void
OsiVolSolverInterface::initFromRlbRub(const int rownum,
const double* rowlb,
const double* rowub)
{
if (maxNumrows_ > 0) {
rowRimAllocator_();
if (rowub) {
CoinDisjointCopyN(rowub, rownum, rowupper_);
} else {
CoinFillN(rowupper_, rownum, OsiVolInfinity);
}
if (rowlb) {
CoinDisjointCopyN(rowlb, rownum, rowlower_);
} else {
CoinFillN(rowlower_, rownum, -OsiVolInfinity);
}
// Set the initial dual solution
CoinFillN(rowprice_, rownum, 0.0);
convertBoundsToSenses_();
}
}
void
OsiVolSolverInterface::addRows(const int numrows,
const CoinPackedVectorBase * const * rows,
const double* rowlb, const double* rowub)
{
if (numrows > 0) {
const int rownum = getNumRows();
rowRimResize_(rownum + numrows);
CoinDisjointCopyN(rowlb, numrows, rowlower_ + rownum);
CoinDisjointCopyN(rowub, numrows, rowupper_ + rownum);
for (int i = rownum + numrows - 1; i >= rownum; --i) {
convertBoundToSense(rowlower_[i], rowupper_[i],
rowsense_[i], rhs_[i], rowrange_[i]);
}
CoinFillN(rowprice_ + rownum, numrows, 0.0);
CoinFillN(lhs_ + rownum, numrows, 0.0);
updateRowMatrix_();
rowMatrix_.appendRows(numrows, rows);
colMatrixCurrent_ = false;
}
}
void
CoinPackedVector::gutsOfSetVector(int size,
const int * inds, const double * elems,
bool testForDuplicateIndex,
const char * method)
{
if ( size != 0 ) {
reserve(size);
nElements_ = size;
CoinDisjointCopyN(inds, size, indices_);
CoinDisjointCopyN(elems, size, elements_);
CoinIotaN(origIndices_, size, 0);
}
if (testForDuplicateIndex) {
try {
CoinPackedVectorBase::setTestForDuplicateIndex(testForDuplicateIndex);
}
catch (CoinError e) {
throw CoinError("duplicate index", method, "CoinPackedVector");
}
} else {
setTestsOff();
}
}
bool
OsiTestSolverInterface::setWarmStart(const CoinWarmStart* warmstart)
{
const CoinWarmStartDual* ws =
dynamic_cast<const CoinWarmStartDual*>(warmstart);
if (! ws)
return false;
const int ws_size = ws->size();
if (ws_size != getNumRows() && ws_size != 0) {
throw CoinError("wrong dual warmstart size", "setWarmStart",
"OsiTestSolverInterface");
}
CoinDisjointCopyN(ws->dual(), ws_size, rowprice_);
return true;
}
void
CoinPackedVector::setFull(int size, const double * elems,
bool testForDuplicateIndex)
{
// Clear out any values presently stored
clear();
// Allocate storage
if ( size!=0 ) {
reserve(size);
nElements_ = size;
CoinIotaN(origIndices_, size, 0);
CoinIotaN(indices_, size, 0);
CoinDisjointCopyN(elems, size, elements_);
}
// Full array can not have duplicates
CoinPackedVectorBase::setTestForDuplicateIndexWhenTrue(testForDuplicateIndex);
}
void
CoinPackedVector::gutsOfSetConstant(int size,
const int * inds, double value,
bool testForDuplicateIndex,
const char * method)
{
if ( size != 0 ) {
reserve(size);
nElements_ = size;
CoinDisjointCopyN(inds, size, indices_);
CoinFillN(elements_, size, value);
CoinIotaN(origIndices_, size, 0);
}
try {
CoinPackedVectorBase::setTestForDuplicateIndex(testForDuplicateIndex);
}
catch (CoinError& e) {
throw CoinError("duplicate index", method, "CoinPackedVector");
}
}
void
OsiTestSolverInterface::setRowPrice(const double *rowprice)
{
CoinDisjointCopyN(rowprice, getNumRows(), rowprice_);
compute_rc_(rowprice_, rc_);
}
void
OsiTestSolverInterface::resolve()
{
int i;
checkData_();
// Only one of these can do any work
updateRowMatrix_();
updateColMatrix_();
const int dsize = getNumRows();
const int psize = getNumCols();
// Negate the objective coefficients if necessary
if (objsense_ < 0) {
std::transform(objcoeffs_, objcoeffs_+psize, objcoeffs_,
std::negate<double>());
}
// Set the lb/ub on the duals
volprob_.dual_lb.allocate(dsize);
volprob_.dual_ub.allocate(dsize);
double * dlb = volprob_.dual_lb.v;
double * dub = volprob_.dual_ub.v;
for (i = 0; i < dsize; ++i) {
dlb[i] = rowupper_[i] < getInfinity() ? -1.0e31 : 0.0;
dub[i] = rowlower_[i] > -getInfinity() ? 1.0e31 : 0.0;
}
volprob_.dsize = dsize;
volprob_.psize = psize;
// Set the dual starting point
VOL_dvector& dsol = volprob_.dsol;
dsol.allocate(dsize);
std::transform(rowprice_, rowprice_+dsize, dsol.v,
