i,value);
temp.setColumnName(i,model.getColumnName(i));
}
for (i=numberColumns-1; i>=0; i--) {
temp.setColumnLower(i,model.getColumnLower(i));
temp.setColumnObjective(i,model.getColumnObjective(i));
temp.setColumnIsInteger(i,model.getColumnIsInteger(i));
}
for (i=0; i<numberRows; i++) {
double value = model.getRowUpper(i);
if (value==-1.0)
temp.setRowUpper(i,"minusOne");
else if (value==1.0)
temp.setRowUpper(i,"plusOne");
else
temp.setRowUpper(i,value);
temp.setRowName(i,model.getRowName(i));
}
// Now elements
for (i=0; i<numberRows; i++) {
CoinModelLink triple=model.firstInRow(i);
while (triple.column()>=0) {
double value = triple.value();
if (value==-1.0)
temp(i,triple.column(),"minusOne");
else if (value==1.0)
temp(i,triple.column(),"plusOne");
else if (value==-2.0)
temp(i,triple.column(),"minusOne-1.0");
else if (value==2.0)
temp(i,triple.column(),"plusOne+1.0+minusOne+(2.0-plusOne)");
else
temp(i,triple.column(),value);
triple=model.next(triple);
}
}
temp.associateElement("minusOne",-1.0);
temp.associateElement("plusOne",1.0);
temp.setProblemName("fromStrings");
temp.writeMps("string.mps");
// check equal
model.setLogLevel(1);
assert (!model.differentModel(temp,false));
}
// Test with various ways of generating
{
/*
Get a model. Try first with netlibDir, fall back to mpsDir (sampleDir)
if that fails.
*/
CoinMpsIO m;
std::string fn = netlibDir+testModel;
double time1 = CoinCpuTime();
int numErr = m.readMps(fn.c_str(),"");
if (numErr != 0) {
std::cout
<< "Could not read " << testModel << " in " << netlibDir
<< "; falling back to " << mpsDir << "." << std::endl ;
fn = mpsDir+testModel ;
numErr = m.readMps(fn.c_str(),"") ;
if (numErr != 0) {
std::cout << "Could not read " << testModel << "; skipping test." << std::endl ;
}
}
if (numErr == 0) {
std::cout
<< "Time for readMps is "
<< (CoinCpuTime()-time1) << " seconds." << std::endl ;
int numberRows = m.getNumRows();
int numberColumns = m.getNumCols();
// Build model
CoinModel model;
CoinPackedMatrix matrixByRow = * m.getMatrixByRow();
const double * element = matrixByRow.getElements();
const int * column = matrixByRow.getIndices();
const CoinBigIndex * rowStart = matrixByRow.getVectorStarts();
const int * rowLength = matrixByRow.getVectorLengths();
const double * rowLower = m.getRowLower();
const double * rowUpper = m.getRowUpper();
const double * columnLower = m.getColLower();
const double * columnUpper = m.getColUpper();
const double * objective = m.getObjCoefficients();
int i;
for (i=0; i<numberRows; i++) {
model.addRow(rowLength[i],column+rowStart[i],
element+rowStart[i],rowLower[i],rowUpper[i],m.rowName(i));
}
// Now do column part
for (i=0; i<numberColumns; i++) {
model.setColumnBounds(i,columnLower[i],columnUpper[i]);
model.setColumnObjective(i,objective[i]);
model.setColumnName(i,m.columnName(i));
if (m.isInteger(i))
model.setColumnIsInteger(i,true);;
}
// Test
CoinSeedRandom(11111);
time1 = 0.0;
int nPass=50;
for (i=0; i<nPass; i++) {
double random = CoinDrand48();
int iSeed = (int) (random*1000000);
//iSeed = 776151;
CoinSeedRandom(iSeed);
std::cout << "before pass " << i << " with seed of " << iSeed << std::endl ;
buildRandom(model,CoinDrand48(),time1,i);
model.validateLinks();
}
std::cout
<< "Time for " << nPass << " CoinModel passes is "
<< time1 << " seconds\n" << std::endl ;
}
}
}
/* Build a model in some interesting way
Nine blocks defined by 4 random numbers
If next random number <0.4 addRow next possible
If <0.8 addColumn if possible
Otherwise do by element
For each one use random <0.5 to add rim at same time
At end fill in rim at random
*/
void buildRandom(CoinModel & baseModel, double random, double & timeIt, int iPass)
{
CoinModel model;
int numberRows = baseModel.numberRows();
int numberColumns = baseModel.numberColumns();
int numberElements = baseModel.numberElements();
// Row numbers and column numbers
int lastRow[4];
int lastColumn[4];
int i;
lastRow[0]=0;
lastColumn[0]=0;
lastRow[3]=numberRows;
lastColumn[3]=numberColumns;
for ( i=1; i<3; i++) {
int size;
size = (int) ((0.25*random+0.2)*numberRows);
random = CoinDrand48();
lastRow[i]=lastRow[i-1]+size;
size = (int) ((0.25*random+0.2)*numberColumns);
random = CoinDrand48();
lastColumn[i]=lastColumn[i-1]+size;
}
// whether block done 0 row first
char block[9]= {0,0,0,0,0,0,0,0,0};
// whether rowRim done
char rowDone[3]= {0,0,0};
// whether columnRim done
char columnDone[3]= {0,0,0};
// Save array for deleting elements
CoinModelTriple * dTriple = new CoinModelTriple[numberElements];
numberElements=0;
double time1 = CoinCpuTime();
for (int jBlock=0; jBlock<9; jBlock++) {
int iType=-1;
int iBlock=-1;
if (random<0.4) {
// trying addRow
int j;
for (j=0; j<3; j++) {
int k;
for (k=0; k<3; k++) {
if (block[3*j+k])
break; //already taken
}
if (k==3) {
// can do but decide which one
iBlock = 3*j + (int) (CoinDrand48()*0.3);
iType=0;
break;
}
}
}
if (iType==-1&&random<0.8) {
// trying addRow
int j;
for (j=0; j<3; j++) {
int k;
for (k=0; k<3; k++) {
if (block[j+3*k])
break; //already taken
}
if (k==3) {
// can do but decide which one
iBlock = j + 3*((int) (CoinDrand48()*0.3));
iType=1;
break;
}
}
}
if (iType==-1) {
iType=2;
int j;
for (j=0; j<9; j++) {
if (!block[j]) {
iBlock=j;
break;
}
}
}
random=CoinDrand48();
assert (iBlock>=0&&iBlock<9);
assert (iType>=0);
assert (!block[iBlock]);
block[iBlock]=static_cast<char>(1+iType);
int jRow = iBlock/3;
int jColumn = iBlock%3;
bool doRow = (CoinDrand48()<0.5)&&!rowDone[jRow];
bool doColumn = (CoinDrand48()<0.5&&!columnDone[jColumn]);
if (!iType) {
// addRow
int * column = new int[lastColumn[jColumn+1]-lastColumn[jColumn]];
double * element = new double[lastColumn[jColumn+1]-lastColumn[jColumn]];
for (i=lastRow[jRow]; i<lastRow[jRow+1]; i++) {
int n=0;
CoinModelLink triple=baseModel.firstInRow(i);
while (triple.column()>=0) {
if (triple.column()>=lastColumn[jColumn]&&triple.column()<lastColumn[jColumn+1]) {
column[n]=triple.column();
element[n++]=triple.value();
}
triple=baseModel.next(triple);
}
assert (i>=model.numberRows());
if (i>model.numberRows()) {
assert (i==lastRow[jRow]);
std::cout << "need to fill in rows" << std::endl ;
for (int k=0; k<jRow; k++) {
int start = CoinMax(lastRow[k],model.numberRows());
int end = lastRow[k+1];
bool doBounds = rowDone[k]!=0;
for (int j=start; j<end; j++) {
if (doBounds)
model.addRow(0,NULL,NULL,baseModel.rowLower(j),
baseModel.rowUpper(j),baseModel.rowName(j));
else
model.addRow(0,NULL,NULL);
}
}
}
if (doRow)
model.addRow(n,column,element,baseModel.rowLower(i),
baseModel.rowUpper(i),baseModel.rowName(i));
else
model.addRow(n,column,element);
}
if (doRow) {
rowDone[jRow]=1;
}
delete [] column;
delete [] element;
} else if (iType==1) {
// addColumn
int * row = new int[lastRow[jRow+1]-lastRow[jRow]];
double * element = new double[lastRow[jRow+1]-lastRow[jRow]];
for (i=lastColumn[jColumn]; i<lastColumn[jColumn+1]; i++) {
int n=0;
CoinModelLink triple=baseModel.firstInColumn(i);
while (triple.row()>=0) {
if (triple.row()>=lastRow[jRow]&&triple.row()<lastRow[jRow+1]) {
row[n]=triple.row();
element[n++]=triple.value();
}
triple=baseModel.next(triple);
}
assert (i>=model.numberColumns());
if (i>model.numberColumns()) {
assert (i==lastColumn[jColumn]);
std::cout << "need to fill in columns" << std::endl ;
for (int k=0; k<jColumn; k++) {
int start = CoinMax(lastColumn[k],model.numberColumns());
int end = lastColumn[k+1];
bool doBounds = columnDone[k]!=0;
for (int j=start; j<end; j++) {
if (doBounds)
model.addColumn(0,NULL,NULL,baseModel.columnLower(j),
baseModel.columnUpper(j),baseModel.objective(j),
baseModel.columnName(j),baseModel.isInteger(j));
else
model.addColumn(0,NULL,NULL);
}
}
}
if (doColumn)
model.addColumn(n,row,element,baseModel.columnLower(i),
baseModel.columnUpper(i),baseModel.objective(i),
baseModel.columnName(i),baseModel.isInteger(i));
else
model.addColumn(n,row,element);
}
if (doColumn) {
columnDone[jColumn]=1;
}
delete [] row;
delete [] element;
} else {
// addElement
// Which way round ?
