int
main(void)
{
// Create a problem pointer. We use the base class here.
OsiSolverInterface *si;
// When we instantiate the object, we need a specific derived class.
si = new OsiClpSolverInterface;
// Read in an mps file. This one's from the MIPLIB library.
si->readMps("../../Data/Sample/p0033");
// Solve the (relaxation of the) problem
si->initialSolve();
// Check the solution
if ( si->isProvenOptimal() ) {
std::cout << "Found optimal solution!" << std::endl;
std::cout << "Objective value is " << si->getObjValue() << std::endl;
int n = si->getNumCols();
const double *solution;
solution = si->getColSolution();
// We could then print the solution or examine it.
} else {
std::cout << "Didn't find optimal solution." << std::endl;
// Could then check other status functions.
}
return 0;
}
void SmpsIO(const char * const name )
{
SmiScnModel smi;
// read SMPS model from files
// <name>.core, <name>.time, and <name>.stoch
smi.readSmps(name);
// generate OSI solver object
// here we use OsiClp
OsiClpSolverInterface *clp = new OsiClpSolverInterface();
// set solver object for SmiScnModel
smi.setOsiSolverHandle(*clp);
// load solver data
// this step generates the deterministic equivalent
// and returns an OsiSolver object
OsiSolverInterface *osiStoch = smi.loadOsiSolverData();
// set some nice Hints to the OSI solver
osiStoch->setHintParam(OsiDoPresolveInInitial,true);
osiStoch->setHintParam(OsiDoScale,true);
osiStoch->setHintParam(OsiDoCrash,true);
// solve
osiStoch->initialSolve();
// print results
printf("Solved stochastic program %s\n", name);
printf("Number of rows: %d\n",osiStoch->getNumRows());
printf("Number of cols: %d\n",osiStoch->getNumCols());
printf("Optimal value: %g\n",osiStoch->getObjValue());
// print solution to file
string outfilename(name);
const string suffix(".out");
outfilename = outfilename + suffix;
FILE *fp = fopen(outfilename.c_str(),"w");
int numScenarios=smi.getNumScenarios();
for (int i=0 ; i<numScenarios; ++i) {
double *dsoln=NULL;
int numCols=0;
fprintf(fp,"Scenario %d \n",i);
dsoln = smi.getColSolution(i,&numCols);
for (int j=0; j<numCols; j++)
fprintf(fp,"%g \n",dsoln[j]);
free(dsoln);
}
fclose(fp);
}
// Override OsiSolver::solve() because Soplex doesn't have branch & bound
int OsiSpxSolver::solve() {
OsiSolverInterface* si = OsiSolver::getSolver();
if(!OsiSolver::prepareSolve()) {
return UNSAT;
}
timer.reset();
try {
si->initialSolve();
} catch (CoinError err) {
err.print(true);
return UNSAT;
}
time = timer.timeElapsed();
if (si->isProvenOptimal())
return SAT;
else if (si->isProvenPrimalInfeasible())
return UNSAT;
else
return UNKNOWN;
}
void
CglResidualCapacityUnitTest(const OsiSolverInterface *baseSiP,
const std::string mpsDir)
{
// Test default constructor
{
CglResidualCapacity aGenerator;
}
// Test copy & assignment
{
CglResidualCapacity rhs;
{
CglResidualCapacity bGenerator;
CglResidualCapacity cGenerator(bGenerator);
rhs=bGenerator;
}
}
// Test get/set methods
{
CglResidualCapacity getset;
double geps = 10 * getset.getEpsilon();
getset.setEpsilon(geps);
double geps2 = getset.getEpsilon();
assert(geps == geps2);
double gtol = 10 * getset.getTolerance();
getset.setTolerance(gtol);
double gtol2 = getset.getTolerance();
assert(gtol == gtol2);
int gpre = getset.getDoPreproc();
gpre = (gpre + 1) % 3 - 1;
getset.setDoPreproc(gpre);
int gpre2 = getset.getDoPreproc();
assert(gpre == gpre2);
}
// Test generateCuts
{
CglResidualCapacity gct;
OsiSolverInterface *siP = baseSiP->clone();
std::string fn = mpsDir+"capPlan1";
std::string fn2 = mpsDir+"capPlan1.mps";
FILE *in_f = fopen(fn2.c_str(), "r");
if(in_f == NULL) {
std::cout<<"Can not open file "<<fn2<<std::endl<<"Skip test of CglResidualCapacity::generateCuts()"<<std::endl;
}
else {
fclose(in_f);
siP->readMps(fn.c_str(),"mps");
siP->initialSolve();
double lpRelax = siP->getObjValue();
OsiCuts cs;
gct.setDoPreproc(1); // Needed for DyLP
gct.generateCuts(*siP, cs);
int nRowCuts = cs.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" Residual Capacity cuts"<<std::endl;
assert(cs.sizeRowCuts() > 0);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cs);
siP->resolve();
double lpRelaxAfter= siP->getObjValue();
std::cout<<"Initial LP value: "<<lpRelax<<std::endl;
std::cout<<"LP value with cuts: "<<lpRelaxAfter<<std::endl;
assert( lpRelax < lpRelaxAfter );
assert(lpRelaxAfter < 964);
}
delete siP;
}
}
void
CglMixedIntegerRoundingUnitTest(const OsiSolverInterface *baseSiP,
const std::string mpsDir)
{
// Test default constructor
{
CglMixedIntegerRounding aGenerator;
}
// Test copy & assignment
{
CglMixedIntegerRounding rhs;
{
CglMixedIntegerRounding bGenerator;
CglMixedIntegerRounding cGenerator(bGenerator);
rhs=bGenerator;
}
}
// Test get/set methods
{
CglMixedIntegerRounding getset;
int gagg = 10 * getset.getMAXAGGR_();
getset.setMAXAGGR_(gagg);
int gagg2 = getset.getMAXAGGR_();
assert(gagg == gagg2);
bool gmult = !getset.getMULTIPLY_();
getset.setMULTIPLY_(gmult);
bool gmult2 = getset.getMULTIPLY_();
assert(gmult == gmult2);
int gcrit = getset.getCRITERION_();
gcrit = (gcrit) % 3 + 1;
getset.setCRITERION_(gcrit);
int gcrit2 = getset.getCRITERION_();
assert(gcrit == gcrit2);
int gpre = getset.getDoPreproc();
gpre = (gpre + 1) % 3 - 1;
getset.setDoPreproc(gpre);
int gpre2 = getset.getDoPreproc();
assert(gpre == gpre2);
}
// Test generateCuts
{
CglMixedIntegerRounding gct;
OsiSolverInterface *siP = baseSiP->clone();
std::string fn = mpsDir+"capPlan1";
std::string fn2 = mpsDir+"capPlan1.mps";
FILE *in_f = fopen(fn2.c_str(), "r");
if(in_f == NULL) {
std::cout<<"Can not open file "<<fn2<<std::endl<<"Skip test of CglMixedIntegerRounding::generateCuts()"<<std::endl;
}
else {
fclose(in_f);
siP->readMps(fn.c_str(),"mps");
siP->initialSolve();
double lpRelax = siP->getObjValue();
OsiCuts cs;
gct.generateCuts(*siP, cs);
int nRowCuts = cs.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" MIR cuts"<<std::endl;
assert(cs.sizeRowCuts() > 0);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cs);
siP->resolve();
double lpRelaxAfter= siP->getObjValue();
std::cout<<"Initial LP value: "<<lpRelax<<std::endl;
std::cout<<"LP value with cuts: "<<lpRelaxAfter<<std::endl;
assert( lpRelax < lpRelaxAfter );
assert(lpRelaxAfter < 964);
}
delete siP;
}
}
// mex function usage:
// [x,y,status] = mexosi(n_vars,n_cons,A,x_lb,x_ub,c,Ax_lb,Ax_ub,isMIP,isQP,vartype,Q,options)
// 0 1 2 3 4 5 6 7 8 9 10 11 12
void mexFunction(int nlhs, mxArray *plhs[],int nrhs, const mxArray *prhs[])
{
// Enable printing in MATLAB
int loglevel = 0;
DerivedHandler *mexprinter = new DerivedHandler(); // assumed open
mexprinter->setLogLevel(loglevel);
// check that we have the right number of inputs
if(nrhs < 10) mexErrMsgTxt("At least 10 inputs required in call to mexosi. Bug in osi.m?...");
// check that we have the right number of outputs
if(nlhs < 3) mexErrMsgTxt("At least 3 ouptuts required in call to mexosi. Bug in osi.m?...");
// Get pointers to input values
const int n_vars = (int)*mxGetPr(prhs[0]);
const int n_cons = (int)*mxGetPr(prhs[1]);
const mxArray *A = prhs[2];
const double *x_lb = mxGetPr(prhs[3]);
const double *x_ub = mxGetPr(prhs[4]);
const double *c = mxGetPr(prhs[5]);
const double *Ax_lb = mxGetPr(prhs[6]);
const double *Ax_ub = mxGetPr(prhs[7]);
const bool isMIP = (bool)*(mxLogical*)mxGetData(prhs[8]);
const bool isQP = (bool)*(mxLogical*)mxGetData(prhs[9]);
mxLogical *isinteger = (mxLogical*)mxGetData(prhs[10]);
const mxArray* Q = prhs[11];
// process the options
int returnStatus = 0;
// extract row/col/value data from A
const mwIndex * A_col_starts = mxGetJc(A);
const mwIndex * A_row_index = mxGetIr(A);
const double * A_data = mxGetPr(A);
// figure out the number of non-zeros in A
int nnz = (int)(A_col_starts[n_vars] - A_col_starts[0]); // number of non-zeros
//mexPrintf("nnz = %d, n_vars = %d, n_cons = %d\n",nnz,n_vars,n_cons);
// we need to convert these into other types of indices for Coin to use them
std::vector<CoinBigIndex> A_col_starts_coin(A_col_starts,A_col_starts+n_vars+1);
std::vector<int> A_row_index_coin(A_row_index,A_row_index+nnz);
// declare the solver
OsiSolverInterface* pSolver;
// initialize the solver
if ( isMIP ) {
pSolver = new OsiCbcSolverInterface;
} else {
pSolver = new OsiClpSolverInterface;
}
// OsiCbcSolverInterface is deprecated and CbcModel should be used instead but don't
// know how to get that working with loadProblem.
// OsiCbcSolverInterface solver1;
// CbcModel model(solver1);
// CbcMain0(model);
// OsiSolverInterface * pSolver = model.solver();
if (nrhs>12) { // get stuff out of the options structure if provided
// Finish me
}
// mexPrintf("Setting Log Level to 0.\n");
// load the problem
mexPrintf("Loading the problem.\n");
pSolver->loadProblem( n_vars, n_cons, // problem size
&A_col_starts_coin[0], &A_row_index_coin[0], A_data, // the A matrix
x_lb, x_ub, c, // the objective and bounds
Ax_lb, Ax_ub ); // the constraint bounds
// pSolver->messageHandler()->setLogLevel(0); // This doesn't seem to work
pSolver->setHintParam(OsiDoReducePrint,true,OsiHintTry);
// deal with integer inputs
if ( isMIP ) {
for(int i=0;i<n_vars;i++) {
if (isinteger[i]) pSolver->setInteger(i);
}
}
if (isQP) {
error("QP is not working yet");
// need to call loadQuadraticObjective here ???