std::bind2nd(std::multiplies<double>(), objsense_));
// adjust the dual vector (if necessary) to be sure it's feasible
double * dv = dsol.v;
for (i = 0; i < dsize; ++i) {
if (dv[i] < dlb[i]) {
dv[i] = dlb[i];
} else if (dv[i] > dub[i]) {
dv[i] = dub[i];
}
}
// If requested, check whether the matrix contains anything but 0/1/-1
#if 0
isZeroOneMinusOne_ = false;
#else
isZeroOneMinusOne_ = test_zero_one_minusone_(colMatrix_);
if (isZeroOneMinusOne_) {
colMatrixOneMinusOne_ = new OsiVolMatrixOneMinusOne_(colMatrix_);
rowMatrixOneMinusOne_ = new OsiVolMatrixOneMinusOne_(rowMatrix_);
}
#endif
volprob_.solve(*this, true);
// extract the solution
// the lower bound on the objective value
lagrangeanCost_ = objsense_ * volprob_.value;
// the primal solution
CoinDisjointCopyN(volprob_.psol.v, psize, colsol_);
// Reset the objective coefficients if necessary
if (objsense_ < 0) {
std::transform(objcoeffs_, objcoeffs_ + psize, objcoeffs_,
std::negate<double>());
// also, multiply the dual solution by -1
std::transform(volprob_.dsol.v, volprob_.dsol.v+dsize, rowprice_,
std::negate<double>());
} else {
// now we just have to copy the dual
CoinDisjointCopyN(volprob_.dsol.v, dsize, rowprice_);
}
// Compute the reduced costs
compute_rc_(rowprice_, rc_);
// Compute the left hand side (row activity levels)
if (isZeroOneMinusOne_) {
colMatrixOneMinusOne_->timesMajor(colsol_, lhs_);
} else {
colMatrix_.times(colsol_, lhs_);
}
if (isZeroOneMinusOne_) {
delete colMatrixOneMinusOne_;
colMatrixOneMinusOne_ = NULL;
delete rowMatrixOneMinusOne_;
rowMatrixOneMinusOne_ = NULL;
}
}
OsiTestSolverInterface&
OsiTestSolverInterface::operator=(const OsiTestSolverInterface& rhs)
{
if (&rhs == this)
return *this;
OsiSolverInterface::operator=(rhs);
gutsOfDestructor_();
rowMatrixCurrent_ = rhs.rowMatrixCurrent_;
if (rowMatrixCurrent_)
rowMatrix_ = rhs.rowMatrix_;
colMatrixCurrent_ = rhs.colMatrixCurrent_;
if (colMatrixCurrent_)
colMatrix_ = rhs.colMatrix_;
if (rhs.maxNumrows_) {
maxNumrows_ = rhs.maxNumrows_;
rowRimAllocator_();
const int rownum = getNumRows();
CoinDisjointCopyN(rhs.rowupper_, rownum, rowupper_);
CoinDisjointCopyN(rhs.rowlower_, rownum, rowlower_);
CoinDisjointCopyN(rhs.rowsense_, rownum, rowsense_);
CoinDisjointCopyN(rhs.rhs_, rownum, rhs_);
CoinDisjointCopyN(rhs.rowrange_, rownum, rowrange_);
CoinDisjointCopyN(rhs.rowprice_, rownum, rowprice_);
CoinDisjointCopyN(rhs.lhs_, rownum, lhs_);
}
if (rhs.maxNumcols_) {
maxNumcols_ = rhs.maxNumcols_;
colRimAllocator_();
const int colnum = getNumCols();
CoinDisjointCopyN(rhs.colupper_, colnum, colupper_);
CoinDisjointCopyN(rhs.collower_, colnum, collower_);
CoinDisjointCopyN(rhs.continuous_, colnum, continuous_);
CoinDisjointCopyN(rhs.objcoeffs_, colnum, objcoeffs_);
CoinDisjointCopyN(rhs.colsol_, colnum, colsol_);
CoinDisjointCopyN(rhs.rc_, colnum, rc_);
}
volprob_.parm.granularity = 0.0;
return *this;
}
CoinTreeSiblings(const int n, CoinTreeNode** nodes) :
current_(0), numSiblings_(n), siblings_(new CoinTreeNode*[n])
{
CoinDisjointCopyN(nodes, n, siblings_);
}
/** This helper function copies an array to another location. The two arrays
must not overlap (otherwise an exception is thrown). For speed 8 entries
are copied at a time. The source array is given by its first and "after
last" entry; the target array is given by its first entry. */
template <class T> inline void
CoinDisjointCopy(register const T* first, register const T* last,
register T* to)
{
CoinDisjointCopyN(first, static_cast<int>(last - first), to);
}
//-----------------------------------------------------------------------------
// Generate Lift-and-Project cuts
//-------------------------------------------------------------------
void CglLiftAndProject::generateCuts(const OsiSolverInterface& si, OsiCuts& cs,
const CglTreeInfo /*info*/)
{
// Assumes the mixed 0-1 problem
//
// min {cx: <Atilde,x> >= btilde}
//
// is in canonical form with all bounds,
// including x_t>=0, -x_t>=-1 for x_t binary,
// explicitly stated in the constraint matrix.