if (CoinDrand48()<0.5) {
// rim first
if (doRow) {
for (i=lastRow[jRow]; i<lastRow[jRow+1]; i++) {
model.setRowLower(i,baseModel.getRowLower(i));
model.setRowUpper(i,baseModel.getRowUpper(i));
model.setRowName(i,baseModel.getRowName(i));
}
rowDone[jRow]=1;
}
if (doColumn) {
for (i=lastColumn[jColumn]; i<lastColumn[jColumn+1]; i++) {
model.setColumnLower(i,baseModel.getColumnLower(i));
model.setColumnUpper(i,baseModel.getColumnUpper(i));
model.setColumnName(i,baseModel.getColumnName(i));
model.setColumnObjective(i,baseModel.getColumnObjective(i));
model.setColumnIsInteger(i,baseModel.getColumnIsInteger(i));
}
columnDone[jColumn]=1;
}
if (CoinDrand48()<0.3) {
// by row
for (i=lastRow[jRow]; i<lastRow[jRow+1]; i++) {
CoinModelLink triple=baseModel.firstInRow(i);
while (triple.column()>=0) {
int iColumn = triple.column();
if (iColumn>=lastColumn[jColumn]&&iColumn<lastColumn[jColumn+1])
model(i,triple.column(),triple.value());
triple=baseModel.next(triple);
}
}
} else if (CoinDrand48()<0.6) {
// by column
for (i=lastColumn[jColumn]; i<lastColumn[jColumn+1]; i++) {
CoinModelLink triple=baseModel.firstInColumn(i);
while (triple.row()>=0) {
int iRow = triple.row();
if (iRow>=lastRow[jRow]&&iRow<lastRow[jRow+1])
model(triple.row(),i,triple.value());
triple=baseModel.next(triple);
}
}
} else {
// scan through backwards
const CoinModelTriple * elements = baseModel.elements();
for (i=baseModel.numberElements()-1; i>=0; i--) {
int iRow = (int) rowInTriple(elements[i]);
int iColumn = elements[i].column;
if (iRow>=lastRow[jRow]&&iRow<lastRow[jRow+1]&&
iColumn>=lastColumn[jColumn]&&iColumn<lastColumn[jColumn+1])
model(iRow,iColumn,elements[i].value);
}
}
} else {
// elements first
if (CoinDrand48()<0.3) {
// by row
for (i=lastRow[jRow]; i<lastRow[jRow+1]; i++) {
CoinModelLink triple=baseModel.firstInRow(i);
while (triple.column()>=0) {
int iColumn = triple.column();
if (iColumn>=lastColumn[jColumn]&&iColumn<lastColumn[jColumn+1])
model(i,triple.column(),triple.value());
triple=baseModel.next(triple);
}
}
} else if (CoinDrand48()<0.6) {
// by column
for (i=lastColumn[jColumn]; i<lastColumn[jColumn+1]; i++) {
CoinModelLink triple=baseModel.firstInColumn(i);
while (triple.row()>=0) {
int iRow = triple.row();
if (iRow>=lastRow[jRow]&&iRow<lastRow[jRow+1])
model(triple.row(),i,triple.value());
triple=baseModel.next(triple);
}
}
} else {
// scan through backwards
const CoinModelTriple * elements = baseModel.elements();
for (i=baseModel.numberElements()-1; i>=0; i--) {
int iRow = (int) rowInTriple(elements[i]);
int iColumn = elements[i].column;
if (iRow>=lastRow[jRow]&&iRow<lastRow[jRow+1]&&
iColumn>=lastColumn[jColumn]&&iColumn<lastColumn[jColumn+1])
model(iRow,iColumn,elements[i].value);
}
}
if (doRow) {
for (i=lastRow[jRow]; i<lastRow[jRow+1]; i++) {
model.setRowLower(i,baseModel.getRowLower(i));
model.setRowUpper(i,baseModel.getRowUpper(i));
model.setRowName(i,baseModel.getRowName(i));
}
rowDone[jRow]=1;
}
if (doColumn) {
for (i=lastColumn[jColumn]; i<lastColumn[jColumn+1]; i++) {
model.setColumnLower(i,baseModel.getColumnLower(i));
model.setColumnUpper(i,baseModel.getColumnUpper(i));
model.setColumnName(i,baseModel.getColumnName(i));
model.setColumnObjective(i,baseModel.getColumnObjective(i));
model.setColumnIsInteger(i,baseModel.getColumnIsInteger(i));
}
columnDone[jColumn]=1;
}
}
}
// Mess up be deleting some elements
if (CoinDrand48()<0.3&&iPass>10) {
double random2=CoinDrand48();
double randomDelete = 0.2 + 0.5*random2; // fraction to delete
//model.validateLinks();
if (random2<0.2) {
// delete some rows
for (int j=lastRow[jRow]; j<lastRow[jRow+1]; j++) {
//model.validateLinks();
if (CoinDrand48()<randomDelete) {
// save and delete
double rowLower = model.rowLower(j);
double rowUpper = model.rowUpper(j);
char * rowName = CoinStrdup(model.rowName(j));
CoinModelLink triple=model.firstInRow(j);
while (triple.column()>=0) {
int iColumn = triple.column();
assert (j==triple.row());
setRowInTriple(dTriple[numberElements],j);
dTriple[numberElements].column=iColumn;
dTriple[numberElements].value = triple.value();
numberElements++;
triple=model.next(triple);
}
model.deleteRow(j);
if (rowDone[jRow]) {
// put back rim
model.setRowLower(j,rowLower);
model.setRowUpper(j,rowUpper);
model.setRowName(j,rowName);
}
free(rowName);
}
}
} else if (random2<0.4) {
// delete some columns
for (int j=lastColumn[jColumn]; j<lastColumn[jColumn+1]; j++) {
//model.validateLinks();
if (CoinDrand48()<randomDelete) {
// save and delete
double columnLower = model.columnLower(j);
double columnUpper = model.columnUpper(j);
double objective = model.objective(j);
bool integer = model.isInteger(j)!=0;
char * columnName = CoinStrdup(model.columnName(j));
CoinModelLink triple=model.firstInColumn(j);
while (triple.column()>=0) {
int iRow = triple.row();
assert (j==triple.column());
dTriple[numberElements].column = j;
setRowInTriple(dTriple[numberElements],iRow);
dTriple[numberElements].value = triple.value();
numberElements++;
triple=model.next(triple);
}
model.deleteColumn(j);
if (columnDone[jColumn]) {
// put back rim
model.setColumnLower(j,columnLower);
model.setColumnUpper(j,columnUpper);
model.setObjective(j,objective);
model.setIsInteger(j,integer);
model.setColumnName(j,columnName);
}
free(columnName);
}
}
} else {
// delete some elements
//model.validateLinks();
const CoinModelTriple * elements = baseModel.elements();
for (i=0; i<model.numberElements(); i++) {
int iRow = (int) rowInTriple(elements[i]);
int iColumn = elements[i].column;
if (iRow>=lastRow[jRow]&&iRow<lastRow[jRow+1]&&
iColumn>=lastColumn[jColumn]&&iColumn<lastColumn[jColumn+1]) {
if (CoinDrand48()<randomDelete) {
dTriple[numberElements].column = iColumn;
setRowInTriple(dTriple[numberElements],iRow);
dTriple[numberElements].value = elements[i].value;
int position = model.deleteElement(iRow,iColumn);
if (position>=0)
numberElements++;
}
}
}
}
}
}
// Do rim if necessary
for (int k=0; k<3; k++) {
if (!rowDone[k]) {
for (i=lastRow[k]; i<lastRow[k+1]; i++) {
model.setRowLower(i,baseModel.getRowLower(i));
model.setRowUpper(i,baseModel.getRowUpper(i));
model.setRowName(i,baseModel.getRowName(i));
}
}
if (!columnDone[k]) {
for (i=lastColumn[k]; i<lastColumn[k+1]; i++) {
model.setColumnLower(i,baseModel.getColumnLower(i));
model.setColumnUpper(i,baseModel.getColumnUpper(i));
model.setColumnName(i,baseModel.getColumnName(i));
model.setColumnObjective(i,baseModel.getColumnObjective(i));
model.setColumnIsInteger(i,baseModel.getColumnIsInteger(i));
}
}
}
// Put back any elements
for (i=0; i<numberElements; i++) {
model(rowInTriple(dTriple[i]),dTriple[i].column,dTriple[i].value);
}
delete [] dTriple;
timeIt += CoinCpuTime()-time1;
model.setLogLevel(1);
assert (!model.differentModel(baseModel,false));
}
int main(int argc, const char *argv[])
{
// Empty model
ClpSimplex model;
std::string mpsFileName;
if (argc >= 2) mpsFileName = argv[1];
else {
#if defined(NETLIBDIR)
mpsFileName = NETLIBDIR "/25fv47.mps";
#else
fprintf(stderr, "Do not know where to find netlib MPS files.\n");
exit(1);
#endif
}
int status = model.readMps(mpsFileName.c_str(), true);
if (status) {
fprintf(stderr, "Bad readMps %s\n", mpsFileName.c_str());
fprintf(stdout, "Bad readMps %s\n", mpsFileName.c_str());
exit(1);
}
// Point to data
int numberRows = model.numberRows();
const double * rowLower = model.rowLower();
const double * rowUpper = model.rowUpper();
int numberColumns = model.numberColumns();
const double * columnLower = model.columnLower();
const double * columnUpper = model.columnUpper();
const double * columnObjective = model.objective();
CoinPackedMatrix * matrix = model.matrix();
// get row copy
CoinPackedMatrix rowCopy = *matrix;
rowCopy.reverseOrdering();
const int * column = rowCopy.getIndices();
const int * rowLength = rowCopy.getVectorLengths();
const CoinBigIndex * rowStart = rowCopy.getVectorStarts();
const double * element = rowCopy.getElements();
//const int * row = matrix->getIndices();
//const int * columnLength = matrix->getVectorLengths();
//const CoinBigIndex * columnStart = matrix->getVectorStarts();