}
// CbcModel model(pSolver);
// model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
// solve the problem
//mexPrintf("Trying to solve the problem.\n");
if (isMIP) {
pSolver->branchAndBound();
// model.branchAndBound();
} else {
// model.initialSolve();
pSolver->initialSolve();
}
// Allocate memory for return data
plhs[0] = mxCreateDoubleMatrix(n_vars,1, mxREAL); // for the solution
plhs[1] = mxCreateDoubleMatrix(n_cons,1, mxREAL); // for the constraint prices
plhs[2] = mxCreateDoubleMatrix(1,1, mxREAL); // for the return status
double *x = mxGetPr(plhs[0]);
double *y = mxGetPr(plhs[1]);
double *returncode = mxGetPr(plhs[2]);
// Copy solutions if available
if ( pSolver->isProvenOptimal() ) {
// if ( model.isProvenOptimal() ) {
// if ( model.solver()->isProvenOptimal() ) {
//mexPrintf("Solution found.\n");
// extract the solutions
const double * solution = pSolver->getColSolution();
const double * dualvars = pSolver->getRowPrice();
// copy the solution to the outpus
memcpy(x,solution,n_vars*sizeof(double));
memcpy(y,dualvars,n_cons*sizeof(double));
*returncode = 1;
} else {
if ( pSolver->isProvenPrimalInfeasible() ) {
mexPrintf("Primal problem is proven infeasible.\n");
*returncode = 0;
} else if ( pSolver->isProvenDualInfeasible() ) {
mexPrintf("Dual problem is proven infeasible.\n");
*returncode = -1;
} else if ( pSolver->isPrimalObjectiveLimitReached() ) {
mexPrintf("The primal objective limit was reached.\n");
*returncode = -2;
} else if ( pSolver->isDualObjectiveLimitReached() ) {
mexPrintf("The dual objective limit was reached.\n");
*returncode = -3;
} else if ( pSolver->isIterationLimitReached() ) {
mexPrintf("The iteration limit was reached\n");
*returncode = -4;
}
}
// clean up memory
if ( mexprinter!= NULL) delete mexprinter;
delete pSolver;
}
int
main(void)
{
// Create a problem pointer. We use the base class here.
OsiSolverInterface *si;
// When we instantiate the object, we need a specific derived class.
si = new OSIXXX;
// Build our own instance from scratch
/*
* This section adapted from Matt Galati's example
* on the COIN-OR Tutorial website.
*
* Problem from Bertsimas, Tsitsiklis page 21
*
* optimal solution: x* = (1,1)
*
* minimize -1 x0 - 1 x1
* s.t 1 x0 + 2 x1 <= 3
* 2 x0 + 1 x1 <= 3
* x0 >= 0
* x1 >= 0
*/
int n_cols = 2;
double *objective = new double[n_cols];//the objective coefficients
double *col_lb = new double[n_cols];//the column lower bounds
double *col_ub = new double[n_cols];//the column upper bounds
//Define the objective coefficients.
//minimize -1 x0 - 1 x1
objective[0] = -1.0;
objective[1] = -1.0;
//Define the variable lower/upper bounds.
// x0 >= 0 => 0 <= x0 <= infinity
// x1 >= 0 => 0 <= x1 <= infinity
col_lb[0] = 0.0;
col_lb[1] = 0.0;
col_ub[0] = si->getInfinity();
col_ub[1] = si->getInfinity();
int n_rows = 2;
double *row_lb = new double[n_rows]; //the row lower bounds
double *row_ub = new double[n_rows]; //the row upper bounds
//Define the constraint matrix.
CoinPackedMatrix *matrix = new CoinPackedMatrix(false,0,0);
matrix->setDimensions(0, n_cols);
//1 x0 + 2 x1 <= 3 => -infinity <= 1 x0 + 2 x2 <= 3
CoinPackedVector row1;
row1.insert(0, 1.0);
row1.insert(1, 2.0);
row_lb[0] = -1.0 * si->getInfinity();
row_ub[0] = 3.0;
matrix->appendRow(row1);
//2 x0 + 1 x1 <= 3 => -infinity <= 2 x0 + 1 x1 <= 3
CoinPackedVector row2;
row2.insert(0, 2.0);
row2.insert(1, 1.0);
row_lb[1] = -1.0 * si->getInfinity();
row_ub[1] = 3.0;
matrix->appendRow(row2);
//load the problem to OSI
si->loadProblem(*matrix, col_lb, col_ub, objective, row_lb, row_ub);
//write the MPS file to a file called example.mps
si->writeMps("example");
// Solve the (relaxation of the) problem
si->initialSolve();
// Check the solution
if ( si->isProvenOptimal() ) {
std::cout << "Found optimal solution!" << std::endl;
std::cout << "Objective value is " << si->getObjValue() << std::endl;
int n = si->getNumCols();
const double *solution;
solution = si->getColSolution();
// We could then print the solution or examine it.
} else {
std::cout << "Didn't find optimal solution." << std::endl;
// Could then check other status functions.
}
return 0;
}
void ModelDiscrete(const char * const name)
{
// example of direct interfaces for discrete distribution
OsiClpSolverInterface *osiClp1 = new OsiClpSolverInterface();
double INF=osiClp1->getInfinity();
/* Model dimensions */
int nels=44; // ncol=27, nrow=9
/* Sparse matrix data...organized by row */
int mrow[]={ 0, 0, 0, 0, 0,
1, 1, 1, 1,
2, 2, 2,
3, 3, 3, 3, 3,
4, 4, 4, 4,
5, 5, 5, 5, 5, 5,
6, 6, 6, 6, 6,
7, 7, 7, 7, 7, 7,
8, 8, 8, 8, 8, 8 };
int mcol[]={ 0, 1, 2, 3, 4,
5, 6, 7, 8,
9,10, 11,
12, 13, 14, 15, 16,
0, 12, 17, 18,
1, 5, 9, 13, 19, 20,
2, 6, 14, 21, 22,
3, 7, 10, 15, 23, 24,
4, 8, 11, 16, 25, 26 };
double dels[] = { 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, 1.0,
16.0, 9.0, -1.0, 1.0,
15.0, 10.0, 5.0, 11.0, -1.0, 1.0,
28.0, 14.0, 22.0, -1.0, 1.0,
23.0, 15.0, 7.0, 17.0, -1.0, 1.0,
81.0, 57.0, 29.0, 55.0, -1.0, 1.0 };
/* Objective */
/* Objective */
double dobj[]={ 18.0, 21.0, 18.0, 16.0, 10.0, 15.0, 16.0, 14.0, 9.0,
10.0, 9.0, 6.0, 17.0, 16.0, 17.0, 15.0, 10.0, 0.0,
13.0, 0.0, 13.0, 0.0, 7.0, 0.0, 7.0, 0.0, 1.0 };
/* Column bounds */
double dclo[]={ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
double dcup[]={ INF, INF, INF, INF, INF, INF, INF, INF, INF,
INF, INF, INF, INF, INF, INF, INF, INF, INF,
INF, INF, INF, INF, INF, INF, INF, INF, INF };
/* Row bounds */
double drlo[]={ -INF, -INF, -INF, -INF, 0.0, 4.0, 0.0, 8.0, 10.0 };
double drup[]={ 10.0, 19.0, 25.0, 15.0, 0.0, 7.0, 0.0, 8.0, 90.0 };
/* Stages */
int nstg=2;
int n_first_stg_rows=4;
int rstg[]={ 0,0,0,0,1,1,1,1,1 };
int cstg[]={ 0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,1,
1,1,1,1,1,1,1,1,1 };
/* Stochastic data */
int nindp=5;
int nsamp[]={ 5, 2, 5, 5, 3 };
double demand[]={ 200, 220, 250, 270, 300,
50, 150,
140, 160, 180, 200, 220,
10, 50, 80, 100, 340,
580, 600, 620 };
double dprobs[]={ 0.2, 0.05, 0.35, 0.2, 0.2,
0.3, 0.7,
0.1, 0.2, 0.4, 0.2, 0.1,
0.2, 0.2, 0.3, 0.2, 0.1,
0.1, 0.8, 0.1 };
/* local variables */
int ii,jj;
// initialize SmiModel
SmiScnModel *smiModel = new SmiScnModel();
smiModel->setOsiSolverHandle(*osiClp1);
// set core model using Osi interface
OsiClpSolverInterface ocsi;
ocsi.loadProblem(CoinPackedMatrix( 1,mrow,mcol,dels,nels),dclo,dcup,dobj,drlo,drup);
// core model
SmiCoreData *smiCore = new SmiCoreData(&ocsi,nstg,cstg,rstg);
cout << "ModelDiscrete: generated Core data" << endl;
// Create discrete distribution
SmiDiscreteDistribution *smiDD = new SmiDiscreteDistribution(smiCore);
cout << "ModelDiscrete: adding random variables" << endl;
int index=0;
for (jj=0;jj<nindp;jj++)
{
SmiDiscreteRV *smiRV = new SmiDiscreteRV(1);
for (ii=0;ii<nsamp[jj];ii++)
{
CoinPackedVector empty_vec;
CoinPackedMatrix empty_mat;
CoinPackedVector cpv_rlo ;
CoinPackedVector cpv_rup ;
cpv_rlo.insert(n_first_stg_rows + jj, demand[index+ii]);
cpv_rup.insert(n_first_stg_rows + jj, demand[index+ii]);
smiRV->addEvent(empty_mat,empty_vec,empty_vec,empty_vec,cpv_rlo,cpv_rup,dprobs[index+ii]);
cpv_rlo.clear();
cpv_rup.clear();
}
smiDD->addDiscreteRV(smiRV);
index+=nsamp[jj];
}
assert(smiDD->getNumRV() == nindp);
cout << "ModelDiscrete: added " << nindp << " random variables" << endl;
cout << "ModelDiscrete: processing into scenarios" << endl;
smiModel->processDiscreteDistributionIntoScenarios(smiDD);
// load problem data into OsiSolver
smiModel->loadOsiSolverData();
// get Osi pointer
OsiSolverInterface *smiOsi = smiModel->getOsiSolverInterface();
// set some parameters
smiOsi->setHintParam(OsiDoPresolveInInitial,true);
smiOsi->setHintParam(OsiDoScale,true);
smiOsi->setHintParam(OsiDoCrash,true);
// solve using Osi Solver
smiOsi->initialSolve();
// test optimal value
assert(fabs(smiOsi->getObjValue()-1566.042)<0.01);
// test solutions
const double *dsoln = smiOsi->getColSolution();
double objSum = 0.0;
/* The canonical way to traverse the tree:
For each scenario, get the leaf node.
Then get the parent. Repeat until parent is NULL.