// See ~/COIN/Examples/Cgl2/cgl2.cpp
// for a general purpose "convert" function.
// Reference [BCC]: Balas, Ceria, and Corneujols,
// "A lift-and-project cutting plane algorithm
// for mixed 0-1 program", Math Prog 58, (1993)
// 295-324.
// This implementation uses Normalization 1.
// Given canonical problem and
// the lp-relaxation solution, x,
// the LAP cut generator attempts to construct
// a cut for every x_j such that 0<x_j<1
// [BCC:307]
// x_j is the strictly fractional binary variable
// the cut is generated from
int j = 0;
// Get basic problem information
// let Atilde be an m by n matrix
const int m = si.getNumRows();
const int n = si.getNumCols();
const double * x = si.getColSolution();
// Remember - Atildes may have gaps..
const CoinPackedMatrix * Atilde = si.getMatrixByRow();
const double * AtildeElements = Atilde->getElements();
const int * AtildeIndices = Atilde->getIndices();
const CoinBigIndex * AtildeStarts = Atilde->getVectorStarts();
const int * AtildeLengths = Atilde->getVectorLengths();
const int AtildeFullSize = AtildeStarts[m];
const double * btilde = si.getRowLower();
// Set up memory for system (10) [BCC:307]
// (the problem over the norm intersected
// with the polar cone)
//
// min <<x^T,Atilde^T>,u> + x_ju_0
// s.t.
// <B,w> = (0,...,0,beta_,beta)^T
// w is nonneg for all but the
// last two entries, which are free.
// where
// w = (u,v,v_0,u_0)in BCC notation
// u and v are m-vectors; u,v >=0
// v_0 and u_0 are free-scalars, and
//
// B = Atilde^T -Atilde^T -e_j e_j
// btilde^T e_0^T 0 0
// e_0^T btilde^T 1 0
// ^T indicates Transpose
// e_0 is a (AtildeNCols x 1) vector of all zeros
// e_j is e_0 with a 1 in the jth position
// Storing B in column order. B is a (n+2 x 2m+2) matrix
// But need to allow for possible gaps in Atilde.
// At each iteration, only need to change 2 cols and objfunc
// Sane design of OsiSolverInterface does not permit mucking
// with matrix.
// Because we must delete and add cols to alter matrix,
// and we can only add columns on the end of the matrix
// put the v_0 and u_0 columns on the end.
// rather than as described in [BCC]
// Initially allocating B with space for v_0 and u_O cols
// but not populating, for efficiency.
// B without u_0 and v_0 is a (n+2 x 2m) size matrix.
int twoM = 2*m;
int BNumRows = n+2;
int BNumCols = twoM+2;
int BFullSize = 2*AtildeFullSize+twoM+3;
double * BElements = new double[BFullSize];
int * BIndices = new int[BFullSize];
CoinBigIndex * BStarts = new CoinBigIndex [BNumCols+1];
int * BLengths = new int[BNumCols];
int i, ij, k=0;
int nPlus1=n+1;
int offset = AtildeStarts[m]+m;
for (i=0; i<m; i++){
for (ij=AtildeStarts[i];ij<AtildeStarts[i]+AtildeLengths[i];ij++){
BElements[k]=AtildeElements[ij];
BElements[k+offset]=-AtildeElements[ij];
BIndices[k]= AtildeIndices[ij];
BIndices[k+offset]= AtildeIndices[ij];
k++;
}
BElements[k]=btilde[i];
BElements[k+offset]=btilde[i];
BIndices[k]=n;
BIndices[k+offset]=nPlus1;
BStarts[i]= AtildeStarts[i]+i;
BStarts[i+m]=offset+BStarts[i];// = AtildeStarts[m]+m+AtildeStarts[i]+i
BLengths[i]= AtildeLengths[i]+1;
BLengths[i+m]= AtildeLengths[i]+1;
k++;
}
BStarts[twoM]=BStarts[twoM-1]+BLengths[twoM-1];
// Cols that will be deleted each iteration
int BNumColsLessOne=BNumCols-1;
int BNumColsLessTwo=BNumCols-2;
const int delCols[2] = {BNumColsLessOne, BNumColsLessTwo};
// Set lower bound on u and v
// u_0, v_0 will be reset as free
const double solverINFINITY = si.getInfinity();
double * BColLowers = new double[BNumCols];
double * BColUppers = new double[BNumCols];
CoinFillN(BColLowers,BNumCols,0.0);
CoinFillN(BColUppers,BNumCols,solverINFINITY);
// Set row lowers and uppers.
// The rhs is zero, for but the last two rows.