//const double * elementByColumn = matrix->getElements();
// solve
model.dual();
// Now build new model
CoinModel build;
double time1 = CoinCpuTime();
// Row bounds
int iRow;
for (iRow = 0; iRow < numberRows; iRow++) {
build.setRowBounds(iRow, rowLower[iRow], rowUpper[iRow]);
// optional name
build.setRowName(iRow, model.rowName(iRow).c_str());
}
// 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]);
// optional name
build.setColumnName(iColumn, model.columnName(iColumn).c_str());
}
// 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]);
}
double time2 = CoinCpuTime();
// Now create clpsimplex
ClpSimplex model2;
model2.loadProblem(build);
double time3 = CoinCpuTime();
printf("Time for build using CoinModel is %g (%g for loadproblem)\n", time3 - time1,
time3 - time2);
model2.dual();
// Now do with strings attached
// Save build to show how to go over rows
CoinModel saveBuild = build;
build = CoinModel();
time1 = CoinCpuTime();
// 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]);
}
}
time2 = CoinCpuTime();
// Now create ClpSimplex
// If small switch on error printing
if (numberColumns < 50)
build.setLogLevel(1);
int numberErrors = model2.loadProblem(build);
// should fail as we never set multiplier
assert(numberErrors);
time3 = CoinCpuTime() - time2;
// subtract out unsuccessful times
time1 += time3;
time2 += time3;
build.associateElement("multiplier", 0.0);
numberErrors = model2.loadProblem(build);
assert(!numberErrors);
time3 = CoinCpuTime();
printf("Time for build using CoinModel is %g (%g for successful loadproblem)\n", time3 - time1,
time3 - time2);
build.writeMps("zero.mps");
// 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);
numberErrors = model2.loadProblem(build, true);
assert(!numberErrors);
model2.dual();
}
return 0;
}
int main(int argc, const char *argv[])
{
{
// Empty model
ClpSimplex model;
// Bounds on rows - as dense vector
double lower[] = {2.0, 1.0};
double upper[] = {COIN_DBL_MAX, 1.0};
// Create space for 2 rows
model.resize(2, 0);
// Fill in
int i;
// Now row bounds
for (i = 0; i < 2; i++) {
model.setRowLower(i, lower[i]);
model.setRowUpper(i, upper[i]);
}
// Now add column 1
int column1Index[] = {0, 1};
double column1Value[] = {1.0, 1.0};
model.addColumn(2, column1Index, column1Value,
0.0, 2, 1.0);
// Now add column 2
int column2Index[] = {1};
double column2Value[] = { -5.0};
model.addColumn(1, column2Index, column2Value,
0.0, COIN_DBL_MAX, 0.0);
// Now add column 3
int column3Index[] = {0, 1};
double column3Value[] = {1.0, 1.0};
model.addColumn(2, column3Index, column3Value,
0.0, 4.0, 4.0);
// solve
model.dual();
/*
Adding one column at a time has a significant overhead so let's
try a more complicated but faster way
First time adding in 10000 columns one by one
*/
model.allSlackBasis();
ClpSimplex modelSave = model;
double time1 = CoinCpuTime();
int k;
for (k = 0; k < 10000; k++) {
int column2Index[] = {0, 1};
double column2Value[] = {1.0, -5.0};
model.addColumn(2, column2Index, column2Value,
0.0, 1.0, 10000.0);
}
printf("Time for 10000 addColumn is %g\n", CoinCpuTime() - time1);
model.dual();
model = modelSave;
// Now use build
CoinBuild buildObject;
time1 = CoinCpuTime();
for (k = 0; k < 100000; k++) {
int column2Index[] = {0, 1};
double column2Value[] = {1.0, -5.0};
buildObject.addColumn(2, column2Index, column2Value,
0.0, 1.0, 10000.0);
}
model.addColumns(buildObject);
printf("Time for 100000 addColumn using CoinBuild is %g\n", CoinCpuTime() - time1);
model.dual();
model = modelSave;
// Now use build +-1
int del[] = {0, 1, 2};
model.deleteColumns(3, del);
CoinBuild buildObject2;
time1 = CoinCpuTime();
for (k = 0; k < 10000; k++) {
int column2Index[] = {0, 1};
double column2Value[] = {1.0, 1.0, -1.0};
int bias = k & 1;
buildObject2.addColumn(2, column2Index, column2Value + bias,
0.0, 1.0, 10000.0);
}
model.addColumns(buildObject2, true);
printf("Time for 10000 addColumn using CoinBuild+-1 is %g\n", CoinCpuTime() - time1);
model.dual();
model = modelSave;
// Now use build +-1
model.deleteColumns(3, del);
CoinModel modelObject2;
time1 = CoinCpuTime();
for (k = 0; k < 10000; k++) {
int column2Index[] = {0, 1};
double column2Value[] = {1.0, 1.0, -1.0};
int bias = k & 1;
modelObject2.addColumn(2, column2Index, column2Value + bias,
0.0, 1.0, 10000.0);
}
model.addColumns(modelObject2, true);
printf("Time for 10000 addColumn using CoinModel+-1 is %g\n", CoinCpuTime() - time1);
//model.writeMps("xx.mps");
model.dual();
model = modelSave;
// Now use model
CoinModel modelObject;
time1 = CoinCpuTime();
for (k = 0; k < 100000; k++) {
int column2Index[] = {0, 1};
double column2Value[] = {1.0, -5.0};
modelObject.addColumn(2, column2Index, column2Value,
0.0, 1.0, 10000.0);
}
model.addColumns(modelObject);
printf("Time for 100000 addColumn using CoinModel is %g\n", CoinCpuTime() - time1);
model.dual();
// Print column solution Just first 3 columns
int numberColumns = model.numberColumns();
numberColumns = CoinMin(3, numberColumns);
// Alternatively getColSolution()
double * columnPrimal = model.primalColumnSolution();
// Alternatively getReducedCost()
double * columnDual = model.dualColumnSolution();
// Alternatively getColLower()
double * columnLower = model.columnLower(); // Alternatively getColUpper()
double * columnUpper = model.columnUpper();
// Alternatively getObjCoefficients()
double * columnObjective = model.objective();
int iColumn;
std::cout << " Primal Dual Lower Upper Cost"
<< std::endl;
for (iColumn = 0; iColumn < numberColumns; iColumn++) {
double value;
std::cout << std::setw(6) << iColumn << " ";
value = columnPrimal[iColumn];
if (fabs(value) < 1.0e5)
std::cout << std::setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << std::setiosflags(std::ios::scientific) << std::setw(14) << value;
value = columnDual[iColumn];
if (fabs(value) < 1.0e5)
std::cout << std::setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << std::setiosflags(std::ios::scientific) << std::setw(14) << value;
value = columnLower[iColumn];
if (fabs(value) < 1.0e5)
std::cout << std::setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << std::setiosflags(std::ios::scientific) << std::setw(14) << value;
value = columnUpper[iColumn];
if (fabs(value) < 1.0e5)
std::cout << std::setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << std::setiosflags(std::ios::scientific) << std::setw(14) << value;
value = columnObjective[iColumn];
if (fabs(value) < 1.0e5)
std::cout << std::setiosflags(std::ios::fixed | std::ios::showpoint) << std::setw(14) << value;
else
std::cout << std::setiosflags(std::ios::scientific) << std::setw(14) << value;
std::cout << std::endl;
}
std::cout << "--------------------------------------" << std::endl;
}
{
// Now copy a model
ClpSimplex model;
int status;
if (argc < 2) {
#if defined(SAMPLEDIR)
status = model.readMps(SAMPLEDIR "/p0033.mps", true);
#else
fprintf(stderr, "Do not know where to find sample MPS files.\n");
exit(1);
#endif
} else
status = model.readMps(argv[1]);
if (status) {
printf("errors on input\n");
exit(77);
}
model.initialSolve();
int numberRows = model.numberRows();
int numberColumns = model.numberColumns();
const double * rowLower = model.rowLower();
const double * rowUpper = model.rowUpper();
// Start off model2
ClpSimplex model2;
model2.addRows(numberRows, rowLower, rowUpper, NULL);
// Build object
CoinBuild buildObject;
// Add columns
const double * columnLower = model.columnLower();
const double * columnUpper = model.columnUpper();
const double * objective = model.objective();
CoinPackedMatrix * matrix = model.matrix();
const int * row = matrix->getIndices();
const int * columnLength = matrix->getVectorLengths();
const CoinBigIndex * columnStart = matrix->getVectorStarts();
const double * elementByColumn = matrix->getElements();
for (int iColumn = 0; iColumn < numberColumns; iColumn++) {
CoinBigIndex start = columnStart[iColumn];
buildObject.addColumn(columnLength[iColumn], row + start, elementByColumn + start,
columnLower[iColumn], columnUpper[iColumn],
objective[iColumn]);
}
// add in
model2.addColumns(buildObject);
model2.initialSolve();
}
{
// and again