(Only the root node has a NULL parent.)
*/
for(int is=0; is<smiModel->getNumScenarios(); ++is)
{
/* this loop calculates the scenario objective value */
double scenSum = 0.0;
// start with leaf node
SmiScnNode *node = smiModel->getLeafNode(is);
// leaf node probability is the scenario probability
double scenprob = node->getModelProb();
while (node != NULL)
{
// getColStart returns the starting index of node in OSI model
for(int j=node->getColStart(); j<node->getColStart()+node->getNumCols(); ++j)
{
// getCoreColIndex returns the corresponding Core index
// in the original (user's) ordering
scenSum += dobj[node->getCoreColIndex(j)]*dsoln[j];
}
// get parent of node
node = node->getParent();
}
objSum += scenSum*scenprob;
}
assert(fabs(smiOsi->getObjValue()-objSum) < 0.01);
// print results
printf("Solved stochastic program %s\n", name);
printf("Number of rows: %d\n",smiOsi->getNumRows());
printf("Number of cols: %d\n",smiOsi->getNumCols());
printf("Optimal value: %g\n",smiOsi->getObjValue());
}
//--------------------------------------------------------------------------
// test the simple rounding cut generators methods.
void
CglSimpleRoundingUnitTest(
const OsiSolverInterface * baseSiP,
const std::string mpsDir )
{
// Test default constructor
{
CglSimpleRounding cg;
}
// Test copy & assignment
{
CglSimpleRounding rhs;
{
CglSimpleRounding cg;
CglSimpleRounding cgC(cg);
rhs=cg;
}
}
// Test gcd and gcdn
{
CglSimpleRounding cg;
int v = cg.gcd(122,356);
assert(v==2);
v=cg.gcd(356,122);
assert(v==2);
v=cg.gcd(54,67);
assert(v==1);
v=cg.gcd(67,54);
assert(v==1);
v=cg.gcd(485,485);
assert(v==485);
v=cg.gcd(17*13,17*23);
assert( v==17);
v=cg.gcd(17*13*5,17*23);
assert( v==17);
v=cg.gcd(17*13*23,17*23);
assert(v==17*23);
int a[4] = {12, 20, 32, 400};
v= cg.gcdv(4,a);
assert(v== 4);
int b[4] = {782, 4692, 51, 2754};
v= cg.gcdv(4,b);
assert(v== 17);
int c[4] = {50, 40, 30, 10};
v= cg.gcdv(4,c);
assert(v== 10);
}
// Test generate cuts method on exmip1.5.mps
{
CglSimpleRounding cg;
OsiSolverInterface * siP = baseSiP->clone();
std::string fn = mpsDir+"exmip1.5.mps";
siP->readMps(fn.c_str(),"");
OsiCuts cuts;
cg.generateCuts(*siP,cuts);
// there should be 3 cuts
int nRowCuts = cuts.sizeRowCuts();
assert(nRowCuts==3);
// get the last "sr"=simple rounding cut that was derived
OsiRowCut srRowCut2 = cuts.rowCut(2);
CoinPackedVector srRowCutPV2 = srRowCut2.row();
// this is what the last cut should look like: i.e. the "solution"
const int solSize = 2;
int solCols[solSize]={2,3};
double solCoefs[solSize]={5.0, 4.0};
OsiRowCut solRowCut;
solRowCut.setRow(solSize,solCols,solCoefs);
solRowCut.setLb(-COIN_DBL_MAX);
solRowCut.setUb(2.0);
// Test for equality between the derived cut and the solution cut
// Note: testing two OsiRowCuts are equal invokes testing two
// CoinPackedVectors are equal which invokes testing two doubles
// are equal. Usually not a good idea to test that two doubles are equal,
// but in this cut the "doubles" represent integer values. Also allow that
// different solvers have different orderings in packed vectors, which may
// not match the ordering defined for solRowCut.
assert(srRowCut2.OsiCut::operator==(solRowCut)) ;
assert(srRowCut2.row().isEquivalent(solRowCut.row())) ;
assert(srRowCut2.lb() == solRowCut.lb()) ;
assert(srRowCut2.ub() == solRowCut.ub()) ;
delete siP;
}
// Test generate cuts method on p0033
{
CglSimpleRounding cg;
OsiSolverInterface * siP = baseSiP->clone();
std::string fn = mpsDir+"p0033";
siP->readMps(fn.c_str(),"mps");
OsiCuts cuts;
cg.generateCuts(*siP,cuts);
// p0033 is the optimal solution to p0033
int objIndices[14] = {
0, 6, 7, 9, 13, 17, 18,
22, 24, 25, 26, 27, 28, 29 };
CoinPackedVector p0033(14,objIndices,1.0);
// test that none of the generated cuts
// chops off the optimal solution
int nRowCuts = cuts.sizeRowCuts();
OsiRowCut rcut;
CoinPackedVector rpv;
int i;
for (i=0; i<nRowCuts; i++){
rcut = cuts.rowCut(i);
rpv = rcut.row();
double p0033Sum = (rpv*p0033).sum();
double rcutub = rcut.ub();
assert (p0033Sum <= rcutub);
}
// test that the cuts improve the
// lp objective function value
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("Final LP min=%f\n\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
delete siP;
}
}
//--------------------------------------------------------------------------
// test EKKsolution methods.
void
CglOddHoleUnitTest(
const OsiSolverInterface * baseSiP,
const std::string mpsDir )
{
CoinRelFltEq eq(0.000001);
// Test default constructor
{
CglOddHole aGenerator;
}
// Test copy & assignment
{
CglOddHole rhs;
{
CglOddHole bGenerator;
CglOddHole cGenerator(bGenerator);
rhs=bGenerator;
}
}
// test on simple case
{
const int nRows=3;
const int nCols=3;
const int nEls=6;
const double elem[]={1.0,1.0,1.0,1.0,1.0,1.0};
const int row[]={0,1,0,2,1,2};
const CoinBigIndex start[]={0,2,4};
const int len[]={2,2,2};
CoinPackedMatrix matrix(true,nRows,nCols,nEls,elem,row,start,len);
const double sol[]={0.5,0.5,0.5};
const double dj[]={0,0,0};
const int which[]={1,1,1};
const int fixed[]={0,0,0};
OsiCuts cs;
CglOddHole test1;
CglTreeInfo info;
info.randomNumberGenerator=NULL;
test1.generateCuts(NULL,matrix,sol,dj,cs,which,fixed,info,true);
CoinPackedVector check;
int index[] = {0,1,2};
double el[] = {1,1,1};
check.setVector(3,index,el);
//assert (cs.sizeRowCuts()==2);
assert (cs.sizeRowCuts()==1);
// sort Elements in increasing order
CoinPackedVector rpv=cs.rowCut(0).row();
rpv.sortIncrIndex();
assert (check==rpv);
}
// Testcase /u/rlh/osl2/mps/scOneInt.mps
// Model has 3 continous, 2 binary, and 1 general
// integer variable.
{
OsiSolverInterface * siP = baseSiP->clone();
std::string fn = mpsDir+"scOneInt";
siP->readMps(fn.c_str(),"mps");
#if 0
CglOddHole cg;
int nCols=siP->getNumCols();
// Test the siP methods for detecting
// variable type
int numCont=0, numBinary=0, numIntNonBinary=0, numInt=0;
for (int thisCol=0; thisCol<nCols; thisCol++) {
if ( siP->isContinuous(thisCol) ) numCont++;
if ( siP->isBinary(thisCol) ) numBinary++;
if ( siP->isIntegerNonBinary(thisCol) ) numIntNonBinary++;
if ( siP->isInteger(thisCol) ) numInt++;
}
assert(numCont==3);
assert(numBinary==2);
assert(numIntNonBinary==1);
assert(numInt==3);
// Test initializeCutGenerator
siP->initialSolve();
assert(xstar !=NULL);
for (i=0; i<nCols; i++){
assert(complement[i]==0);
}
int nRows=siP->getNumRows();
for (i=0; i<nRows; i++){
int vectorsize = siP->getMatrixByRow()->getVectorSize(i);
assert(vectorsize==2);
}
kccg.cleanUpCutGenerator(complement,xstar);
#endif
delete siP;
}
}
void
CglRedSplitUnitTest(const OsiSolverInterface *baseSiP,
const std::string mpsDir)
{
// Test default constructor
{
CglRedSplit aGenerator;
}
// Test copy & assignment
{
CglRedSplit rhs;
{
CglRedSplit bGenerator;
CglRedSplit cGenerator(bGenerator);
rhs=bGenerator;
}
}
// Test get/set methods
{
CglRedSplit getset;
CglRedSplitParam gsparam = getset.getParam();
double geps = 10 * gsparam.getEPS();
gsparam.setEPS(geps);
double geps2 = gsparam.getEPS();
assert(geps == geps2);
double gepse = 10 * gsparam.getEPS_ELIM();
gsparam.setEPS_ELIM(gepse);
double gepse2 = gsparam.getEPS_ELIM();
assert(gepse == gepse2);
double gmv = 10 * gsparam.getMINVIOL();
gsparam.setMINVIOL(gmv);
double gmv2 = gsparam.getMINVIOL();
assert(gmv == gmv2);
int gucg = gsparam.getUSE_CG2();
gucg = 1 - gucg;
gsparam.setUSE_CG2(gucg);
int gucg2 = gsparam.getUSE_CG2();
assert(gucg == gucg2);
}
// Test generateCuts
{
CglRedSplit gct;
OsiSolverInterface *siP = baseSiP->clone();
std::string fn = mpsDir+"p0033";
std::string fn2 = mpsDir+"p0033.mps";
FILE *in_f = fopen(fn2.c_str(), "r");
if(in_f == NULL) {
std::cout<<"Can not open file "<<fn2<<std::endl<<"Skip test of CglRedSplit::generateCuts()"<<std::endl;
}
else {
fclose(in_f);
siP->readMps(fn.c_str(),"mps");
siP->initialSolve();
double lpRelax = siP->getObjValue();
OsiCuts cs;
gct.getParam().setMAX_SUPPORT(34);
gct.getParam().setUSE_CG2(1);
// gct.getParam().setUSE_CG2(1);
gct.generateCuts(*siP, cs);
int nRowCuts = cs.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" Reduce-and-Split cuts"<<std::endl;
assert(cs.sizeRowCuts() > 0);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cs);
siP->resolve();
double lpRelaxAfter= siP->getObjValue();
std::cout<<"Initial LP value: "<<lpRelax<<std::endl;
std::cout<<"LP value with cuts: "<<lpRelaxAfter<<std::endl;
assert( lpRelax < lpRelaxAfter );
assert(lpRelaxAfter < 3089.1);
}
delete siP;
}
}
void
CglLandPUnitTest(
OsiSolverInterface * si,
const std::string &mpsDir)
{
CoinRelFltEq eq(1e-05);
// Test default constructor
{
CglLandP aGenerator;
assert(aGenerator.parameter().pivotLimit==20);
assert(aGenerator.parameter().maxCutPerRound==5000);
assert(aGenerator.parameter().failedPivotLimit==1);
assert(aGenerator.parameter().degeneratePivotLimit==0);
assert(eq(aGenerator.parameter().pivotTol, 1e-04));
assert(eq(aGenerator.parameter().away, 5e-04));
assert(eq(aGenerator.parameter().timeLimit, COIN_DBL_MAX));
assert(eq(aGenerator.parameter().singleCutTimeLimit, COIN_DBL_MAX));
assert(aGenerator.parameter().useTableauRow==true);
assert(aGenerator.parameter().modularize==false);
assert(aGenerator.parameter().strengthen==true);
assert(aGenerator.parameter().perturb==true);
assert(aGenerator.parameter().pivotSelection==CglLandP::mostNegativeRc);
}
// Test copy constructor
{
CglLandP a;
{
CglLandP b;
b.parameter().pivotLimit = 100;
b.parameter().maxCutPerRound = 100;
b.parameter().failedPivotLimit = 10;
b.parameter().degeneratePivotLimit = 10;
b.parameter().pivotTol = 1e-07;
b.parameter().away = 1e-10;
b.parameter().timeLimit = 120;
b.parameter().singleCutTimeLimit = 15;
b.parameter().useTableauRow = true;
b.parameter().modularize = true;
b.parameter().strengthen = false;
b.parameter().perturb = false;
b.parameter().pivotSelection=CglLandP::bestPivot;
//Test Copy
CglLandP c(b);
assert(c.parameter().pivotLimit == 100);
assert(c.parameter().maxCutPerRound == 100);
assert(c.parameter().failedPivotLimit == 10);
assert(c.parameter().degeneratePivotLimit == 10);
assert(c.parameter().pivotTol == 1e-07);
assert(c.parameter().away == 1e-10);
assert(c.parameter().timeLimit == 120);
assert(c.parameter().singleCutTimeLimit == 15);
assert(c.parameter().useTableauRow == true);
assert(c.parameter().modularize == true);
assert(c.parameter().strengthen == false);
assert(c.parameter().perturb == false);
assert(c.parameter().pivotSelection == CglLandP::bestPivot);
a=b;
assert(a.parameter().pivotLimit == 100);
assert(a.parameter().maxCutPerRound == 100);
assert(a.parameter().failedPivotLimit == 10);
assert(a.parameter().degeneratePivotLimit == 10);
assert(a.parameter().pivotTol == 1e-07);
assert(a.parameter().away == 1e-10);
assert(a.parameter().timeLimit == 120);
assert(a.parameter().singleCutTimeLimit == 15);
assert(a.parameter().useTableauRow == true);
assert(a.parameter().modularize == true);
assert(a.parameter().strengthen == false);
assert(a.parameter().perturb == false);
assert(a.parameter().pivotSelection == CglLandP::bestPivot);
}
}
{
// Maximize 2 x2
// s.t.