// For these the rhs is beta_
double * BRowLowers = new double[BNumRows];
double * BRowUppers = new double[BNumRows];
CoinFillN(BRowLowers,BNumRows,0.0);
CoinFillN(BRowUppers,BNumRows,0.0);
BRowLowers[BNumRows-2]=beta_;
BRowUppers[BNumRows-2]=beta_;
BRowLowers[BNumRows-1]=beta_;
BRowUppers[BNumRows-1]=beta_;
// Calculate base objective <<x^T,Atilde^T>,u>
// Note: at each iteration coefficient u_0
// changes to <x^T,e_j>
// w=(u,v,beta,v_0,u_0) size 2m+3
// So, BOjective[2m+2]=x[j]
double * BObjective= new double[BNumCols];
double * Atildex = new double[m];
CoinFillN(BObjective,BNumCols,0.0);
Atilde->times(x,Atildex); // Atildex is size m, x is size n
CoinDisjointCopyN(Atildex,m,BObjective);
// Number of cols and size of Elements vector
// in B without the v_0 and u_0 cols
int BFullSizeLessThree = BFullSize-3;
// Load B matrix into a column orders CoinPackedMatrix
CoinPackedMatrix * BMatrix = new CoinPackedMatrix(true, BNumRows,
BNumColsLessTwo,
BFullSizeLessThree,
BElements,BIndices,
BStarts,BLengths);
// Assign problem into a solver interface
// Note: coneSi will cleanup the memory itself
OsiSolverInterface * coneSi = si.clone(false);
coneSi->assignProblem (BMatrix, BColLowers, BColUppers,
BObjective,
BRowLowers, BRowUppers);
// Problem sense should default to "min" by default,
// but just to be virtuous...
coneSi->setObjSense(1.0);
// The plot outline from here on down:
// coneSi has been assigned B without the u_0 and v_0 columns
// Calculate base objective <<x^T,Atilde^T>,u>
// bool haveWarmStart = false;
// For (j=0; j<n, j++)
// if (!isBinary(x_j) || x_j<=0 || x_j>=1) continue;
// // IMPROVEME: if(haveWarmStart) check if j attractive
// add {-e_j,0,-1} matrix column for v_0
// add {e_j,0,0} matrix column for u_0
// objective coefficient for u_0 is x_j
// if (haveWarmStart)
// set warmstart info
// solve min{objw:Bw=0; w>=0,except v_0, u_0 free}
// if (bounded)
// get warmstart info
// haveWarmStart=true;
// ustar = optimal u solution
// ustar_0 = optimal u_0 solution
// alpha^T= <ustar^T,Atilde> -ustar_0e_j^T
// (double check <alpha^T,x> >= beta_ should be violated)
// add <alpha^T,x> >= beta_ to cutset
// endif
// delete column for u_0 // this deletes all column info.
// delete column for v_0
// endFor
// clean up memory
// return 0;
int * nVectorIndices = new int[n];
CoinIotaN(nVectorIndices, n, 0);
bool haveWarmStart = false;
bool equalObj1, equalObj2;
CoinRelFltEq eq;
double v_0Elements[2] = {-1,1};
double u_0Elements[1] = {1};
CoinWarmStart * warmStart = 0;
double * ustar = new double[m];
CoinFillN(ustar, m, 0.0);
double* alpha = new double[n];
CoinFillN(alpha, n, 0.0);
for (j=0;j<n;j++){
if (!si.isBinary(j)) continue; // Better to ask coneSi? No!
// coneSi has no binInfo.
equalObj1=eq(x[j],0);
equalObj2=eq(x[j],1);
if (equalObj1 || equalObj2) continue;
// IMPROVEME: if (haveWarmStart) check if j attractive;
// AskLL:wanted to declare u_0 and v_0 packedVec outside loop
// and setIndices, but didn't see a method to do that(?)
// (Could "insert". Seems inefficient)
int v_0Indices[2]={j,nPlus1};
int u_0Indices[1]={j};
//
CoinPackedVector v_0(2,v_0Indices,v_0Elements,false);
CoinPackedVector u_0(1,u_0Indices,u_0Elements,false);
#if CGL_DEBUG
const CoinPackedMatrix *see1 = coneSi->getMatrixByRow();
#endif
coneSi->addCol(v_0,-solverINFINITY,solverINFINITY,0);
coneSi->addCol(u_0,-solverINFINITY,solverINFINITY,x[j]);
if(haveWarmStart) {
coneSi->setWarmStart(warmStart);
coneSi->resolve();
}
else {
#if CGL_DEBUG
const CoinPackedMatrix *see2 = coneSi->getMatrixByRow();
#endif
coneSi->initialSolve();
}
if(coneSi->isProvenOptimal()){
warmStart = coneSi->getWarmStart();
haveWarmStart=true;
const double * wstar = coneSi->getColSolution();
CoinDisjointCopyN(wstar, m, ustar);
Atilde->transposeTimes(ustar,alpha);
alpha[j]+=wstar[BNumCols-1];
#if debug
int p;
double sum;
for(p=0;p<n;p++)sum+=alpha[p]*x[p];
if (sum<=beta_){
throw CoinError("Cut not violated",
"cutGeneration",
"CglLiftAndProject");
}
#endif
// add <alpha^T,x> >= beta_ to cutset
OsiRowCut rc;
rc.setRow(n,nVectorIndices,alpha);
rc.setLb(beta_);
rc.setUb(solverINFINITY);
cs.insert(rc);
}
// delete col for u_o and v_0
coneSi->deleteCols(2,delCols);
// clean up memory
}
// clean up
delete [] alpha;
delete [] ustar;
delete [] nVectorIndices;
// BMatrix, BColLowers,BColUppers, BObjective, BRowLowers, BRowUppers
// are all freed by OsiSolverInterface destructor (?)