ClpSimplex model;
int status;
if (argc < 2) {
#if defined(SAMPLEDIR)
status = model.readMps(SAMPLEDIR "/p0033.mps", true);
#else
fprintf(stderr, "Do not know where to find sample MPS files.\n");
exit(1);
#endif
} else
status = model.readMps(argv[1]);
if (status) {
printf("errors on input\n");
exit(77);
}
model.initialSolve();
int numberRows = model.numberRows();
int numberColumns = model.numberColumns();
const double * rowLower = model.rowLower();
const double * rowUpper = model.rowUpper();
// Build object
CoinModel buildObject;
for (int iRow = 0; iRow < numberRows; iRow++)
buildObject.setRowBounds(iRow, rowLower[iRow], rowUpper[iRow]);
// Add columns
const double * columnLower = model.columnLower();
const double * columnUpper = model.columnUpper();
const double * objective = model.objective();
CoinPackedMatrix * matrix = model.matrix();
const int * row = matrix->getIndices();
const int * columnLength = matrix->getVectorLengths();
const CoinBigIndex * columnStart = matrix->getVectorStarts();
const double * elementByColumn = matrix->getElements();
for (int iColumn = 0; iColumn < numberColumns; iColumn++) {
CoinBigIndex start = columnStart[iColumn];
buildObject.addColumn(columnLength[iColumn], row + start, elementByColumn + start,
columnLower[iColumn], columnUpper[iColumn],
objective[iColumn]);
}
// add in
ClpSimplex model2;
model2.loadProblem(buildObject);
model2.initialSolve();
}
return 0;
}
int main (int argc, const char *argv[])
{
// Get data
std::string fileName = "./sudoku_sample.csv";
if (argc>=2) fileName = argv[1];
FILE * fp = fopen(fileName.c_str(),"r");
if (!fp) {
printf("Unable to open file %s\n",fileName.c_str());
exit(0);
}
#define MAX_SIZE 16
int valueOffset=1;
double lo[MAX_SIZE*MAX_SIZE],up[MAX_SIZE*MAX_SIZE];
char line[80];
int row,column;
/***************************************
Read .csv file and see if 9 or 16 Su Doku
***************************************/
int size=9;
for (row=0;row<size;row++) {
fgets(line,80,fp);
// Get size of sudoku puzzle (9 or 16)
if (!row) {
int get=0;
size=1;
while (line[get]>=32) {
if (line[get]==',')
size++;
get++;
}
assert (size==9||size==16);
printf("Solving Su Doku of size %d\n",size);
if (size==16)
valueOffset=0;
}
int get=0;
for (column=0;column<size;column++) {
lo[size*row+column]=valueOffset;
up[size*row+column]=valueOffset-1+size;
if (line[get]!=','&&line[get]>=32) {
// skip blanks
if (line[get]==' ') {
get++;
continue;
}
int value = line[get]-'0';
if (size==9) {
assert (value>=1&&value<=9);
} else {
assert (size==16);
if (value<0||value>9) {
if (line[get]=='"') {
get++;
value = 10 + line[get]-'A';
if (value<10||value>15) {
value = 10 + line[get]-'a';
}
get++;
} else {
value = 10 + line[get]-'A';
if (value<10||value>15) {
value = 10 + line[get]-'a';
}
}
}
assert (value>=0&&value<=15);
}
lo[size*row+column]=value;
up[size*row+column]=value;
get++;
}
get++;
}
}
int block_size = (int) sqrt ((double) size);
/***************************************
Now build rules for all different
3*9 or 3*16 sets of variables
Number variables by row*size+column
***************************************/
int starts[3*MAX_SIZE+1];
int which[3*MAX_SIZE*MAX_SIZE];
int put=0;
int set=0;
starts[0]=0;
// By row
for (row=0;row<size;row++) {
for (column=0;column<size;column++)
which[put++]=row*size+column;
starts[set+1]=put;
set++;
}
// By column
for (column=0;column<size;column++) {
for (row=0;row<size;row++)
which[put++]=row*size+column;
starts[set+1]=put;
set++;
}
// By box
for (row=0;row<size;row+=block_size) {
for (column=0;column<size;column+=block_size) {
for (int row2=row;row2<row+block_size;row2++) {
for (int column2=column;column2<column+block_size;column2++)
which[put++]=row2*size+column2;
}
starts[set+1]=put;
set++;
}
}
OsiClpSolverInterface solver1;
/***************************************
Create model
Set variables to be general integer variables although
priorities probably mean that it won't matter
***************************************/
CoinModel build;
// Columns
char name[4];
for (row=0;row<size;row++) {
for (column=0;column<size;column++) {
if (row<10) {
if (column<10)
sprintf(name,"X%d%d",row,column);
else
sprintf(name,"X%d%c",row,'A'+(column-10));
} else {
if (column<10)
sprintf(name,"X%c%d",'A'+(row-10),column);
else
sprintf(name,"X%c%c",'A'+(row-10),'A'+(column-10));
}
double value = CoinDrand48()*100.0;
build.addColumn(0,NULL,NULL,lo[size*row+column],
up[size*row+column], value, name,true);
}
}
/***************************************
Now add in extra variables for N way branching
***************************************/
for (row=0;row<size;row++) {
for (column=0;column<size;column++) {
int iColumn = size*row+column;
double value = lo[iColumn];
if (value<up[iColumn]) {
for (int i=0;i<size;i++)
build.addColumn(0,NULL,NULL,0.0,1.0,0.0);
} else {
// fixed
// obviously could do better if we missed out variables
int which = ((int) value) - valueOffset;
for (int i=0;i<size;i++) {
if (i!=which)
build.addColumn(0,NULL,NULL,0.0,0.0,0.0);
else
build.addColumn(0,NULL,NULL,0.0,1.0,0.0);
}
}
}
}
/***************************************
Now rows
***************************************/
double values[]={1.0,1.0,1.0,1.0,
1.0,1.0,1.0,1.0,
1.0,1.0,1.0,1.0,
1.0,1.0,1.0,1.0};
int indices[MAX_SIZE+1];
double rhs = size==9 ? 45.0 : 120.0;
for (row=0;row<3*size;row++) {
int iStart = starts[row];
for (column=0;column<size;column++)
indices[column]=which[column+iStart];
build.addRow(size,indices,values,rhs,rhs);
}
double values2[MAX_SIZE+1];
values2[0]=-1.0;
for (row=0;row<size;row++)
values2[row+1]=row+valueOffset;
// Now add rows for extra variables
for (row=0;row<size;row++) {
for (column=0;column<size;column++) {
int iColumn = row*size+column;
int base = size*size + iColumn*size;
indices[0]=iColumn;
for (int i=0;i<size;i++)
indices[i+1]=base+i;
build.addRow(size+1,indices,values2,0.0,0.0);
}
}
solver1.loadFromCoinModel(build);
build.writeMps("xx.mps");
double time1 = CoinCpuTime();
solver1.initialSolve();
CbcModel model(solver1);
model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
model.solver()->setHintParam(OsiDoScale,false,OsiHintTry);
/***************************************
Add in All different cut generator and All different branching
So we will have integers then cut branching then N way branching
in reverse priority order
***************************************/
// Cut generator
CglAllDifferent allDifferent(3*size,starts,which);
model.addCutGenerator(&allDifferent,-99,"allDifferent");
model.cutGenerator(0)->setWhatDepth(5);
CbcObject ** objects = new CbcObject * [4*size*size];
int nObj=0;
for (row=0;row<3*size;row++) {
int iStart = starts[row];
objects[row]= new CbcBranchAllDifferent(&model,size,which+iStart);
objects[row]->setPriority(2000+nObj); // do after rest satisfied
nObj++;
}
/***************************************
Add in N way branching and while we are at it add in cuts
***************************************/
CglStored stored;
for (row=0;row<size;row++) {
for (column=0;column<size;column++) {
int iColumn = row*size+column;
int base = size*size + iColumn*size;
int i;
for ( i=0;i<size;i++)
indices[i]=base+i;
CbcNWay * obj = new CbcNWay(&model,size,indices,nObj);
int seq[200];
int newUpper[200];
memset(newUpper,0,sizeof(newUpper));
for (i=0;i<size;i++) {
int state=9999;
int one=1;
int nFix=1;
// Fix real variable
seq[0]=iColumn;
newUpper[0]=valueOffset+i;
int kColumn = base+i;
int j;
// same row
for (j=0;j<size;j++) {
int jColumn = row*size+j;
int jjColumn = size*size+jColumn*size+i;
if (jjColumn!=kColumn) {
seq[nFix++]=jjColumn; // must be zero
}
}
// same column
for (j=0;j<size;j++) {
int jColumn = j*size+column;
int jjColumn = size*size+jColumn*size+i;
if (jjColumn!=kColumn) {
seq[nFix++]=jjColumn; // must be zero
}
}
// same block
int kRow = row/block_size;
kRow *= block_size;
int kCol = column/block_size;
kCol *= block_size;
for (j=kRow;j<kRow+block_size;j++) {
for (int jc=kCol;jc<kCol+block_size;jc++) {
int jColumn = j*size+jc;
int jjColumn = size*size+jColumn*size+i;
if (jjColumn!=kColumn) {
seq[nFix++]=jjColumn; // must be zero
}
}
}
// seem to need following?