// 2x1 + 2x2 <= 3
// -2x1 + 2x2 <= 1
// 7x1 + 4x2 <= 8
// -7x1 + 4x2 <= 1
// x1, x2 >= 0 and x1, x2 integer
// Slacks are s1, s2, s3, s4
//Test that problem is correct
// Optimal Basis is x1, x2, s3, s4 with tableau
// x1 0.25 s1 -0.25 s2 = 0.5
// x2 0.25 s1 0.25 s2 = 1
// -2.75 s1 0.75 s2 s3 = 0.5
// 0.75 s1 -2.75 s2 s4 = 0.5
// z= -0.25 s1 -0.25 s2 = -1
// Gomory cut from variable x1 is x2 <= 0.5
// Can be improved by first pivoting s2 in and s4 out, then s1 in and s3 out
// to x2 <= 0.25
{
int start[2] = {0,4};
int length[2] = {4,4};
int rows[8] = {0,1,2,3,0,1,2,3};
double elements[8] = {2.0,-2.0,7.0,-7.0,2.0,2.0,4.0,4.0};
CoinPackedMatrix columnCopy(true,4,2,8,elements,rows,start,length);
double rowLower[4]={-COIN_DBL_MAX,-COIN_DBL_MAX,
-COIN_DBL_MAX,-COIN_DBL_MAX};
double rowUpper[4]={3.,1.,8.,1.};
double colLower[2]={0.0,0.0};
double colUpper[2]={1.0,1.0};
double obj[2]={-1,-1};
int intVar[2]={0,1};
OsiSolverInterface * siP = si->clone();
siP->loadProblem(columnCopy, colLower, colUpper, obj, rowLower, rowUpper);
siP->setInteger(intVar,2);
CglLandP test;
test.setLogLevel(2);
test.parameter().sepSpace = CglLandP::Full;
siP->resolve();
// Test generateCuts method
{
OsiCuts cuts;
test.generateCuts(*siP,cuts);
cuts.printCuts();
assert(cuts.sizeRowCuts()==1);
OsiRowCut aCut = cuts.rowCut(0);
assert(eq(aCut.lb(), -.0714286));
CoinPackedVector row = aCut.row();
if (row.getNumElements() == 1)
{
assert(row.getIndices()[0]==1);
assert(eq(row.getElements()[0], -4*.0714286));
}
else if (row.getNumElements() == 2)
{
assert(row.getIndices()[0]==0);
assert(eq(row.getElements()[0], 0.));
assert(row.getIndices()[1]==1);
assert(eq(row.getElements()[1], -1));
}
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
}
if (0)
{
OsiCuts cuts;
test.generateCuts(*siP,cuts);
cuts.printCuts();
assert(cuts.sizeRowCuts()==1);
OsiRowCut aCut = cuts.rowCut(0);
CoinPackedVector row = aCut.row();
if (row.getNumElements() == 1)
{
assert(row.getIndices()[0]==1);
assert(eq(row.getElements()[0], -1));
}
else if (row.getNumElements() == 2)
{
assert(row.getIndices()[0]==0);
assert(eq(row.getElements()[0], 0.));
assert(row.getIndices()[1]==1);
assert(eq(row.getElements()[1], -1));
}
assert(eq(aCut.lb(), 0.));
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
}
delete siP;
}
}
if (1) //Test on p0033
{
// Setup
OsiSolverInterface * siP = si->clone();
std::string fn(mpsDir+"p0033");
siP->readMps(fn.c_str(),"mps");
siP->activateRowCutDebugger("p0033");
CglLandP test;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, 2520.5717391304347) );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
#endif
OsiCuts cuts;
// Test generateCuts method
test.generateCuts(*siP,cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
//assert( eq(lpRelaxAfter, 2592.1908295194507) );
std::cout<<"Relaxation after "<<lpRelaxAfter<<std::endl;
assert( lpRelaxAfter> 2840. );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
delete siP;
}
if (1) //test again with modularization
{
// Setup
OsiSolverInterface * siP = si->clone();
std::string fn(mpsDir+"p0033");
siP->readMps(fn.c_str(),"mps");
siP->activateRowCutDebugger("p0033");
CglLandP test;
test.parameter().modularize = true;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, 2520.5717391304347) );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
#endif
OsiCuts cuts;
// Test generateCuts method
test.generateCuts(*siP,cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
//assert( eq(lpRelaxAfter, 2592.1908295194507) );
std::cout<<"Relaxation after "<<lpRelaxAfter<<std::endl;
assert( lpRelaxAfter> 2840. );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
delete siP;
}
if (1) //test again with alternate pivoting rule
{
// Setup
OsiSolverInterface * siP = si->clone();
std::string fn(mpsDir+"p0033");
siP->readMps(fn.c_str(),"mps");
siP->activateRowCutDebugger("p0033");
CglLandP test;
test.parameter().pivotSelection = CglLandP::bestPivot;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, 2520.5717391304347) );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
#endif
OsiCuts cuts;
// Test generateCuts method
test.generateCuts(*siP,cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
//assert( eq(lpRelaxAfter, 2592.1908295194507) );
std::cout<<"Relaxation after "<<lpRelaxAfter<<std::endl;
assert( lpRelaxAfter> 2840. );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
delete siP;
}
if (1) //Finally test code in documentation
{
// Setup
OsiSolverInterface * siP = si->clone();
std::string fn(mpsDir+"p0033");
siP->readMps(fn.c_str(),"mps");
siP->activateRowCutDebugger("p0033");
CglLandP landpGen;
landpGen.parameter().timeLimit = 10.;
landpGen.parameter().pivotLimit = 2;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, 2520.5717391304347) );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
#endif
OsiCuts cuts;
// Test generateCuts method
landpGen.generateCuts(*siP, cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
//assert( eq(lpRelaxAfter, 2592.1908295194507) );
std::cout<<"Relaxation after "<<lpRelaxAfter<<std::endl;
assert( lpRelaxAfter> 2840. );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
delete siP;
}
}
//Solver function
int sci_rmps(char *fname)
{
//creating a problem pointer using base class of OsiSolverInterface and
//instantiate the object using derived class of ClpSolverInterface
OsiSolverInterface* si = new OsiClpSolverInterface();
// Error management variable
SciErr sciErr;
//data declarations
int *piAddressVarOne = NULL; //pointer used to access argument of the function
char* ptr; //pointer to point to address of file name
double* options_; //options to set maximum iterations
CheckInputArgument(pvApiCtx, 2,2 ); //Check we have exactly two arguments as input or not
CheckOutputArgument(pvApiCtx, 6, 6); //Check we have exactly six arguments on output side or not
//Getting the input arguments from Scilab
//Getting the MPS file path
//Reading mps file
getStringFromScilab(1,&ptr);
std::cout<<ptr;
//get options from Scilab
if(getFixedSizeDoubleMatrixInList(2 , 2 , 1 , 1 , &options_))
{
return 1;
}
//Read the MPS file
si->readMps(ptr);
//setting options for maximum iterations
si->setIntParam(OsiMaxNumIteration,options_[0]);
//Solve the problem
si->initialSolve();
//Quering about the problem
//get number of variables
double numVars_;
numVars_ = si->getNumCols();
//get number of constraint equations
double numCons_;
numCons_ = si->getNumRows();
//Output the solution to Scilab
//get solution for x
const double* xValue = si->getColSolution();
//get objective value
double objValue = si->getObjValue();
//get Status value
double status;
if(si->isProvenOptimal())
status=0;
else if(si->isProvenPrimalInfeasible())
status=1;
else if(si->isProvenDualInfeasible())
status=2;
else if(si->isIterationLimitReached())
status=3;
else if(si->isAbandoned())
status=4;
else if(si->isPrimalObjectiveLimitReached())
status=5;
else if(si->isDualObjectiveLimitReached())
status=6;
//get number of iterations
double iterations = si->getIterationCount();
//get reduced cost
const double* reducedCost = si->getReducedCost();
//get dual vector
const double* dual = si->getRowPrice();
returnDoubleMatrixToScilab(1 , 1 , numVars_ , xValue);
returnDoubleMatrixToScilab(2 , 1 , 1 , &objValue);
returnDoubleMatrixToScilab(3 , 1 , 1 , &status);
returnDoubleMatrixToScilab(4 , 1 , 1 , &iterations);
returnDoubleMatrixToScilab(5 , 1 , numVars_ , reducedCost);
returnDoubleMatrixToScilab(6 , 1 , numCons_ , dual);
free(xValue);
free(dual);
free(reducedCost);
}
//--------------------------------------------------------------------------
void
CglKnapsackCoverUnitTest(
const OsiSolverInterface * baseSiP,
const std::string mpsDir )
{
int i;
CoinRelFltEq eq(0.000001);
// Test default constructor
{
CglKnapsackCover kccGenerator;
}
// Test copy & assignment
{
CglKnapsackCover rhs;
{
CglKnapsackCover kccGenerator;
CglKnapsackCover cgC(kccGenerator);
rhs=kccGenerator;
}
}
// test exactSolveKnapsack
{
CglKnapsackCover kccg;
const int n=7;
double c=50;
double p[n] = {70,20,39,37,7,5,10};
double w[n] = {31, 10, 20, 19, 4, 3, 6};
double z;
int x[n];
int exactsol = kccg.exactSolveKnapsack(n, c, p, w, z, x);
assert(exactsol==1);
assert (z == 107);
assert (x[0]==1);
assert (x[1]==0);
assert (x[2]==0);
assert (x[3]==1);
assert (x[4]==0);
assert (x[5]==0);
assert (x[6]==0);
}
/*
// Testcase /u/rlh/osl2/mps/scOneInt.mps
// Model has 3 continous, 2 binary, and 1 general
// integer variable.
