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;
}
int main(int argc, const char *argv[])
{
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);
}
{
// check if we need to change bounds to rows
int numberColumns = model.numberColumns();
const double * columnLower = model.columnLower();
const double * columnUpper = model.columnUpper();
int iColumn;
CoinBuild build;
double one = 1.0;
for (iColumn = 0; iColumn < numberColumns; iColumn++) {
if (columnUpper[iColumn] < 1.0e20 &&
columnLower[iColumn] > -1.0e20) {
if (fabs(columnLower[iColumn]) < fabs(columnUpper[iColumn])) {
double value = columnUpper[iColumn];
model.setColumnUpper(iColumn, COIN_DBL_MAX);
build.addRow(1, &iColumn, &one, -COIN_DBL_MAX, value);
} else {
double value = columnLower[iColumn];
model.setColumnLower(iColumn, -COIN_DBL_MAX);
build.addRow(1, &iColumn, &one, value, COIN_DBL_MAX);
}
}
}
if (build.numberRows())
model.addRows(build);
}
int numberColumns = model.numberColumns();
const double * columnLower = model.columnLower();
const double * columnUpper = model.columnUpper();
int numberRows = model.numberRows();
double * rowLower = CoinCopyOfArray(model.rowLower(), numberRows);
double * rowUpper = CoinCopyOfArray(model.rowUpper(), numberRows);
const double * objective = model.objective();
CoinPackedMatrix * matrix = model.matrix();
// get transpose
CoinPackedMatrix rowCopy = *matrix;
int iRow, iColumn;
int numberExtraRows = 0;
for (iRow = 0; iRow < numberRows; iRow++) {
if (rowLower[iRow] <= -1.0e20) {
} else if (rowUpper[iRow] >= 1.0e20) {
} else {
if (rowUpper[iRow] != rowLower[iRow])
numberExtraRows++;
}
}
const int * row = matrix->getIndices();
const int * columnLength = matrix->getVectorLengths();
const CoinBigIndex * columnStart = matrix->getVectorStarts();
const double * elementByColumn = matrix->getElements();
double objOffset = 0.0;
for (iColumn = 0; iColumn < numberColumns; iColumn++) {
double offset = 0.0;
if (columnUpper[iColumn] >= 1.0e20) {
if (columnLower[iColumn] > -1.0e20)
offset = columnLower[iColumn];
} else if (columnLower[iColumn] <= -1.0e20) {
offset = columnUpper[iColumn];
} else {
// taken care of before
abort();
}
if (offset) {
objOffset += offset * objective[iColumn];
for (CoinBigIndex j = columnStart[iColumn];
j < columnStart[iColumn] + columnLength[iColumn]; j++) {
int iRow = row[j];
if (rowLower[iRow] > -1.0e20)
rowLower[iRow] -= offset * elementByColumn[j];
if (rowUpper[iRow] < 1.0e20)
rowUpper[iRow] -= offset * elementByColumn[j];
}
}
}
int * which = new int[numberRows+numberExtraRows];
rowCopy.reverseOrdering();
rowCopy.transpose();
double * fromRowsLower = new double[numberRows+numberExtraRows];
double * fromRowsUpper = new double[numberRows+numberExtraRows];
double * newObjective = new double[numberRows+numberExtraRows];
double * fromColumnsLower = new double[numberColumns];
double * fromColumnsUpper = new double[numberColumns];
for (iColumn = 0; iColumn < numberColumns; iColumn++) {
// Offset is already in
if (columnUpper[iColumn] >= 1.0e20) {
if (columnLower[iColumn] > -1.0e20) {
fromColumnsLower[iColumn] = -COIN_DBL_MAX;
fromColumnsUpper[iColumn] = objective[iColumn];
} else {
// free
fromColumnsLower[iColumn] = objective[iColumn];
fromColumnsUpper[iColumn] = objective[iColumn];
}
} else if (columnLower[iColumn] <= -1.0e20) {
fromColumnsLower[iColumn] = objective[iColumn];
fromColumnsUpper[iColumn] = COIN_DBL_MAX;
} else {
abort();
}
}
int kRow = 0;
for (iRow = 0; iRow < numberRows; iRow++) {
if (rowLower[iRow] <= -1.0e20) {
assert(rowUpper[iRow] < 1.0e20);
newObjective[kRow] = -rowUpper[iRow];
fromRowsLower[kRow] = -COIN_DBL_MAX;
fromRowsUpper[kRow] = 0.0;
which[kRow] = iRow;
kRow++;
} else if (rowUpper[iRow] >= 1.0e20) {
newObjective[kRow] = -rowLower[iRow];
fromRowsLower[kRow] = 0.0;
fromRowsUpper[kRow] = COIN_DBL_MAX;
which[kRow] = iRow;
kRow++;
} else {
if (rowUpper[iRow] == rowLower[iRow]) {
newObjective[kRow] = -rowLower[iRow];
fromRowsLower[kRow] = -COIN_DBL_MAX;;
fromRowsUpper[kRow] = COIN_DBL_MAX;
which[kRow] = iRow;
kRow++;
} else {
// range
newObjective[kRow] = -rowUpper[iRow];
fromRowsLower[kRow] = -COIN_DBL_MAX;
fromRowsUpper[kRow] = 0.0;
which[kRow] = iRow;
kRow++;
newObjective[kRow] = -rowLower[iRow];
fromRowsLower[kRow] = 0.0;
fromRowsUpper[kRow] = COIN_DBL_MAX;
which[kRow] = iRow;
kRow++;
}
}
}
if (numberExtraRows) {
CoinPackedMatrix newCopy;
newCopy.submatrixOfWithDuplicates(rowCopy, kRow, which);
rowCopy = newCopy;
}
ClpSimplex modelDual;
modelDual.loadProblem(rowCopy, fromRowsLower, fromRowsUpper, newObjective,
fromColumnsLower, fromColumnsUpper);
modelDual.setObjectiveOffset(objOffset);
delete [] fromRowsLower;
delete [] fromRowsUpper;
delete [] fromColumnsLower;
delete [] fromColumnsUpper;
delete [] newObjective;
delete [] which;
delete [] rowLower;
delete [] rowUpper;
modelDual.writeMps("dual.mps");
return 0;
}