const int * upperAddress = newUpper;
const int * seqAddress = seq;
CbcFixVariable fix(1,&state,&one,&upperAddress,&seqAddress,&nFix,&upperAddress,&seqAddress);
obj->setConsequence(indices[i],fix);
// Now do as cuts
for (int kk=1;kk<nFix;kk++) {
int jColumn = seq[kk];
int cutInd[2];
cutInd[0]=kColumn;
if (jColumn>kColumn) {
cutInd[1]=jColumn;
stored.addCut(-COIN_DBL_MAX,1.0,2,cutInd,values);
}
}
}
objects[nObj]= obj;
objects[nObj]->setPriority(nObj);
nObj++;
}
}
model.addObjects(nObj,objects);
for (row=0;row<nObj;row++)
delete objects[row];
delete [] objects;
model.messageHandler()->setLogLevel(1);
model.addCutGenerator(&stored,1,"stored");
// Say we want timings
int numberGenerators = model.numberCutGenerators();
int iGenerator;
for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
CbcCutGenerator * generator = model.cutGenerator(iGenerator);
generator->setTiming(true);
}
// Set this to get all solutions (all ones in newspapers should only have one)
//model.setCutoffIncrement(-1.0e6);
/***************************************
Do branch and bound
***************************************/
// Do complete search
model.branchAndBound();
std::cout<<"took "<<CoinCpuTime()-time1<<" seconds, "
<<model.getNodeCount()<<" nodes with objective "
<<model.getObjValue()
<<(!model.status() ? " Finished" : " Not finished")
<<std::endl;
/***************************************
Print solution and check it is feasible
We could modify output so could be imported by spreadsheet
***************************************/
if (model.getMinimizationObjValue()<1.0e50) {
const double * solution = model.bestSolution();
int put=0;
for (row=0;row<size;row++) {
for (column=0;column<size;column++) {
int value = (int) floor(solution[row*size+column]+0.5);
assert (value>=lo[put]&&value<=up[put]);
// save for later test
lo[put++]=value;
printf("%d ",value);
}
printf("\n");
}
// check valid
bool valid=true;
// By row
for (row=0;row<size;row++) {
put=0;
for (column=0;column<size;column++)
which[put++]=row*size+column;
assert (put==size);
int i;
for (i=0;i<put;i++)
which[i]=(int) lo[which[i]];
std::sort(which,which+put);
int last = valueOffset-1;
for (i=0;i<put;i++) {
int value=which[i];
if (value!=last+1)
valid=false;
last=value;
}
}
// By column
for (column=0;column<size;column++) {
put=0;
for (row=0;row<size;row++)
which[put++]=row*size+column;
assert (put==size);
int i;
for (i=0;i<put;i++)
which[i]=(int) lo[which[i]];
std::sort(which,which+put);
int last = valueOffset-1;
for (i=0;i<put;i++) {
int value=which[i];
if (value!=last+1)
valid=false;
last=value;
}
}
// By box
for (row=0;row<size;row+=block_size) {
for (column=0;column<size;column+=block_size) {
put=0;
for (int row2=row;row2<row+block_size;row2++) {
for (int column2=column;column2<column+block_size;column2++)
which[put++]=row2*size+column2;
}
assert (put==size);
int i;
for (i=0;i<put;i++)
which[i]=(int) lo[which[i]];
std::sort(which,which+put);
int last = valueOffset-1;
for (i=0;i<put;i++) {
int value=which[i];
if (value!=last+1)
valid=false;
last=value;
}
}
}
if (valid) {
printf("solution is valid\n");
} else {
printf("solution is not valid\n");
abort();
}
}
return 0;
}
int main (int argc, const char *argv[])
{
OsiClpSolverInterface solver1;
/*
We are going to treat x1 and x2 as integer and x3 and x4 as a set.
We define two new variables y1 == x1*x4 and y2 == x2*x3.
We define a variable z == x1*x4/x2*x3 so y2*z == y1
(we will treat y2 as a set)
Then we have objective - minimize w1 + w2 where
w1 - w2 = 1.0/6.931 - z
The model would be a lot smaller if we had column generation.
*/
// Create model
CoinModel build;
// Keep values of all variables for reporting purposes even if not necessary
/*
z is first, then x then y1,y2 then w1,w2
then y1 stuff, y2 stuff and finally y2 -> z stuff.
For rows same but 2 per y then rest of z stuff
*/
int loInt=12;
int hiInt=60;
int ybaseA=5, ybaseB=9, ylen=hiInt-loInt+1;
int base = ybaseB+2*2*ylen;
int yylen = hiInt*hiInt-loInt*loInt+1;
int zbase = 10;
int i;
// Do single variables
double value[] ={1.0,1.0};
int row[2];
/* z - obviously we can't choose bounds too tight but we need bounds
so choose 20% off as obviously feasible.
fastest way to solve would be too run for a few seconds to get
tighter bounds then re-formulate and solve. */
double loose=0.2;
double loZ = (1-loose)*(1.0/6.931), hiZ = (1+loose)*(1.0/6.931);
row[0]=0; // for reporting
row[1]=zbase+1; // for real use
build.addColumn(2,row,value,loZ, hiZ, 0.0);
// x
for (i=0;i<4;i++) {
row[0]=i+1;
build.addColumn(1,row,value,loInt, hiInt,0.0);
// we don't need to say x2, x3 integer but won't hurt
build.setInteger(i+1);
}
// y
for (i=0;i<2;i++) {
// y from x*x, and convexity
row[0]=ybaseA+2*i;
if (i==0)
row[1]=zbase+2; // yb*z == ya
else
row[1]=zbase-1; // to feed into z
build.addColumn(2,row,value,loInt*loInt, hiInt*hiInt,0.0);
// we don't need to say integer but won't hurt
build.setInteger(ybaseA+i);
}
// skip z convexity put w in final equation
row[0]=zbase+1;
build.addColumn(1,row,value,0.0,1.0,1.0);
value[0]=-1.0;
build.addColumn(1,row,value,0.0,1.0,1.0);
// Do columns so we know where each is
for (i=ybaseB;i<base+(2*yylen);i++)
build.setColumnBounds(i,0.0,1.0);
// Now do rows
// z definition
build.setRowBounds(0,0.0,0.0);
for (i=0;i<yylen;i++) {
// l
build.setElement(0,base+2*i,-loZ);
// u
build.setElement(0,base+2*i+1,-hiZ);
}
// x
for (i=0;i<2;i++) {
int iVarRow = 1+i;
int iSetRow = 4-i; // as it is x1*x4 and x2*x3
build.setRowBounds(iVarRow,0.0,0.0);
build.setRowBounds(iSetRow,0.0,0.0);
int j;
int base2 = ybaseB + 2*ylen*i;
for (j=0;j<ylen;j++) {
// l
build.setElement(iVarRow,base2+2*j,-loInt);
build.setElement(iSetRow,base2+2*j,-loInt-j);
// u
build.setElement(iVarRow,base2+2*j+1,-hiInt);
build.setElement(iSetRow,base2+2*j+1,-loInt-j);
}
}
// y
for (i=0;i<2;i++) {
int iRow = 5+2*i;
int iConvex = iRow+1;
build.setRowBounds(iRow,0.0,0.0);
build.setRowBounds(iConvex,1.0,1.0);
int j;
int base2 = ybaseB + 2*ylen*i;
for (j=0;j<ylen;j++) {
// l
build.setElement(iRow,base2+2*j,-loInt*(j+loInt));
build.setElement(iConvex,base2+2*j,1.0);
// u
build.setElement(iRow,base2+2*j+1,-hiInt*(j+loInt));
build.setElement(iConvex,base2+2*j+1,1.0);
}
}
// row that feeds into z and convexity
build.setRowBounds(zbase-1,0.0,0.0);
build.setRowBounds(zbase,1.0,1.0);
for (i=0;i<yylen;i++) {
// l
build.setElement(zbase-1,base+2*i,-(i+loInt*loInt));
build.setElement(zbase,base+2*i,1.0);
// u
build.setElement(zbase-1,base+2*i+1,-(i+loInt*loInt));
build.setElement(zbase,base+2*i+1,1.0);
}
// and real equation rhs
build.setRowBounds(zbase+1,1.0/6.931,1.0/6.931);
// z*y
build.setRowBounds(zbase+2,0.0,0.0);
for (i=0;i<yylen;i++) {
// l
build.setElement(zbase+2,base+2*i,-(i+loInt*loInt)*loZ);
// u
build.setElement(zbase+2,base+2*i+1,-(i+loInt*loInt)*hiZ);
}
// And finally two more rows to break symmetry
build.setRowBounds(zbase+3,-COIN_DBL_MAX,0.0);
build.setElement(zbase+3,1,1.0);
build.setElement(zbase+3,4,-1.0);
build.setRowBounds(zbase+4,-COIN_DBL_MAX,0.0);
build.setElement(zbase+4,2,1.0);
build.setElement(zbase+4,3,-1.0);
solver1.loadFromCoinModel(build);
// To make CbcBranchLink simpler assume that all variables with same i are consecutive
double time1 = CoinCpuTime();
solver1.initialSolve();
solver1.writeMps("bad");
CbcModel model(solver1);
model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
model.solver()->setHintParam(OsiDoScale,false,OsiHintTry);
CbcObject ** objects = new CbcObject * [3];
/* Format is number in sets, number in each link, first variable in matrix)
and then a weight for each in set to say where to branch.
In this case use NULL to say 0,1,2 ...
Finally a set number as ID.