{
OsiSolverInterface * siP = baseSiP->clone();
int * complement=NULL;
double * xstar=NULL;
siP->readMps("../Mps/scOneInt","mps");
CglKnapsackCover kccg;
int nCols=siP->getNumCols();
// Test the siP methods for detecting
// variable type
int numCont=0, numBinary=0, numIntNonBinary=0, numInt=0;
for (int thisCol=0; thisCol<nCols; thisCol++) {
if ( siP->isContinuous(thisCol) ) numCont++;
if ( siP->isBinary(thisCol) ) numBinary++;
if ( siP->isIntegerNonBinary(thisCol) ) numIntNonBinary++;
if ( siP->isInteger(thisCol) ) numInt++;
}
assert(numCont==3);
assert(numBinary==2);
assert(numIntNonBinary==1);
assert(numInt==3);
// Test initializeCutGenerator
siP->initialSolve();
assert(xstar !=NULL);
for (i=0; i<nCols; i++){
assert(complement[i]==0);
}
int nRows=siP->getNumRows();
for (i=0; i<nRows; i++){
int vectorsize = siP->getMatrixByRow()->vectorSize(i);
assert(vectorsize==2);
}
kccg.cleanUpCutGenerator(complement,xstar);
delete siP;
}
*/
// Testcase /u/rlh/osl2/mps/tp3.mps
// Models has 3 cols, 3 rows
// Row 0 yields a knapsack, others do not.
{
// setup
OsiSolverInterface * siP = baseSiP->clone();
std::string fn(mpsDir+"tp3");
siP->readMps(fn.c_str(),"mps");
// All integer variables should be binary.
// Assert that this is true.
for ( i = 0; i < siP->getNumCols(); i++ )
if ( siP->isInteger(i) )
assert(siP->getColUpper()[i]==1.0 && siP->isBinary(i));
OsiCuts cs;
CoinPackedVector krow;
double b=0;
int nCols=siP->getNumCols();
int * complement=new int [nCols];
double * xstar=new double [nCols];
CglKnapsackCover kccg;
// solve LP relaxation
// a "must" before calling initialization
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
std::cout<<"Initial LP value: "<<lpRelaxBefore<<std::endl;
assert( eq(siP->getObjValue(), 97.185) );
double mycs[] = {.627, .667558333333, .038};
siP->setColSolution(mycs);
const double *colsol = siP->getColSolution();
int k;
for (k=0; k<nCols; k++){
xstar[k]=colsol[k];
complement[k]=0;
}
// test deriveAKnapsack
int rind = ( siP->getRowSense()[0] == 'N' ) ? 1 : 0;
const CoinShallowPackedVector reqdBySunCC = siP->getMatrixByRow()->getVector(rind) ;
int deriveaknap = kccg.deriveAKnapsack(*siP, cs, krow,b,complement,xstar,rind,reqdBySunCC);
assert(deriveaknap ==1);
assert(complement[0]==0);
assert(complement[1]==1);
assert(complement[2]==1);
int inx[3] = {0,1,2};
double el[3] = {161, 120, 68};
CoinPackedVector r;
r.setVector(3,inx,el);
assert (krow == r);
//assert (b == 183.0); ????? but x1 and x2 at 1 is valid
// test findGreedyCover
CoinPackedVector cover,remainder;
#if 0
int findgreedy = kccg.findGreedyCover( 0, krow, b, xstar, cover, remainder );
assert( findgreedy == 1 );
int coveri = cover.getNumElements();
assert( cover.getNumElements() == 2);
coveri = cover.getIndices()[0];
assert( cover.getIndices()[0] == 0);
assert( cover.getIndices()[1] == 1);
assert( cover.getElements()[0] == 161.0);
assert( cover.getElements()[1] == 120.0);
assert( remainder.getNumElements() == 1);
assert( remainder.getIndices()[0] == 2);
assert( remainder.getElements()[0] == 68.0);
// test liftCoverCut
CoinPackedVector cut;
double * rowupper = ekk_rowupper(model);
double cutRhs = cover.getNumElements() - 1.0;
kccg.liftCoverCut(b, krow.getNumElements(),
cover, remainder,
cut);
assert ( cut.getNumElements() == 3 );
assert ( cut.getIndices()[0] == 0 );
assert ( cut.getIndices()[1] == 1 );
assert ( cut.getIndices()[2] == 2 );
assert( cut.getElements()[0] == 1 );
assert( cut.getElements()[1] == 1 );
assert( eq(cut.getElements()[2], 0.087719) );
// test liftAndUncomplementAndAdd
OsiCuts cuts;
kccg.liftAndUncomplementAndAdd(*siP.getRowUpper()[0],krow,b,complement,0,
cover,remainder,cuts);
int sizerowcuts = cuts.sizeRowCuts();
assert ( sizerowcuts== 1 );
OsiRowCut testRowCut = cuts.rowCut(0);
CoinPackedVector testRowPV = testRowCut.row();
OsiRowCut sampleRowCut;
const int sampleSize = 3;
int sampleCols[sampleSize]={0,1,2};
double sampleElems[sampleSize]={1.0,-1.0,-0.087719};
sampleRowCut.setRow(sampleSize,sampleCols,sampleElems);
sampleRowCut.setLb(-DBL_MAX);
sampleRowCut.setUb(-0.087719);
bool equiv = testRowPV.equivalent(sampleRowCut.row(),CoinRelFltEq(1.0e-05) );
assert ( equiv );
#endif
// test find PseudoJohnAndEllisCover
cover.setVector(0,NULL, NULL);
remainder.setVector(0,NULL,NULL);
rind = ( siP->getRowSense()[0] == 'N' ) ? 1 : 0;
int findPJE = kccg.findPseudoJohnAndEllisCover( rind, krow,
b, xstar, cover, remainder );
assert( findPJE == 1 );
assert ( cover.getIndices()[0] == 0 );
assert ( cover.getIndices()[1] == 2 );
assert ( cover.getElements()[0] == 161 );
assert ( cover.getElements()[1] == 68 );
assert ( remainder.getIndices()[0] == 1 );
assert ( remainder.getElements()[0] == 120 );
OsiCuts cuts;
kccg.liftAndUncomplementAndAdd((*siP).getRowUpper()[rind],krow,b, complement, rind,
cover,remainder,cuts);
assert (cuts.sizeRowCuts() == 1 );
OsiRowCut testRowCut = cuts.rowCut(0);
CoinPackedVector testRowPV = testRowCut.row();
const int sampleSize = 3;
int sampleCols[sampleSize]={0,1,2};
double sampleElems[sampleSize]={1.0, -1.0, -1.0};
OsiRowCut sampleRowCut;
sampleRowCut.setRow(sampleSize,sampleCols,sampleElems);
sampleRowCut.setLb(-COIN_DBL_MAX);
sampleRowCut.setUb(-1.0);
// test for 'close enough'
assert( testRowPV.isEquivalent(sampleRowCut.row(),CoinRelFltEq(1.0e-05) ) );
// Reset complement & test next row
for (i=0; i<nCols; i++){
complement[i]=0;
}
rind++;
const CoinShallowPackedVector reqdBySunCC2 = siP->getMatrixByRow()->getVector(rind) ;
deriveaknap = kccg.deriveAKnapsack(*siP,cuts,krow,b,complement,xstar,rind,reqdBySunCC2);
assert(deriveaknap==0);
// Reset complement & test next row
for (i=0; i<nCols; i++){
complement[i]=0;
}
const CoinShallowPackedVector reqdBySunCC3 = siP->getMatrixByRow()->getVector(2) ;
deriveaknap = kccg.deriveAKnapsack(*siP,cuts,krow,b,complement,xstar,2,
reqdBySunCC3);
assert(deriveaknap == 0);
// Clean up
delete [] complement;
delete [] xstar;
delete siP;
}
#if 0
// Testcase /u/rlh/osl2/mps/tp4.mps
// Models has 6 cols, 1 knapsack row and
// 3 rows explicily bounding variables
// Row 0 yields a knapsack cover cut
// using findGreedyCover which moves the
// LP objective function value.
{
// Setup
EKKContext * env=ekk_initializeContext();
EKKModel * model = ekk_newModel(env,"");
OsiSolverInterface si(model);
ekk_importModel(model, "tp4.mps");
CglKnapsackCover kccg;
kccg.ekk_validateIntType(si);
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
ekk_allSlackBasis(model);
ekk_crash(model,1);
ekk_primalSimplex(model,1);
double lpRelaxBefore=ekk_getRobjvalue(model);
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
#endif
// Determine if lp sol is ip optimal
// Note: no ekk_function to do this
int nCols=ekk_getInumcols(model);
double * optLpSol = ekk_colsol(model);
int ipOpt = 1;
i=0;
while (i++<nCols && ipOpt){
if(optLpSol[i] < 1.0-1.0e-08 && optLpSol[i]> 1.0e-08) ipOpt = 0;
}
if (ipOpt){
#ifdef CGL_DEBUG
printf("Lp solution is within ip optimality tolerance\n");
#endif
}
else {
OsiSolverInterface iModel(model);
OsiCuts cuts;
// Test generateCuts method
kccg.generateCuts(iModel,cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = iModel.applyCuts(cuts);
ekk_mergeBlocks(model,1);
ekk_dualSimplex(model);
double lpRelaxAfter=ekk_getRobjvalue(model);
#ifdef CGL_DEBUG
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
// This may need to be updated as other
// minimal cover finders are added
assert( cuts.sizeRowCuts() == 1 );
OsiRowCut testRowCut = cuts.rowCut(0);
CoinPackedVector testRowPV = testRowCut.row();
OsiRowCut sampleRowCut;
const int sampleSize = 6;
int sampleCols[sampleSize]={0,1,2,3,4,5};
double sampleElems[sampleSize]={1.0,1.0,1.0,1.0,0.5, 2.0};
sampleRowCut.setRow(sampleSize,sampleCols,sampleElems);
sampleRowCut.setLb(-DBL_MAX);
sampleRowCut.setUb(3.0);
bool equiv = testRowPV.equivalent(sampleRowCut.row(),CoinRelFltEq(1.0e-05) );
assert( testRowPV.equivalent(sampleRowCut.row(),CoinRelFltEq(1.0e-05) ) );
}
// Exit out of OSL
ekk_deleteModel(model);
ekk_endContext(env);
}
#endif
// Testcase /u/rlh/osl2/mps/tp5.mps
// Models has 6 cols, 1 knapsack row and
// 3 rows explicily bounding variables
// Row 0 yields a knapsack cover cut
// using findGreedyCover which moves the
// LP objective function value.