delete [] BLengths;
delete [] BStarts;
delete [] BIndices;
delete [] BElements;
}
//-------------------------------------------------------------------
// Determine row types. Find the VUBS and VLBS.
//-------------------------------------------------------------------
void
CglFlowCover::flowPreprocess(const OsiSolverInterface& si) const
{
CoinPackedMatrix matrixByRow(*si.getMatrixByRow());
int numRows = si.getNumRows();
int numCols = si.getNumCols();
const char* sense = si.getRowSense();
const double* RHS = si.getRightHandSide();
const double* coefByRow = matrixByRow.getElements();
const int* colInds = matrixByRow.getIndices();
const int* rowStarts = matrixByRow.getVectorStarts();
const int* rowLengths = matrixByRow.getVectorLengths();
int iRow = -1;
int iCol = -1;
numCols_ = numCols; // Record col and row numbers for copy constructor
numRows_ = numRows;
if (rowTypes_ != 0) {
delete [] rowTypes_; rowTypes_ = 0;
}
rowTypes_ = new CglFlowRowType [numRows];// Destructor will free memory
// Get integer types
const char * columnType = si.getColType (true);
// Summarize the row type infomation.
int numUNDEFINED = 0;
int numVARUB = 0;
int numVARLB = 0;
int numVAREQ = 0;
int numMIXUB = 0;
int numMIXEQ = 0;
int numNOBINUB = 0;
int numNOBINEQ = 0;
int numSUMVARUB = 0;
int numSUMVAREQ = 0;
int numUNINTERSTED = 0;
int* ind = new int [numCols];
double* coef = new double [numCols];
for (iRow = 0; iRow < numRows; ++iRow) {
int rowLen = rowLengths[iRow];
char sen = sense[iRow];
double rhs = RHS[iRow];
CoinDisjointCopyN(colInds + rowStarts[iRow], rowLen, ind);
CoinDisjointCopyN(coefByRow + rowStarts[iRow], rowLen, coef);
CglFlowRowType rowType = determineOneRowType(si, rowLen, ind, coef,
sen, rhs);
rowTypes_[iRow] = rowType;
switch(rowType) {
case CGLFLOW_ROW_UNDEFINED:
++numUNDEFINED;
break;
case CGLFLOW_ROW_VARUB:
++numVARUB;
break;
case CGLFLOW_ROW_VARLB:
++numVARLB;
break;
case CGLFLOW_ROW_VAREQ:
++numVAREQ;
break;
case CGLFLOW_ROW_MIXUB:
++numMIXUB;
break;
case CGLFLOW_ROW_MIXEQ:
++numMIXEQ;
break;
case CGLFLOW_ROW_NOBINUB:
++numNOBINUB;
break;
case CGLFLOW_ROW_NOBINEQ:
++numNOBINEQ;
break;
case CGLFLOW_ROW_SUMVARUB:
++numSUMVARUB;
break;
case CGLFLOW_ROW_SUMVAREQ:
++numSUMVAREQ;
break;
case CGLFLOW_ROW_UNINTERSTED:
++numUNINTERSTED;
break;
default:
throw CoinError("Unknown row type", "flowPreprocess",
"CglFlowCover");
}
}
delete [] ind; ind = NULL;
delete [] coef; coef = NULL;
if(CGLFLOW_DEBUG) {
std::cout << "The num of rows = " << numRows << std::endl;
std::cout << "Summary of Row Type" << std::endl;
std::cout << "numUNDEFINED = " << numUNDEFINED << std::endl;
std::cout << "numVARUB = " << numVARUB << std::endl;
std::cout << "numVARLB = " << numVARLB << std::endl;
std::cout << "numVAREQ = " << numVAREQ << std::endl;
std::cout << "numMIXUB = " << numMIXUB << std::endl;
std::cout << "numMIXEQ = " << numMIXEQ << std::endl;
std::cout << "numNOBINUB = " << numNOBINUB << std::endl;
std::cout << "numNOBINEQ = " << numNOBINEQ << std::endl;
std::cout << "numSUMVARUB = " << numSUMVARUB << std::endl;
std::cout << "numSUMVAREQ = " << numSUMVAREQ << std::endl;
std::cout << "numUNINTERSTED = " << numUNINTERSTED << std::endl;
}
//---------------------------------------------------------------------------
// Setup vubs_ and vlbs_
if (vubs_ != 0) { delete [] vubs_; vubs_ = 0; }
vubs_ = new CglFlowVUB [numCols]; // Destructor will free memory
if (vlbs_ != 0) { delete [] vlbs_; vlbs_ = 0; }
vlbs_ = new CglFlowVLB [numCols]; // Destructor will free memory
for (iCol = 0; iCol < numCols; ++iCol) { // Initilized in constructor
vubs_[iCol].setVar(UNDEFINED_); // but, need redo since may call