*/
objects[0]=new CbcLink(&model,ylen,2,ybaseB,NULL,0);
objects[0]->setPriority(10);
objects[1]=new CbcLink(&model,ylen,2,ybaseB+2*ylen,NULL,0);
objects[1]->setPriority(20);
objects[2]=new CbcLink(&model,yylen,2,base,NULL,0);
objects[2]->setPriority(1);
model.addObjects(3,objects);
for (i=0;i<3;i++)
delete objects[i];
delete [] objects;
model.messageHandler()->setLogLevel(1);
// Do complete search
model.setDblParam(CbcModel::CbcMaximumSeconds,1200.0);
model.setDblParam(CbcModel::CbcCutoffIncrement,1.0e-8);
model.branchAndBound();
std::cout<<"took "<<CoinCpuTime()-time1<<" seconds, "
<<model.getNodeCount()<<" nodes with objective "
<<model.getObjValue()
<<(!model.status() ? " Finished" : " Not finished")
<<std::endl;
if (model.getMinimizationObjValue()<1.0e50) {
const double * solution = model.bestSolution();
int numberColumns = model.solver()->getNumCols();
double x1=solution[1];
double x2=solution[2];
double x3=solution[3];
double x4=solution[4];
printf("Optimal solution %g %g %g %g\n",x1,x2,x3,x4);
for (int iColumn=0;iColumn<numberColumns;iColumn++) {
double value=solution[iColumn];
if (fabs(value)>1.0e-7)
std::cout<<iColumn<<" "<<value<<std::endl;
}
}
return 0;
}
//-----------------------------------------------------------------------------
void CbcSolver2::resolve()
{
int numberColumns = modelPtr_->numberColumns();
if ((count_<10&&algorithm_==2)||!algorithm_) {
OsiClpSolverInterface::resolve();
if (modelPtr_->status()==0) {
count_++;
double * solution = modelPtr_->primalColumnSolution();
int i;
for (i=0;i<numberColumns;i++) {
if (solution[i]>1.0e-6||modelPtr_->getStatus(i)==ClpSimplex::basic) {
node_[i]=CoinMax(count_,node_[i]);
howMany_[i]++;
}
}
} else {
if (!algorithm_==2)
printf("infeasible early on\n");
}
} else {
// use counts
int numberRows=modelPtr_->numberRows();
int * whichRow = new int[numberRows];
int * whichColumn = new int [numberColumns];
int i;
const double * lower = modelPtr_->columnLower();
const double * upper = modelPtr_->columnUpper();
const double * rowUpper = modelPtr_->rowUpper();
bool equality=false;
for (i=0;i<numberRows;i++) {
if (rowUpper[i]==1.0) {
equality=true;
break;
}
}
setBasis(basis_,modelPtr_);
int nNewCol=0;
// Column copy
//const double * element = modelPtr_->matrix()->getElements();
const int * row = modelPtr_->matrix()->getIndices();
const CoinBigIndex * columnStart = modelPtr_->matrix()->getVectorStarts();
const int * columnLength = modelPtr_->matrix()->getVectorLengths();
int * rowActivity = new int[numberRows];
memset(rowActivity,0,numberRows*sizeof(int));
int * rowActivity2 = new int[numberRows];
memset(rowActivity2,0,numberRows*sizeof(int));
char * mark = new char[numberColumns];
memset(mark,0,numberColumns);
// Get rows which are satisfied
for (i=0;i<numberColumns;i++) {
if (lower[i]>0.0) {
CoinBigIndex j;
for (j=columnStart[i];
j<columnStart[i]+columnLength[i];j++) {
int iRow=row[j];
rowActivity2[iRow] ++;
}
} else if (!upper[i]) {
mark[i]=2; // no good
}
}
// If equality - check not infeasible
if (equality) {
bool feasible=true;
for (i=0;i<numberRows;i++) {
if (rowActivity2[i]>1) {
feasible=false;
break;
}
}
if (!feasible) {
delete [] rowActivity;
delete [] rowActivity2;
modelPtr_->setProblemStatus(1);
delete [] whichRow;
delete [] whichColumn;
delete [] mark;
printf("infeasible by inspection (over)\n");
return;
}
}
int nNoGood=0;
for (i=0;i<numberColumns;i++) {
if (mark[i]==2) {
nNoGood++;
continue;
}
bool choose;
if (algorithm_==1)
choose = true;
else
choose = (node_[i]>count_-memory_&&node_[i]>0);
bool any;
if (equality) {
// See if forced to be zero
CoinBigIndex j;
any=true;
for (j=columnStart[i];
j<columnStart[i]+columnLength[i];j++) {
int iRow=row[j];
if (rowActivity2[iRow])
any=false; // can't be in
}
} else {
// See if not useful
CoinBigIndex j;
any=false;
for (j=columnStart[i];
j<columnStart[i]+columnLength[i];j++) {
int iRow=row[j];
if (!rowActivity2[iRow])
any=true; // useful
}
}
if (!any&&!lower[i]) {
choose=false;
// and say can't be useful
mark[i]=2;
nNoGood++;
}
if (strategy_&&modelPtr_->getColumnStatus(i)==ClpSimplex::basic)
choose=true;
if (choose||lower[i]>0.0) {
mark[i]=1;
whichColumn[nNewCol++]=i;
CoinBigIndex j;
double value = upper[i];
if (value) {
for (j=columnStart[i];
j<columnStart[i]+columnLength[i];j++) {
int iRow=row[j];
rowActivity[iRow] ++;
}
}
}
}
// If equality add in slacks
CoinModel build;
if (equality) {
int row=0;
for (i=0;i<numberRows;i++) {
// put in all rows if wanted
if(strategy_)
rowActivity2[i]=0;
if (!rowActivity2[i]) {
double element=1.0;
build.addColumn(1,&row,&element,0.0,1.0,1.0e8); // large cost
row++;
}
}
}
int nOK=0;
int nNewRow=0;
for (i=0;i<numberRows;i++) {
if (rowActivity[i])
nOK++;
if (!rowActivity2[i])
whichRow[nNewRow++]=i; // not satisfied
else
modelPtr_->setRowStatus(i,ClpSimplex::basic); // make slack basic
}
if (nOK<numberRows) {
for (i=0;i<numberColumns;i++) {
if (!mark[i]) {
CoinBigIndex j;
int good=0;
for (j=columnStart[i];
j<columnStart[i]+columnLength[i];j++) {
int iRow=row[j];
if (!rowActivity[iRow]) {
rowActivity[iRow] ++;
good++;
}
}
if (good) {
nOK+=good;
whichColumn[nNewCol++]=i;
}
}
}
}
delete [] rowActivity;
delete [] rowActivity2;
if (nOK<numberRows) {
modelPtr_->setProblemStatus(1);
delete [] whichRow;
delete [] whichColumn;
delete [] mark;
printf("infeasible by inspection\n");
return;
}
bool allIn=false;
if (nNewCol+nNoGood+numberRows>numberColumns) {
// add in all
allIn=true;
for (i=0;i<numberColumns;i++) {
if (!mark[i]) {
whichColumn[nNewCol++]=i;
}
}
}
ClpSimplex * temp = new ClpSimplex(modelPtr_,nNewRow,whichRow,nNewCol,whichColumn);
if (equality)
temp->addColumns(build);
temp->setLogLevel(1);
printf("small has %d rows and %d columns (%d impossible to help) %s\n",
nNewRow,nNewCol,nNoGood,allIn ? "all in" : "");
temp->setSpecialOptions(128+512);
temp->setDualObjectiveLimit(1.0e50);
temp->dual();
assert (!temp->status());
double * solution = modelPtr_->primalColumnSolution();
const double * solution2 = temp->primalColumnSolution();
memset(solution,0,numberColumns*sizeof(double));
for (i=0;i<nNewCol;i++) {
int iColumn = whichColumn[i];
solution[iColumn]=solution2[i];
modelPtr_->setStatus(iColumn,temp->getStatus(i));
}
double * rowSolution = modelPtr_->primalRowSolution();
const double * rowSolution2 = temp->primalRowSolution();
double * dual = modelPtr_->dualRowSolution();
const double * dual2 = temp->dualRowSolution();
memset(dual,0,numberRows*sizeof(double));
for (i=0;i<nNewRow;i++) {
int iRow=whichRow[i];
modelPtr_->setRowStatus(iRow,temp->getRowStatus(i));
rowSolution[iRow]=rowSolution2[i];
dual[iRow]=dual2[i];
}
// See if optimal
double * dj = modelPtr_->dualColumnSolution();
// get reduced cost for large problem
// this assumes minimization
memcpy(dj,modelPtr_->objective(),numberColumns*sizeof(double));
modelPtr_->transposeTimes(-1.0,dual,dj);
modelPtr_->setObjectiveValue(temp->objectiveValue());
modelPtr_->setProblemStatus(0);
int nBad=0;
for (i=0;i<numberColumns;i++) {
if (modelPtr_->getStatus(i)==ClpSimplex::atLowerBound
&&upper[i]>lower[i]&&dj[i]<-1.0e-5)
nBad++;
}
//modelPtr_->writeMps("bada.mps");
//temp->writeMps("badb.mps");
delete temp;
if (nBad&&!allIn) {
assert (algorithm_==2);
//printf("%d bad\n",nBad);
timesBad_++;
// just non mark==2
int nAdded=0;
for (i=0;i<numberColumns;i++) {
if (!mark[i]) {
whichColumn[nNewCol++]=i;
nAdded++;
}
}
assert (nAdded);
{
temp = new ClpSimplex(modelPtr_,nNewRow,whichRow,nNewCol,whichColumn);
if (equality)
temp->addColumns(build);
temp->setLogLevel(2);
temp->setSpecialOptions(128+512);
temp->setDualObjectiveLimit(1.0e50);
temp->primal(1);
assert (!temp->status());
double * solution = modelPtr_->primalColumnSolution();
const double * solution2 = temp->primalColumnSolution();
memset(solution,0,numberColumns*sizeof(double));
for (i=0;i<nNewCol;i++) {
int iColumn = whichColumn[i];
solution[iColumn]=solution2[i];
modelPtr_->setStatus(iColumn,temp->getStatus(i));
}
double * rowSolution = modelPtr_->primalRowSolution();
const double * rowSolution2 = temp->primalRowSolution();
double * dual = modelPtr_->dualRowSolution();
const double * dual2 = temp->dualRowSolution();
memset(dual,0,numberRows*sizeof(double));
for (i=0;i<nNewRow;i++) {
int iRow=whichRow[i];
modelPtr_->setRowStatus(iRow,temp->getRowStatus(i));
rowSolution[iRow]=rowSolution2[i];
dual[iRow]=dual2[i];
}
modelPtr_->setObjectiveValue(temp->objectiveValue());
modelPtr_->setProblemStatus(0);
iterationsBad_ += temp->numberIterations();
printf("clean %d\n",temp->numberIterations());
delete temp;
}
}
delete [] mark;
delete [] whichRow;
delete [] whichColumn;
basis_ = getBasis(modelPtr_);
modelPtr_->setSpecialOptions(0);
count_++;