{
// Setup
OsiSolverInterface * siP = baseSiP->clone();
std::string fn(mpsDir+"tp5");
siP->readMps(fn.c_str(),"mps");
// All integer variables should be binary.
// Assert that this is true.
for ( i = 0; i < siP->getNumCols(); i++ )
if ( siP->isInteger(i) )
assert(siP->getColUpper()[i]==1.0 && siP->isBinary(i));
CglKnapsackCover kccg;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, -51.66666666667) );
double mycs[] = {.8999999999, .899999999999, .89999999999, 1.110223e-16, .5166666666667, 0};
siP->setColSolution(mycs);
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
#endif
// Determine if lp sol is 0/1 optimal
int nCols=siP->getNumCols();
const double * optLpSol = siP->getColSolution();
bool ipOpt = true;
i=0;
while (i++<nCols && ipOpt){
if(optLpSol[i] > kccg.epsilon_ && optLpSol[i] < kccg.onetol_) ipOpt = false;
}
if (ipOpt){
#ifdef CGL_DEBUG
printf("Lp solution is within ip optimality tolerance\n");
#endif
}
else {
// set up
OsiCuts cuts;
CoinPackedVector krow;
double b=0.0;
int * complement=new int[nCols];
double * xstar=new double[nCols];
// initialize cut generator
const double *colsol = siP->getColSolution();
for (i=0; i<nCols; i++){
xstar[i]=colsol[i];
complement[i]=0;
}
int row = ( siP->getRowSense()[0] == 'N' ) ? 1 : 0;
// transform row into canonical knapsack form
const CoinShallowPackedVector reqdBySunCC = siP->getMatrixByRow()->getVector(row) ;
if (kccg.deriveAKnapsack(*siP, cuts, krow, b, complement, xstar, row,reqdBySunCC)){
CoinPackedVector cover, remainder;
// apply greedy logic to detect violated minimal cover inequalities
if (kccg.findGreedyCover(row, krow, b, xstar, cover, remainder) == 1){
// lift, uncomplements, and add cut to cut set
kccg.liftAndUncomplementAndAdd((*siP).getRowUpper()[row],krow, b, complement, row, cover, remainder, cuts);
}
// reset optimal column solution (xstar) information in OSL
const double * rowupper = siP->getRowUpper();
int k;
if (fabs(b-rowupper[row]) > 1.0e-05) {
for(k=0; k<krow.getNumElements(); k++) {
if (complement[krow.getIndices()[k]]){
xstar[krow.getIndices()[k]]= 1.0-xstar[krow.getIndices()[k]];
complement[krow.getIndices()[k]]=0;
}
}
}
// clean up
delete [] complement;
delete [] xstar;
}
// apply the cuts
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
assert( eq(lpRelaxAfter, -30.0) );
#ifdef CGL_DEBUG
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
// test that expected cut was detected
assert( lpRelaxBefore < lpRelaxAfter );
assert( cuts.sizeRowCuts() == 1 );
OsiRowCut testRowCut = cuts.rowCut(0);
CoinPackedVector testRowPV = testRowCut.row();
OsiRowCut sampleRowCut;
const int sampleSize = 6;
int sampleCols[sampleSize]={0,1,2,3,4,5};
double sampleElems[sampleSize]={1.0,1.0,1.0,0.25,1.0,2.0};
sampleRowCut.setRow(sampleSize,sampleCols,sampleElems);
sampleRowCut.setLb(-COIN_DBL_MAX);
sampleRowCut.setUb(3.0);
assert(testRowPV.isEquivalent(sampleRowCut.row(),CoinRelFltEq(1.0e-05)));
}
delete siP;
}
// Testcase /u/rlh/osl2/mps/p0033
// Miplib3 problem p0033
// Test that no cuts chop off the optimal solution
{
// Setup
OsiSolverInterface * siP = baseSiP->clone();
std::string fn(mpsDir+"p0033");
siP->readMps(fn.c_str(),"mps");
// All integer variables should be binary.
// Assert that this is true.
for ( i = 0; i < siP->getNumCols(); i++ )
if ( siP->isInteger(i) )
assert(siP->getColUpper()[i]==1.0 && siP->isBinary(i));
int nCols=siP->getNumCols();
CglKnapsackCover kccg;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, 2520.5717391304347) );
double mycs[] = {0, 1, 0, 0, -2.0837010502455788e-19, 1, 0, 0, 1,
0.021739130434782594, 0.35652173913043478,
-6.7220534694101275e-18, 5.3125906451789717e-18,
1, 0, 1.9298798670241979e-17, 0, 0, 0,
7.8875708048320448e-18, 0.5, 0,
0.85999999999999999, 1, 1, 0.57999999999999996,
1, 0, 1, 0, 0.25, 0, 0.67500000000000004};
siP->setColSolution(mycs);
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
#endif
OsiCuts cuts;
// Test generateCuts method
kccg.generateCuts(*siP,cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
assert( eq(lpRelaxAfter, 2829.0597826086955) );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
// the CoinPackedVector p0033 is the optimal
// IP solution to the miplib problem p0033
int objIndices[14] = {
0, 6, 7, 9, 13, 17, 18,
22, 24, 25, 26, 27, 28, 29 };
CoinPackedVector p0033(14,objIndices,1.0);
// Sanity check
const double * objective=siP->getObjCoefficients();
double ofv =0 ;
int r;
for (r=0; r<nCols; r++){
ofv=ofv + p0033[r]*objective[r];
}
CoinRelFltEq eq;
assert( eq(ofv,3089.0) );
int nRowCuts = cuts.sizeRowCuts();
OsiRowCut rcut;
CoinPackedVector rpv;
for (i=0; i<nRowCuts; i++){
rcut = cuts.rowCut(i);
rpv = rcut.row();
double p0033Sum = (rpv*p0033).sum();
assert (p0033Sum <= rcut.ub() );
}
delete siP;
}
// if a debug file is there then look at it
{
FILE * fp = fopen("knapsack.debug","r");
if (fp) {
int ncol,nel;
double up;
int x = fscanf(fp,"%d %d %lg",&ncol,&nel,&up);
if (x<=0)
throw("bad fscanf");
printf("%d columns, %d elements, upper %g\n",ncol,nel,up);
double * sol1 = new double[nel];
double * el1 = new double[nel];
int * col1 = new int[nel];
CoinBigIndex * start = new CoinBigIndex [ncol+1];
memset(start,0,ncol*sizeof(CoinBigIndex ));
int * row = new int[nel];
int i;
for (i=0;i<nel;i++) {
x=fscanf(fp,"%d %lg %lg",col1+i,el1+i,sol1+i);
if (x<=0)
throw("bad fscanf");
printf("[%d, e=%g, v=%g] ",col1[i],el1[i],sol1[i]);
start[col1[i]]=1;
row[i]=0;
}
printf("\n");
// Setup
OsiSolverInterface * siP = baseSiP->clone();
double lo=-1.0e30;
double * upper = new double[ncol];
start[ncol]=nel;
int last=0;
for (i=0;i<ncol;i++) {
upper[i]=1.0;
int marked=start[i];
start[i]=last;
if (marked)
last++;
}
siP->loadProblem(ncol,1,start,row,el1,NULL,upper,NULL,&lo,&up);
// use upper for solution
memset(upper,0,ncol*sizeof(double));
for (i=0;i<nel;i++) {
int icol=col1[i];
upper[icol]=sol1[i];
siP->setInteger(icol);
}
siP->setColSolution(upper);
delete [] sol1;
delete [] el1;
delete [] col1;
delete [] start;
delete [] row;
delete [] upper;
CglKnapsackCover kccg;
OsiCuts cuts;
// Test generateCuts method
kccg.generateCuts(*siP,cuts);
// print out and compare to known cuts
int numberCuts = cuts.sizeRowCuts();
if (numberCuts) {
for (i=0;i<numberCuts;i++) {
OsiRowCut * thisCut = cuts.rowCutPtr(i);
int n=thisCut->row().getNumElements();
printf("Cut %d has %d entries, rhs %g %g =>",i,n,thisCut->lb(),
thisCut->ub());
int j;
const int * index = thisCut->row().getIndices();
const double * element = thisCut->row().getElements();
for (j=0;j<n;j++) {
printf(" (%d,%g)",index[j],element[j]);
}
printf("\n");
}
}
fclose(fp);
}
}
// Testcase /u/rlh/osl2/mps/p0201
// Miplib3 problem p0282
// Test that no cuts chop off the optimal ip solution
{
// Setup
OsiSolverInterface * siP = baseSiP->clone();
std::string fn(mpsDir+"p0201");
siP->readMps(fn.c_str(),"mps");
// All integer variables should be binary.
// Assert that this is true.
for ( i = 0; i < siP->getNumCols(); i++ )
if ( siP->isInteger(i) )
assert(siP->getColUpper()[i]==1.0 && siP->isBinary(i));
const int nCols=siP->getNumCols();
CglKnapsackCover kccg;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparisn
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, 6875.) );
double mycs[] =
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.5, 0, 0, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.5,
0, 0, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.5, 0, 0,
0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.5, 0, 0, 0, 0.5,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.5, 0, 0, 0, 0.5, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.5, 0, 0, 0, 0.5, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0.5, 0, 0, 0, 0.5, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0.5, 0, 0, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0.5, 0, 0, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0.5, 0, 0, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1};
siP->setColSolution(mycs);
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
#endif
OsiCuts cuts;
// Test generateCuts method
kccg.generateCuts(*siP,cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
assert( eq(lpRelaxAfter, 7125) );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore < lpRelaxAfter );
// Optimal IP solution to p0201
int objIndices[22] = { 8, 10, 21, 38, 39, 56,
60, 74, 79, 92, 94, 110, 111, 128, 132, 146,
151,164, 166, 182,183, 200 };
CoinPackedVector p0201(22,objIndices,1.0);
// Sanity check
const double * objective=siP->getObjCoefficients();
double ofv =0 ;
int r;
for (r=0; r<nCols; r++){
ofv=ofv + p0201[r]*objective[r];
}
CoinRelFltEq eq;
assert( eq(ofv,7615.0) );
//printf("p0201 optimal ofv = %g\n",ofv);
int nRowCuts = cuts.sizeRowCuts();
OsiRowCut rcut;
CoinPackedVector rpv;
for (i=0; i<nRowCuts; i++){
rcut = cuts.rowCut(i);
rpv = rcut.row();
double p0201Sum = (rpv*p0201).sum();
assert (p0201Sum <= rcut.ub() );
}
delete siP;
}
// see if I get the same covers that N&W get
{
OsiSolverInterface * siP=baseSiP->clone();
std::string fn(mpsDir+"nw460");
siP->readMps(fn.c_str(),"mps");
// All integer variables should be binary.