vlbs_[iCol].setVar(UNDEFINED_); // preprocess(...) more than once
}
for (iRow = 0; iRow < numRows; ++iRow) {
CglFlowRowType rowType2 = rowTypes_[iRow];
if ( (rowType2 == CGLFLOW_ROW_VARUB) ||
(rowType2 == CGLFLOW_ROW_VARLB) ||
(rowType2 == CGLFLOW_ROW_VAREQ) ) {
int startPos = rowStarts[iRow];
int index0 = colInds[startPos];
int index1 = colInds[startPos + 1];
double coef0 = coefByRow[startPos];
double coef1 = coefByRow[startPos + 1];
int xInd, yInd; // x is binary
double xCoef, yCoef;
if ( columnType[index0]==1 ) {
xInd = index0; yInd = index1;
xCoef = coef0; yCoef = coef1;
}
else {
xInd = index1; yInd = index0;
xCoef = coef1; yCoef = coef0;
}
switch (rowType2) {
case CGLFLOW_ROW_VARUB: // Inequality: y <= ? * x
vubs_[yInd].setVar(xInd);
vubs_[yInd].setVal(-xCoef / yCoef);
break;
case CGLFLOW_ROW_VARLB: // Inequality: y >= ? * x
vlbs_[yInd].setVar(xInd);
vlbs_[yInd].setVal(-xCoef / yCoef);
break;
case CGLFLOW_ROW_VAREQ: // Inequality: y >= AND <= ? * x
vubs_[yInd].setVar(xInd);
vubs_[yInd].setVal(-xCoef / yCoef);
vlbs_[yInd].setVar(xInd);
vlbs_[yInd].setVal(-xCoef / yCoef);
break;
default:
throw CoinError("Unknown row type: impossible",
"flowPreprocess", "CglFlowCover");
}
}
}
if(CGLFLOW_DEBUG) {
printVubs(std::cout);
}
}
//#############################################################################
OsiSolverInterface *
MibSBilevel::setUpModel(OsiSolverInterface * oSolver, bool newOsi,
const double *lpSol)
{
/** Create lower-level model with fixed upper-level vars **/
int probType =
model_->MibSPar_->entry(MibSParams::bilevelProblemType);
bool warmStartLL =
model_->MibSPar_->entry(MibSParams::warmStartLL);
bool doDualFixing =
model_->MibSPar_->entry(MibSParams::doDualFixing);
std::string feasCheckSolver =
model_->MibSPar_->entry(MibSParams::feasCheckSolver);
OsiSolverInterface * nSolver;
double etol(model_->etol_);
int i(0), j(0), index1(0), index2(0);
int uCols(model_->getUpperDim());
int lRows(model_->getLowerRowNum());
int lCols(model_->getLowerDim());
int * uColIndices = model_->getUpperColInd();
int * lColIndices = model_->getLowerColInd();
int * lRowIndices = model_->getLowerRowInd();
double objSense(model_->getLowerObjSense());
double * lObjCoeffs = model_->getLowerObjCoeffs();
const CoinPackedMatrix * matrix = oSolver->getMatrixByRow();
double coeff(0.0);
if (!lpSol){
lpSol = oSolver->getColSolution();
}
const double * origRowLb = model_->getOrigRowLb();
const double * origRowUb = model_->getOrigRowUb();
const double * origColLb = model_->getOrigColLb();
const double * origColUb = model_->getOrigColUb();
double * rowUb = new double[lRows];
double * rowLb = new double[lRows];
double * colUb = new double[lCols];
double * colLb = new double[lCols];
//CoinZeroN(rowUb, lRows);
//CoinZeroN(rowLb, lRows);
//CoinZeroN(colUb, lCols);
//CoinZeroN(colLb, lCols);
/** Set the row bounds **/
for(i = 0; i < lRows; i++){
rowLb[i] = origRowLb[lRowIndices[i]];
rowUb[i] = origRowUb[lRowIndices[i]];
}
for(i = 0; i < lCols; i++){
colLb[i] = origColLb[lColIndices[i]];
colUb[i] = origColUb[lColIndices[i]];
}
if (newOsi){
if (feasCheckSolver == "Cbc"){
nSolver = new OsiCbcSolverInterface();
}else if (feasCheckSolver == "SYMPHONY"){
nSolver = new OsiSymSolverInterface();
}else if (feasCheckSolver == "CPLEX"){
#ifdef USE_CPLEX
nSolver = new OsiCpxSolverInterface();
#else
throw CoinError("CPLEX chosen as solver, but it has not been enabled",
"setUpModel", "MibsBilevel");
#endif
}else{
throw CoinError("Unknown solver chosen",
"setUpModel", "MibsBilevel");
}
int * integerVars = new int[lCols];
double * objCoeffs = new double[lCols];
CoinFillN(integerVars, lCols, 0);
//CoinZeroN(objCoeffs, lCols);
int intCnt(0);