if ((count_%100)==0&&algorithm_==2)
printf("count %d, bad %d - iterations %d\n",count_,timesBad_,iterationsBad_);
for (i=0;i<numberColumns;i++) {
if (solution[i]>1.0e-6||modelPtr_->getStatus(i)==ClpSimplex::basic) {
node_[i]=CoinMax(count_,node_[i]);
howMany_[i]++;
}
}
if (modelPtr_->objectiveValue()>=modelPtr_->dualObjectiveLimit())
modelPtr_->setProblemStatus(1);
}
}
OsiSolverInterface *
expandKnapsack(CoinModel & model, int * whichColumn, int * knapsackStart,
int * knapsackRow, int &numberKnapsack,
CglStored & stored, int logLevel,
int fixedPriority, int SOSPriority, CoinModel & tightenedModel)
{
int maxTotal = numberKnapsack;
// load from coin model
OsiSolverLink *si = new OsiSolverLink();
OsiSolverInterface * finalModel = NULL;
si->setDefaultMeshSize(0.001);
// need some relative granularity
si->setDefaultBound(100.0);
si->setDefaultMeshSize(0.01);
si->setDefaultBound(100000.0);
si->setIntegerPriority(1000);
si->setBiLinearPriority(10000);
si->load(model, true, logLevel);
// get priorities
const int * priorities = model.priorities();
int numberColumns = model.numberColumns();
if (priorities) {
OsiObject ** objects = si->objects();
int numberObjects = si->numberObjects();
for (int iObj = 0; iObj < numberObjects; iObj++) {
int iColumn = objects[iObj]->columnNumber();
if (iColumn >= 0 && iColumn < numberColumns) {
#ifndef NDEBUG
OsiSimpleInteger * obj =
dynamic_cast <OsiSimpleInteger *>(objects[iObj]) ;
#endif
assert (obj);
int iPriority = priorities[iColumn];
if (iPriority > 0)
objects[iObj]->setPriority(iPriority);
}
}
if (fixedPriority > 0) {
si->setFixedPriority(fixedPriority);
}
if (SOSPriority < 0)
SOSPriority = 100000;
}
CoinModel coinModel = *si->coinModel();
assert(coinModel.numberRows() > 0);
tightenedModel = coinModel;
int numberRows = coinModel.numberRows();
// Mark variables
int * whichKnapsack = new int [numberColumns];
int iRow, iColumn;
for (iColumn = 0; iColumn < numberColumns; iColumn++)
whichKnapsack[iColumn] = -1;
int kRow;
bool badModel = false;
// analyze
if (logLevel > 1) {
for (iRow = 0; iRow < numberRows; iRow++) {
/* Just obvious one at first
positive non unit coefficients
all integer
positive rowUpper
for now - linear (but further down in code may use nonlinear)
column bounds should be tight
*/
//double lower = coinModel.getRowLower(iRow);
double upper = coinModel.getRowUpper(iRow);
if (upper < 1.0e10) {
CoinModelLink triple = coinModel.firstInRow(iRow);
bool possible = true;
int n = 0;
int n1 = 0;
while (triple.column() >= 0) {
int iColumn = triple.column();
const char * el = coinModel.getElementAsString(iRow, iColumn);
if (!strcmp("Numeric", el)) {
if (coinModel.columnLower(iColumn) == coinModel.columnUpper(iColumn)) {
triple = coinModel.next(triple);
continue; // fixed
}
double value = coinModel.getElement(iRow, iColumn);
if (value < 0.0) {
possible = false;
} else {
n++;
if (value == 1.0)
n1++;
if (coinModel.columnLower(iColumn) < 0.0)
possible = false;
if (!coinModel.isInteger(iColumn))
possible = false;
if (whichKnapsack[iColumn] >= 0)
possible = false;
}
} else {
possible = false; // non linear
}
triple = coinModel.next(triple);
}
if (n - n1 > 1 && possible) {
double lower = coinModel.getRowLower(iRow);
double upper = coinModel.getRowUpper(iRow);
CoinModelLink triple = coinModel.firstInRow(iRow);
while (triple.column() >= 0) {
int iColumn = triple.column();
lower -= coinModel.columnLower(iColumn) * triple.value();
upper -= coinModel.columnLower(iColumn) * triple.value();
triple = coinModel.next(triple);
}
printf("%d is possible %g <=", iRow, lower);
// print
triple = coinModel.firstInRow(iRow);
while (triple.column() >= 0) {
int iColumn = triple.column();
if (coinModel.columnLower(iColumn) != coinModel.columnUpper(iColumn))
printf(" (%d,el %g up %g)", iColumn, triple.value(),
coinModel.columnUpper(iColumn) - coinModel.columnLower(iColumn));
triple = coinModel.next(triple);
}
printf(" <= %g\n", upper);
}
}
}
}
numberKnapsack = 0;
for (kRow = 0; kRow < numberRows; kRow++) {
iRow = kRow;
/* Just obvious one at first
positive non unit coefficients
all integer
positive rowUpper
for now - linear (but further down in code may use nonlinear)
column bounds should be tight
*/
//double lower = coinModel.getRowLower(iRow);
double upper = coinModel.getRowUpper(iRow);
if (upper < 1.0e10) {
CoinModelLink triple = coinModel.firstInRow(iRow);
bool possible = true;
int n = 0;
int n1 = 0;
while (triple.column() >= 0) {
int iColumn = triple.column();
const char * el = coinModel.getElementAsString(iRow, iColumn);
if (!strcmp("Numeric", el)) {
if (coinModel.columnLower(iColumn) == coinModel.columnUpper(iColumn)) {
triple = coinModel.next(triple);
continue; // fixed
}
double value = coinModel.getElement(iRow, iColumn);
if (value < 0.0) {
possible = false;
} else {
n++;
if (value == 1.0)
n1++;
if (coinModel.columnLower(iColumn) < 0.0)
possible = false;
if (!coinModel.isInteger(iColumn))
possible = false;
if (whichKnapsack[iColumn] >= 0)
possible = false;
}
} else {
possible = false; // non linear
}
triple = coinModel.next(triple);
}
if (n - n1 > 1 && possible) {
// try
CoinModelLink triple = coinModel.firstInRow(iRow);
while (triple.column() >= 0) {
int iColumn = triple.column();
if (coinModel.columnLower(iColumn) != coinModel.columnUpper(iColumn))
whichKnapsack[iColumn] = numberKnapsack;
triple = coinModel.next(triple);
}
knapsackRow[numberKnapsack++] = iRow;
}
}
}
if (logLevel > 0)
printf("%d out of %d candidate rows are possible\n", numberKnapsack, numberRows);
// Check whether we can get rid of nonlinearities
/* mark rows
-2 in knapsack and other variables
-1 not involved
n only in knapsack n
*/
int * markRow = new int [numberRows];
for (iRow = 0; iRow < numberRows; iRow++)
markRow[iRow] = -1;
int canDo = 1; // OK and linear
for (iColumn = 0; iColumn < numberColumns; iColumn++) {
CoinModelLink triple = coinModel.firstInColumn(iColumn);
int iKnapsack = whichKnapsack[iColumn];
bool linear = true;
// See if quadratic objective
const char * expr = coinModel.getColumnObjectiveAsString(iColumn);
if (strcmp(expr, "Numeric")) {
linear = false;
}
while (triple.row() >= 0) {
int iRow = triple.row();
if (iKnapsack >= 0) {
if (markRow[iRow] == -1) {
markRow[iRow] = iKnapsack;
} else if (markRow[iRow] != iKnapsack) {
markRow[iRow] = -2;
}
}
const char * expr = coinModel.getElementAsString(iRow, iColumn);
if (strcmp(expr, "Numeric")) {
linear = false;
}
triple = coinModel.next(triple);
}
if (!linear) {
if (whichKnapsack[iColumn] < 0) {
canDo = 0;
break;
} else {
canDo = 2;
}
}
}
int * markKnapsack = NULL;
double * coefficient = NULL;
double * linear = NULL;
int * whichRow = NULL;
int * lookupRow = NULL;
badModel = (canDo == 0);
if (numberKnapsack && canDo) {
/* double check - OK if
no nonlinear
nonlinear only on columns in knapsack
nonlinear only on columns in knapsack * ONE other - same for all in knapsack
AND that is only row connected to knapsack
(theoretically could split knapsack if two other and small numbers)
also ONE could be ONE expression - not just a variable
*/
int iKnapsack;
markKnapsack = new int [numberKnapsack];
coefficient = new double [numberKnapsack];
linear = new double [numberColumns];
for (iKnapsack = 0; iKnapsack < numberKnapsack; iKnapsack++)
markKnapsack[iKnapsack] = -1;
if (canDo == 2) {
for (iRow = -1; iRow < numberRows; iRow++) {
int numberOdd;
CoinPackedMatrix * row = coinModel.quadraticRow(iRow, linear, numberOdd);
if (row) {
// see if valid
const double * element = row->getElements();
const int * column = row->getIndices();
const CoinBigIndex * columnStart = row->getVectorStarts();
const int * columnLength = row->getVectorLengths();
int numberLook = row->getNumCols();
for (int i = 0; i < numberLook; i++) {
int iKnapsack = whichKnapsack[i];
if (iKnapsack < 0) {
// might be able to swap - but for now can't have knapsack in
for (int j = columnStart[i]; j < columnStart[i] + columnLength[i]; j++) {
int iColumn = column[j];
if (whichKnapsack[iColumn] >= 0) {
canDo = 0; // no good
badModel = true;
break;
}
}
} else {
// OK if in same knapsack - or maybe just one
int marked = markKnapsack[iKnapsack];
for (int j = columnStart[i]; j < columnStart[i] + columnLength[i]; j++) {
int iColumn = column[j];
if (whichKnapsack[iColumn] != iKnapsack && whichKnapsack[iColumn] >= 0) {
canDo = 0; // no good
badModel = true;
break;
} else if (marked == -1) {
markKnapsack[iKnapsack] = iColumn;
marked = iColumn;
coefficient[iKnapsack] = element[j];
coinModel.associateElement(coinModel.columnName(iColumn), 1.0);
} else if (marked != iColumn) {
badModel = true;
canDo = 0; // no good
break;
} else {
// could manage with different coefficients - but for now ...