// Assert that this is true.
for ( i = 0; i < siP->getNumCols(); i++ )
if ( siP->isInteger(i) )
assert(siP->getColUpper()[i]==1.0 && siP->isBinary(i));
CglKnapsackCover kccg;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, -225.68951787852194) );
double mycs[] = {0.7099213482046447, 0, 0.34185802225477174, 1, 1, 0, 1, 1, 0};
siP->setColSolution(mycs);
OsiCuts cuts;
// Test generateCuts method
kccg.generateCuts(*siP,cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
assert( eq(lpRelaxAfter, -176) );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
#ifdef MJS
assert( lpRelaxBefore < lpRelaxAfter );
#endif
int nRowCuts = cuts.sizeRowCuts();
OsiRowCut rcut;
CoinPackedVector rpv;
for (i=0; i<nRowCuts; i++){
rcut = cuts.rowCut(i);
rpv = rcut.row();
int j;
printf("Row cut number %i has rhs = %g\n",i,rcut.ub());
for (j=0; j<rpv.getNumElements(); j++){
printf("index %i, element %g\n", rpv.getIndices()[j], rpv.getElements()[j]);
}
printf("\n");
}
delete siP;
}
// Debugging: try "exmip1.mps"
{
// Setup
OsiSolverInterface * siP = baseSiP->clone();
std::string fn(mpsDir+"exmip1");
siP->readMps(fn.c_str(),"mps");
// All integer variables should be binary.
// Assert that this is true.
for ( i = 0; i < siP->getNumCols(); i++ )
if ( siP->isInteger(i) )
assert(siP->getColUpper()[i]==1.0 && siP->isBinary(i));
CglKnapsackCover kccg;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
assert( eq(lpRelaxBefore, 3.2368421052631575) );
double mycs[] = {2.5, 0, 0, 0.6428571428571429, 0.5, 4, 0, 0.26315789473684253};
siP->setColSolution(mycs);
// Test generateCuts method
OsiCuts cuts;
kccg.generateCuts(*siP,cuts);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
assert( eq(lpRelaxAfter, 3.2368421052631575) );
#ifdef CGL_DEBUG
printf("\n\nOrig LP min=%f\n",lpRelaxBefore);
printf("\n\nFinal LP min=%f\n",lpRelaxAfter);
#endif
assert( lpRelaxBefore <= lpRelaxAfter );
delete siP;
}
#ifdef CGL_DEBUG
// See what findLPMostViolatedMinCover for knapsack with 2 elements does
{
int nCols = 2;
int row = 1;
CoinPackedVector krow;
double e[2] = {5,10};
int ii[2] = {0,1};
krow.setVector(nCols,ii,e);
double b=11;
double xstar[2] = {.2,.9};
CoinPackedVector cover;
CoinPackedVector remainder;
CglKnapsackCover kccg;
kccg.findLPMostViolatedMinCover(nCols, row, krow, b, xstar, cover, remainder);
printf("num in cover = %i\n",cover.getNumElements());
int j;
for (j=0; j<cover.getNumElements(); j++){
printf(" index %i element % g\n", cover.getIndices()[j], cover.getElements()[j]);
}
}
#endif
#ifdef CGL_DEBUG
// see what findLPMostViolatedMinCover does
{
int nCols = 5;
int row = 1;
CoinPackedVector krow;
double e[5] = {1,1,1,1,10};
int ii[5] = {0,1,2,3,4};
krow.setVector(nCols,ii,e);
double b=11;
double xstar[5] = {.9,.9,1,1,.1};
CoinPackedVector cover;
CoinPackedVector remainder;
CglKnapsackCover kccg;
kccg.findLPMostViolatedMinCover(nCols, row, krow, b, xstar, cover, remainder);
printf("num in cover = %i\n",cover.getNumElements());
int j;
for (j=0; j<cover.getNumElements(); j++){
printf(" index %i element % g\n", cover.getIndices()[j], cover.getElements()[j]);
}
}
#endif
}
void ModelScenario(const char * const name )
{
OsiClpSolverInterface *osiClp1 = new OsiClpSolverInterface();
double INF=osiClp1->getInfinity();
// example of direct interfaces for scenario generation
/* Model dimensions */
int nels=44; // ncol=27, nrow=9
/* Sparse matrix data...organized by row */
int mrow[]={ 0, 0, 0, 0, 0,
1, 1, 1, 1,
2, 2, 2,
3, 3, 3, 3, 3,
4, 4, 4, 4,
5, 5, 5, 5, 5, 5,
6, 6, 6, 6, 6,
7, 7, 7, 7, 7, 7,
8, 8, 8, 8, 8, 8 };
int mcol[]={ 0, 1, 2, 3, 4,
5, 6, 7, 8,
9,10, 11,
12, 13, 14, 15, 16,
0, 12, 17, 18,
1, 5, 9, 13, 19, 20,
2, 6, 14, 21, 22,
3, 7, 10, 15, 23, 24,
4, 8, 11, 16, 25, 26 };
double dels[] = { 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, 1.0,
16.0, 9.0, -1.0, 1.0,
15.0, 10.0, 5.0, 11.0, -1.0, 1.0,
28.0, 14.0, 22.0, -1.0, 1.0,
23.0, 15.0, 7.0, 17.0, -1.0, 1.0,
81.0, 57.0, 29.0, 55.0, -1.0, 1.0 };
/* Objective */
double dobj[]={ 18.0, 21.0, 18.0, 16.0, 10.0, 15.0, 16.0, 14.0, 9.0,
10.0, 9.0, 6.0, 17.0, 16.0, 17.0, 15.0, 10.0, 0.0,
13.0, 0.0, 13.0, 0.0, 7.0, 0.0, 7.0, 0.0, 1.0 };
/* Column bounds */
double dclo[]={ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
double dcup[]={ INF, INF, INF, INF, INF, INF, INF, INF, INF,
INF, INF, INF, INF, INF, INF, INF, INF, INF,
INF, INF, INF, INF, INF, INF, INF, INF, INF };
/* Row bounds */
double drlo[]={ -INF, -INF, -INF, -INF, 0.0, 4.0, 0.0, 8.0, 10.0 };
double drup[]={ 10.0, 19.0, 25.0, 15.0, 0.0, 7.0, 0.0, 8.0, 90.0 };
/* Stages */
int nstg=2;
int n_first_stg_rows=4;
int rstg[]={ 0,0,0,0,1,1,1,1,1 };
int cstg[]={ 0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,1,
1,1,1,1,1,1,1,1,1 };
/* Stochastic data */
int nindp=5;
int nsamp[]={ 5, 2, 5, 5, 3 };
double demand[]={ 200, 220, 250, 270, 300,
50, 150,
140, 160, 180, 200, 220,
10, 50, 80, 100, 340,
580, 600, 620 };
double dprobs[]={ 0.2, 0.05, 0.35, 0.2, 0.2,
0.3, 0.7,
0.1, 0.2, 0.4, 0.2, 0.1,
0.2, 0.2, 0.3, 0.2, 0.1,
0.1, 0.8, 0.1 };
/* local variables */
int ns=1,ii,iii,jj,*indx,*incr;
double dp=1.0;
for (ii=0;ii<nindp;ii++) ns *= nsamp[ii]; /* Compute number of scenarios */
// initialize SmiModel
SmiScnModel *smiModel = new SmiScnModel();
smiModel->setOsiSolverHandle(*osiClp1);
// set core model using Osi interface
OsiClpSolverInterface ocsi;
ocsi.loadProblem(CoinPackedMatrix( 1,mrow,mcol,dels,nels),dclo,dcup,dobj,drlo,drup);
SmiCoreData *osiCore = new SmiCoreData(&ocsi,nstg,cstg,rstg);
cout << "ModelScenario: Created CoreData" << endl;
// Coin structures for scenario updates to right hand sides
CoinPackedVector cpv_rlo;
CoinPackedVector cpv_rup;
// initialize right hand side data for first scenario
indx = (int *) malloc( (1+nindp)*sizeof(int) );
memset( indx,0,(1+nindp)*sizeof(int));
for (jj=0;jj<nindp;jj++) {
indx[jj+1] += indx[jj] + nsamp[jj];
dp *= dprobs[ indx[jj] ];
drlo[n_first_stg_rows + jj] = demand[ indx[jj] ];
drup[n_first_stg_rows + jj] = demand[ indx[jj] ];
cpv_rlo.insert(n_first_stg_rows + jj,demand[ indx[jj] ]);
cpv_rup.insert(n_first_stg_rows + jj,demand[ indx[jj] ]);
}
cout << "ModelScenario: Adding " << ns << " scenarios" << endl;
// first scenario
int anc = 0;
int branch = 1;
int is = smiModel->generateScenario(osiCore,NULL,NULL,NULL,NULL,
&cpv_rlo,&cpv_rup,branch,anc,dp);
/***** ...main loop to generate scenarios from discrete random variables
For each scenario index ii:
If the sample size nsamp[jj] divides the scenario index ii,
reverse the increment direction incr[jj]
and increase the random variable index jj by 1.
Increment the jj'th random variable by incr[jj]
and generate new sample data.
***** */
/* sample space increment initialized to 1 */
incr = (int *) malloc( nindp*sizeof(int) );
for (jj=0;jj<nindp;jj++) incr[jj] = 1;
for (int iss=1;iss<ns;iss++) {
iii=iss; jj=0;
while ( !(iii%nsamp[jj]) ) {
iii /= nsamp[jj];
incr[jj] = -incr[jj];
jj++;
}
dp /= dprobs[ indx[jj] ];
indx[jj] += incr[jj];
dp *= dprobs[ indx[jj] ];
// set data
drlo[n_first_stg_rows + jj] = demand[ indx[jj] ];
drup[n_first_stg_rows + jj] = demand[ indx[jj] ];
cpv_rlo.setElement(cpv_rlo.findIndex(n_first_stg_rows + jj),demand[ indx[jj] ]);
cpv_rup.setElement(cpv_rup.findIndex(n_first_stg_rows + jj),demand[ indx[jj] ]);
// genScenario
is = smiModel->generateScenario(osiCore,NULL,NULL,NULL,NULL,
&cpv_rlo,&cpv_rup,branch,anc,dp);
}
assert(ns==smiModel->getNumScenarios());
cout << "ModelScenario: Finished adding scenarios" << endl;
// load problem data into OsiSolver
smiModel->loadOsiSolverData();
// get Osi pointer
OsiSolverInterface *smiOsi = smiModel->getOsiSolverInterface();
// set some parameters
smiOsi->setHintParam(OsiDoPresolveInInitial,true);
smiOsi->setHintParam(OsiDoScale,true);
smiOsi->setHintParam(OsiDoCrash,true);
// solve using Osi Solver
smiOsi->initialSolve();
// test optimal value
assert(fabs(smiOsi->getObjValue()-1566.042)<0.01);
// test solutions
const double *dsoln = smiOsi->getColSolution();
double objSum = 0.0;
/* The canonical way to traverse the tree:
For each scenario, get the leaf node.