/** Fill in array of lower-level integer variables **/
for(i = 0; i < lCols; i++){
index1 = lColIndices[i];
if(oSolver->isInteger(index1)){
integerVars[intCnt] = i;
intCnt++;
}
}
CoinDisjointCopyN(lObjCoeffs, lCols, objCoeffs);
CoinPackedMatrix * newMat = new CoinPackedMatrix(false, 0, 0);
newMat->setDimensions(0, lCols);
double tmp(0.0);
/*
for(i = 0; i < lRows; i++){
CoinPackedVector row;
index1 = lRowIndices[i];
start = matStarts[index1];
end = start + matrix->getVectorSize(index1);
for(j = start; j < end; j++){
index2 = matIndices[j];
//tmp = findIndex(index, lCols, lColIndices);
tmp = binarySearch(0, lCols - 1, index2, lColIndices);
if(tmp > -1)
row.insert(tmp, matElements[j]);
}
newMat->appendRow(row);
}
*/
for(i = 0; i < lRows; i++){
CoinPackedVector row;
index1 = lRowIndices[i];
for(j = 0; j < lCols; j++){
index2 = lColIndices[j];
tmp = matrix->getCoefficient(index1, index2);
row.insert(j, tmp);
}
newMat->appendRow(row);
}
/*
nSolver->assignProblem(newMat, colLb, colUb,
objCoeffs, rowLb, rowUb);
*/
nSolver->loadProblem(*newMat, colLb, colUb,
objCoeffs, rowLb, rowUb);
for(i = 0; i < intCnt; i++){
nSolver->setInteger(integerVars[i]);
}
//nSolver->setInteger(integerVars, intCnt);
nSolver->setObjSense(objSense); //1 min; -1 max
nSolver->setHintParam(OsiDoReducePrint, true, OsiHintDo);
#if 0
if(0){
dynamic_cast<OsiCbcSolverInterface *>
(nSolver)->getModelPtr()->messageHandler()->setLogLevel(0);
}
else{
dynamic_cast<OsiSymSolverInterface *>
(nSolver)->setSymParam("prep_level", -1);
dynamic_cast<OsiSymSolverInterface *>
(nSolver)->setSymParam("verbosity", -2);
dynamic_cast<OsiSymSolverInterface *>
(nSolver)->setSymParam("max_active_nodes", 1);
}
#endif
delete [] integerVars;
}else{
nSolver = solver_;
}
#define SYM_VERSION_IS_WS strcmp(SYMPHONY_VERSION, "WS")
#if SYMPHONY_VERSION_IS_WS
if (feasCheckSolver == "SYMPHONY" && probType == 1 && warmStartLL &&
!newOsi && doDualFixing){ //Interdiction
/** Get upper bound from best known (feasible) lower level solution and try
to fix additional variables by sensitivity analysis **/
std::vector<std::pair<AlpsKnowledge*, double> > solutionPool;
model_->getKnowledgeBroker()->
getAllKnowledges(AlpsKnowledgeTypeSolution, solutionPool);
const double * sol;
double objval, Ub(objSense*nSolver->getInfinity());
BlisSolution* blisSol;
std::vector<std::pair<AlpsKnowledge*, double> >::const_iterator si;
for (si = solutionPool.begin(); si != solutionPool.end(); ++si){
blisSol = dynamic_cast<BlisSolution*>(si->first);
sol = blisSol->getValues();
for (i = 0; i < uCols; i++){
if (lpSol[uColIndices[i]] > 1 - etol &&
sol[lColIndices[i]] > 1-etol){
break;
}
}
if (i == uCols && -objSense*blisSol->getQuality() < Ub){
Ub = -objSense*blisSol->getQuality();
}
}
/** Figure out which variables get fixed by the upper level solution **/
int *newUbInd = new int[uCols];
int *newLbInd = new int[uCols];
double *newUbVal = new double[uCols];
double *newLbVal = new double[uCols];
double newLb;
for (i = 0; i < uCols; i++){
newUbInd[i] = uColIndices[i];
newLbInd[i] = uColIndices[i];
newLbVal[i] = 0;
if (lpSol[uColIndices[i]] > 1 - etol){
newUbVal[i] = 0;
}else{
newUbVal[i] = 1;
}
}
/** If we found an upper bound, then do the dual fixing **/
if (Ub < objSense*nSolver->getInfinity()){
sym_environment *env =
dynamic_cast<OsiSymSolverInterface *>(nSolver)->getSymphonyEnvironment();
for (i = 0; i < uCols; i++){
if (newUbVal[i] == 1){
// Try fixing it to zero
newUbVal[i] = 0;
sym_get_lb_for_new_rhs(env, 0, NULL, NULL, uCols, newLbInd,
newLbVal, uCols, newUbInd, newUbVal,
&newLb);
if (objSense*newLb > Ub + etol){
//Victory! This variable can be fixed to 1 permanently
newLbVal[i] = 1;
}
//Set upper bound back to 1