assert(coefficient[iKnapsack] == element[j]);
}
}
}
}
delete row;
}
}
}
if (canDo) {
// for any rows which are cuts
whichRow = new int [numberRows];
lookupRow = new int [numberRows];
bool someNonlinear = false;
double maxCoefficient = 1.0;
for (iKnapsack = 0; iKnapsack < numberKnapsack; iKnapsack++) {
if (markKnapsack[iKnapsack] >= 0) {
someNonlinear = true;
int iColumn = markKnapsack[iKnapsack];
maxCoefficient = CoinMax(maxCoefficient, fabs(coefficient[iKnapsack] * coinModel.columnUpper(iColumn)));
}
}
if (someNonlinear) {
// associate all columns to stop possible error messages
for (iColumn = 0; iColumn < numberColumns; iColumn++) {
coinModel.associateElement(coinModel.columnName(iColumn), 1.0);
}
}
ClpSimplex tempModel;
tempModel.loadProblem(coinModel);
// Create final model - first without knapsacks
int nCol = 0;
int nRow = 0;
for (iRow = 0; iRow < numberRows; iRow++) {
if (markRow[iRow] < 0) {
lookupRow[iRow] = nRow;
whichRow[nRow++] = iRow;
} else {
lookupRow[iRow] = -1;
}
}
for (iColumn = 0; iColumn < numberColumns; iColumn++) {
if (whichKnapsack[iColumn] < 0)
whichColumn[nCol++] = iColumn;
}
ClpSimplex finalModelX(&tempModel, nRow, whichRow, nCol, whichColumn, false, false, false);
OsiClpSolverInterface finalModelY(&finalModelX, true);
finalModel = finalModelY.clone();
finalModelY.releaseClp();
// Put back priorities
const int * priorities = model.priorities();
if (priorities) {
finalModel->findIntegers(false);
OsiObject ** objects = finalModel->objects();
int numberObjects = finalModel->numberObjects();
for (int iObj = 0; iObj < numberObjects; iObj++) {
int iColumn = objects[iObj]->columnNumber();
if (iColumn >= 0 && iColumn < nCol) {
#ifndef NDEBUG
OsiSimpleInteger * obj =
dynamic_cast <OsiSimpleInteger *>(objects[iObj]) ;
#endif
assert (obj);
int iPriority = priorities[whichColumn[iColumn]];
if (iPriority > 0)
objects[iObj]->setPriority(iPriority);
}
}
}
for (iRow = 0; iRow < numberRows; iRow++) {
whichRow[iRow] = iRow;
}
int numberOther = finalModel->getNumCols();
int nLargest = 0;
int nelLargest = 0;
int nTotal = 0;
for (iKnapsack = 0; iKnapsack < numberKnapsack; iKnapsack++) {
iRow = knapsackRow[iKnapsack];
int nCreate = maxTotal;
int nelCreate = coinModel.expandKnapsack(iRow, nCreate, NULL, NULL, NULL, NULL);
if (nelCreate < 0)
badModel = true;
nTotal += nCreate;
nLargest = CoinMax(nLargest, nCreate);
nelLargest = CoinMax(nelLargest, nelCreate);
}
if (nTotal > maxTotal)
badModel = true;
if (!badModel) {
// Now arrays for building
nelLargest = CoinMax(nelLargest, nLargest) + 1;
double * buildObj = new double [nLargest];
double * buildElement = new double [nelLargest];
int * buildStart = new int[nLargest+1];
int * buildRow = new int[nelLargest];
// alow for integers in knapsacks
OsiObject ** object = new OsiObject * [numberKnapsack+nTotal];
int nSOS = 0;
int nObj = numberKnapsack;
for (iKnapsack = 0; iKnapsack < numberKnapsack; iKnapsack++) {
knapsackStart[iKnapsack] = finalModel->getNumCols();
iRow = knapsackRow[iKnapsack];
int nCreate = 10000;
coinModel.expandKnapsack(iRow, nCreate, buildObj, buildStart, buildRow, buildElement);
// Redo row numbers
for (iColumn = 0; iColumn < nCreate; iColumn++) {
for (int j = buildStart[iColumn]; j < buildStart[iColumn+1]; j++) {
int jRow = buildRow[j];
jRow = lookupRow[jRow];
assert (jRow >= 0 && jRow < nRow);
buildRow[j] = jRow;
}
}
finalModel->addCols(nCreate, buildStart, buildRow, buildElement, NULL, NULL, buildObj);
int numberFinal = finalModel->getNumCols();
for (iColumn = numberOther; iColumn < numberFinal; iColumn++) {
if (markKnapsack[iKnapsack] < 0) {
finalModel->setColUpper(iColumn, maxCoefficient);
finalModel->setInteger(iColumn);
} else {
finalModel->setColUpper(iColumn, maxCoefficient + 1.0);
finalModel->setInteger(iColumn);
}
OsiSimpleInteger * sosObject = new OsiSimpleInteger(finalModel, iColumn);
sosObject->setPriority(1000000);
object[nObj++] = sosObject;
buildRow[iColumn-numberOther] = iColumn;
buildElement[iColumn-numberOther] = 1.0;
}
if (markKnapsack[iKnapsack] < 0) {
// convexity row
finalModel->addRow(numberFinal - numberOther, buildRow, buildElement, 1.0, 1.0);
} else {
int iColumn = markKnapsack[iKnapsack];
int n = numberFinal - numberOther;
buildRow[n] = iColumn;
buildElement[n++] = -fabs(coefficient[iKnapsack]);
// convexity row (sort of)
finalModel->addRow(n, buildRow, buildElement, 0.0, 0.0);
OsiSOS * sosObject = new OsiSOS(finalModel, n - 1, buildRow, NULL, 1);
sosObject->setPriority(iKnapsack + SOSPriority);
// Say not integral even if is (switch off heuristics)
sosObject->setIntegerValued(false);
object[nSOS++] = sosObject;
}
numberOther = numberFinal;
}
finalModel->addObjects(nObj, object);
for (iKnapsack = 0; iKnapsack < nObj; iKnapsack++)
delete object[iKnapsack];
delete [] object;
// Can we move any rows to cuts
const int * cutMarker = coinModel.cutMarker();
if (cutMarker && 0) {
printf("AMPL CUTS OFF until global cuts fixed\n");
cutMarker = NULL;
}
if (cutMarker) {
// Row copy
const CoinPackedMatrix * matrixByRow = finalModel->getMatrixByRow();
const double * elementByRow = matrixByRow->getElements();
const int * column = matrixByRow->getIndices();
const CoinBigIndex * rowStart = matrixByRow->getVectorStarts();
const int * rowLength = matrixByRow->getVectorLengths();
const double * rowLower = finalModel->getRowLower();
const double * rowUpper = finalModel->getRowUpper();
int nDelete = 0;
for (iRow = 0; iRow < numberRows; iRow++) {
if (cutMarker[iRow] && lookupRow[iRow] >= 0) {
int jRow = lookupRow[iRow];
whichRow[nDelete++] = jRow;
int start = rowStart[jRow];
stored.addCut(rowLower[jRow], rowUpper[jRow],
rowLength[jRow], column + start, elementByRow + start);
}
}
finalModel->deleteRows(nDelete, whichRow);
}
knapsackStart[numberKnapsack] = finalModel->getNumCols();
delete [] buildObj;
delete [] buildElement;
delete [] buildStart;
delete [] buildRow;
finalModel->writeMps("full");
}
}
}
delete [] whichKnapsack;
delete [] markRow;
delete [] markKnapsack;
delete [] coefficient;
delete [] linear;
delete [] whichRow;
delete [] lookupRow;
delete si;
si = NULL;
if (!badModel && finalModel) {
finalModel->setDblParam(OsiObjOffset, coinModel.objectiveOffset());
return finalModel;
} else {
delete finalModel;
printf("can't make knapsacks - did you set fixedPriority (extra1)\n");
return NULL;
}
}