newUbVal[i] = 1;
if (newLbVal[i] == 0){
// Try fixing it to one
newLbVal[i] = 1;
sym_get_lb_for_new_rhs(env, 0, NULL, NULL, uCols, newLbInd,
newLbVal, uCols, newUbInd, newUbVal,
&newLb);
if (objSense*newLb > Ub + etol){
//Victory! This variable can be fixed to 0 permanently
newUbVal[i] = 0;
}
newLbVal[i] = 0;
}
}
}
}
/** Now set the row bounds to account for fixings **/
/** This is probably very frgaile. Assuming interdiction
rows come last. It would be better to set variable
bounds directly, but this doesn't seem to work right now. **/
int iRowStart = lRows-uCols;
#if 1
for(i = iRowStart; i < lRows; i++){
nSolver->setRowLower(i, newLbVal[i-iRowStart]);
nSolver->setRowUpper(i, newUbVal[i-iRowStart]);
}
#else
for(i = 0; i < uCols; i++){
nSolver->setColLower(i, newLbVal[i]);
nSolver->setColUpper(i, newUbVal[i]);
}
#endif
delete[] newUbInd;
delete[] newLbInd;
delete[] newUbVal;
delete[] newLbVal;
}else{
#endif
//FIXME: NEED TO GET ROW SENSE HERE
/** Get contribution of upper-level columns **/
double * upComp = new double[lRows];
CoinFillN(upComp, lRows, 0.0);
for(i = 0; i < lRows; i++){
index1 = lRowIndices[i];
for(j = 0; j < uCols; j++){
index2 = uColIndices[j];
coeff = matrix->getCoefficient(index1, index2);
if (coeff != 0){
upComp[i] += coeff * lpSol[index2];
}
}
}
/** Correct the row bounds to account for fixed upper-level vars **/
for(i = 0; i < lRows; i++){
nSolver->setRowLower(i, rowLb[i] - upComp[i]);
nSolver->setRowUpper(i, rowUb[i] - upComp[i]);
}
delete [] upComp;
#if SYMPHONY_VERSION_IS_WS
}
#endif
//I don't think this is needed
//if(!getWarmStart())
// setWarmStart(nSolver->getWarmStart());
return nSolver;
}
void
BM_tm::initialize_core(BCP_vec<BCP_var_core*>& vars,
BCP_vec<BCP_cut_core*>& cuts,
BCP_lp_relax*& matrix)
{
char* argv_[3];
char** argv = argv_;
argv[0] = NULL;
argv[1] = strdup(par.entry(BM_par::NL_filename).c_str());
argv[2] = NULL;
/* Get the basic options. */
Bonmin::BonminAmplSetup bonmin;
bonmin.readOptionsFile(par.entry(BM_par::IpoptParamfile).c_str());
bonmin.initialize(argv);
free(argv[1]);
Bonmin::OsiTMINLPInterface& nlp = *bonmin.nonlinearSolver();
#if defined(BM_DISREGARD_SOS)
const Bonmin::TMINLP::SosInfo * sos = nlp.model()->sosConstraints();
if (sos->num > 0) {
printf("There are SOS constraints... disregarding them...\n");
}
#endif
OsiSolverInterface& clp = *bonmin.continuousSolver();
const int numCols = clp.getNumCols();
const int numRows = clp.getNumRows();
const double* clb = clp.getColLower();
const double* cub = clp.getColUpper();
double* obj = new double[numCols];
if (bonmin.getAlgorithm() == Bonmin::B_BB /* pure B&B */) {
std::cout<<"Doing branch and bound"<<std::endl;
CoinFillN(obj, numCols, 0.0);
matrix = NULL;
} else {
std::cout<<"Doing hybrid"<<std::endl;
CoinDisjointCopyN(clp.getObjCoefficients(), numCols, obj);
cuts.reserve(numRows);
const double* rlb = clp.getRowLower();
const double* rub = clp.getRowUpper();
for (int i = 0; i < numRows; ++i) {
cuts.push_back(new BCP_cut_core(rlb[i], rub[i]));
}
matrix = new BCP_lp_relax(true /*column major ordered*/);
matrix->copyOf(*clp.getMatrixByCol(), obj, clb, cub, rlb, rub);
}
vars.reserve(numCols);
for (int i = 0; i < numCols; ++i) {
BCP_var_t type = BCP_ContinuousVar;
if (clp.isBinary(i)) type = BCP_BinaryVar;
if (clp.isInteger(i)) type = BCP_IntegerVar;
vars.push_back(new BCP_var_core(type, obj[i], clb[i], cub[i]));
}
delete[] obj;
/* Initialize pseudocosts */
int nObj = 0;
for (int i = 0; i < numCols; ++i) {
if (nlp.isInteger(i)) {
++nObj;
}
}
#if ! defined(BM_DISREGARD_SOS)
const Bonmin::TMINLP::SosInfo * sos = nlp.model()->sosConstraints();
nObj += sos->num;
#endif
pseudoCosts_.initialize(nObj);
}