Then get the parent. Repeat until parent is NULL.
(Only the root node has a NULL parent.)
*/
for(is=0; is<ns; ++is)
{
/* this loop calculates the scenario objective value */
double scenSum = 0.0;
// start with leaf node
SmiScnNode *node = smiModel->getLeafNode(is);
// leaf node probability is the scenario probability
double scenprob = node->getModelProb();
while (node != NULL)
{
// getColStart returns the starting index of node in OSI model
for(int j=node->getColStart(); j<node->getColStart()+node->getNumCols(); ++j)
{
// getCoreColIndex returns the corresponding Core index
// in the original (user's) ordering
scenSum += dobj[node->getCoreColIndex(j)]*dsoln[j];
}
// get parent of node
node = node->getParent();
}
objSum += scenSum*scenprob;
}
assert(fabs(smiOsi->getObjValue()-objSum) < 0.01);
// print results
printf("Solved stochastic program %s\n", name);
printf("Number of rows: %d\n",smiOsi->getNumRows());
printf("Number of cols: %d\n",smiOsi->getNumCols());
printf("Optimal value: %g\n",smiOsi->getObjValue());
}
void
CglCliqueUnitTest(const OsiSolverInterface *baseSiP,
const std::string mpsDir)
{
// Test default constructor
{
CglClique aGenerator;
}
// Test copy & assignment
{
CglClique rhs;
{
CglClique bGenerator;
CglClique cGenerator(bGenerator);
//rhs=bGenerator;
}
}
// Test get/set methods
{
CglClique getset;
// None to test
}
// Test generateCuts
{
CglClique gct;
OsiSolverInterface *siP = baseSiP->clone();
std::string fn = mpsDir+"l152lav";
std::string fn2 = mpsDir+"l152lav.mps";
FILE *in_f = fopen(fn2.c_str(), "r");
if(in_f == NULL) {
std::cout<<"Can not open file "<<fn2<<std::endl<<"Skip test of CglClique::generateCuts()"<<std::endl;
}
else {
fclose(in_f);
siP->readMps(fn.c_str(),"mps");
siP->initialSolve();
double lpRelax = siP->getObjValue();
OsiCuts cs;
gct.generateCuts(*siP, cs);
int nRowCuts = cs.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" Clique cuts"<<std::endl;
assert(cs.sizeRowCuts() > 0);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cs);
siP->resolve();
double lpRelaxAfter= siP->getObjValue();
std::cout<<"Initial LP value: "<<lpRelax<<std::endl;
std::cout<<"LP value with cuts: "<<lpRelaxAfter<<std::endl;
assert( lpRelax < lpRelaxAfter );
assert(lpRelaxAfter < 4722.1);
}
delete siP;
}
}
void
CglTwomirUnitTest(const OsiSolverInterface *baseSiP,
const std::string mpsDir)
{
// Test default constructor
{
CglTwomir aGenerator;
}
// Test copy & assignment
{
CglTwomir rhs;
{
CglTwomir bGenerator;
CglTwomir cGenerator(bGenerator);
rhs=bGenerator;
}
}
// Test get/set methods
{
CglTwomir getset;
int gtmin = getset.getTmin() + 1;
int gtmax = getset.getTmax() + 1;
getset.setMirScale(gtmin, gtmax);
double gtmin2 = getset.getTmin();
double gtmax2 = getset.getTmax();
assert(gtmin == gtmin2);
assert(gtmax == gtmax2);
int gamax = 2 * getset.getAmax() + 1;
getset.setAMax(gamax);
int gamax2 = getset.getAmax();
assert(gamax == gamax2);
}
// Test generateCuts
{
CglTwomir gct;
OsiSolverInterface *siP = baseSiP->clone();
std::string fn = mpsDir+"capPlan1";
std::string fn2 = mpsDir+"capPlan1.mps";
FILE *in_f = fopen(fn2.c_str(), "r");
if(in_f == NULL) {
std::cout<<"Can not open file "<<fn2<<std::endl<<"Skip test of CglTwomir::generateCuts()"<<std::endl;
}
else {
fclose(in_f);
siP->readMps(fn.c_str(),"mps");
siP->initialSolve();
double lpRelax = siP->getObjValue();
OsiCuts cs;
gct.generateCuts(*siP, cs);
int nRowCuts = cs.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" Twomir cuts"<<std::endl;
assert(cs.sizeRowCuts() > 0);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cs);
siP->resolve();
double lpRelaxAfter= siP->getObjValue();
std::cout<<"Initial LP value: "<<lpRelax<<std::endl;
std::cout<<"LP value with cuts: "<<lpRelaxAfter<<std::endl;
assert( lpRelax < lpRelaxAfter );
assert(lpRelaxAfter < 964);
}
delete siP;
}
}
//--------------------------------------------------------------------------
// ** At present this does not use any solver
void
CglGomoryUnitTest(
const OsiSolverInterface * baseSiP,
const std::string mpsDir )
{
CoinRelFltEq eq(0.000001);
// Test default constructor
{
CglGomory aGenerator;
assert (aGenerator.getLimit()==50);
assert (aGenerator.getAway()==0.05);
}
// Test copy & assignment etc
{
CglGomory rhs;
{
CglGomory bGenerator;
bGenerator.setLimit(99);
bGenerator.setAway(0.2);
CglGomory cGenerator(bGenerator);
rhs=bGenerator;
assert (rhs.getLimit()==99);
assert (rhs.getAway()==0.2);
}
}
// Test explicit form - all integer (pg 125 Wolsey)
if (1) {
OsiCuts osicuts;
CglGomory test1;
int i;
int nOldCuts=0,nRowCuts;
// matrix data
//deliberate hiccup of 2 between 0 and 1
CoinBigIndex start[5]={0,4,7,8,9};
int length[5]={2,3,1,1,1};
int rows[11]={0,2,-1,-1,0,1,2,0,1,2};
double elements[11]={7.0,2.0,1.0e10,1.0e10,-2.0,1.0,-2.0,1,1,1};
CoinPackedMatrix matrix(true,3,5,8,elements,rows,start,length);
// rim data (objective not used just yet)
double rowLower[5]={14.0,3.0,3.0,1.0e10,1.0e10};
double rowUpper[5]={14.0,3.0,3.0,-1.0e10,-1.0e10};
double colLower[7]={0.0,0.0,0.0,0.0,0.0,0.0,0.0};
double colUpper[7]={100.0,100.0,100.0,100.0,100.0,100.0,100.0};
// integer
char intVar[7]={2,2,2,2,2,2,2};
// basis 1
int rowBasis1[3]={-1,-1,-1};
int colBasis1[5]={1,1,-1,-1,1};
CoinWarmStartBasis warm;
warm.setSize(5,3);
for (i=0;i<3;i++) {
if (rowBasis1[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<5;i++) {
if (colBasis1[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 1
double colsol1[5]={20.0/7.0,3.0,0.0,0.0,23.0/7.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol1,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==2);
// cuts always <=
int testCut=0; // test first cut as stronger
double rhs=-6.0;
double testCut1[5]={0.0,0.0,-1.0,-2.0,0.0};
double * cut = testCut1;
double * colsol = colsol1;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==2);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
// explicit slack
matrix.setDimensions(-1,6);
rpv.insert(5,1.0*7.0); // to get cut in book
rowLower[3]=ub;
rowUpper[3]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 2
int rowBasis2[4]={-1,-1,-1,-1};
int colBasis2[6]={1,1,1,1,-1,-1};
warm.setSize(6,4);
for (i=0;i<4;i++) {
if (rowBasis2[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<6;i++) {
if (colBasis2[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 2
double colsol2[6]={2.0,0.5,1.0,2.5,0.0,0.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol2,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts-nOldCuts==2);
// cuts always <=
testCut=0; // test first cut as stronger
rhs=-1.0;
double testCut2[6]={0.0,0.0,0.0,0.0,-1.0,0.0};
cut = testCut2;
colsol = colsol2;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==1);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
// explicit slack
matrix.setDimensions(-1,7);
rpv.insert(6,1.0);
rowLower[4]=ub;
rowUpper[4]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 3
int rowBasis3[5]={-1,-1,-1,-1,-1};
int colBasis3[7]={1,1,1,1,1,-1,-1};
warm.setSize(7,5);
for (i=0;i<5;i++) {
if (rowBasis3[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<7;i++) {
if (colBasis3[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 3
double colsol3[7]={2.0,1.0,2.0,2.0,1.0,0.0,0.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol3,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==nOldCuts);
}
// Test explicit form - this time with x4 flipped
if (1) {
OsiCuts osicuts;
CglGomory test1;
int i;
int nOldCuts=0,nRowCuts;
// matrix data
//deliberate hiccup of 2 between 0 and 1
CoinBigIndex start[5]={0,4,7,8,9};
int length[5]={2,3,1,1,1};
int rows[11]={0,2,-1,-1,0,1,2,0,1,2};
double elements[11]={7.0,2.0,1.0e10,1.0e10,-2.0,1.0,-2.0,1,-1,1};
CoinPackedMatrix matrix(true,3,5,8,elements,rows,start,length);
// rim data (objective not used just yet)
double rowLower[5]={14.0,-5.0,3.0,1.0e10,1.0e10};
double rowUpper[5]={14.0,-5.0,3.0,-1.0e10,-1.0e10};
double colLower[7]={0.0,0.0,0.0,0.0,0.0,0.0,0.0};
double colUpper[7]={100.0,100.0,100.0,8.0,100.0,100.0,100.0};
// integer
char intVar[7]={2,2,2,2,2,2,2};
// basis 1
int rowBasis1[3]={-1,-1,-1};
int colBasis1[5]={1,1,-1,-1,1};
CoinWarmStartBasis warm;
warm.setSize(5,3);
for (i=0;i<3;i++) {
if (rowBasis1[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<5;i++) {
if (colBasis1[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 1
double colsol1[5]={20.0/7.0,3.0,0.0,8.0,23.0/7.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol1,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==2);
// cuts always <=
int testCut=0; // test first cut as stronger
double rhs=10.0;
double testCut1[5]={0.0,0.0,-1.0,2.0,0.0};
double * cut = testCut1;
double * colsol = colsol1;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==2);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
// explicit slack
matrix.setDimensions(-1,6);
rpv.insert(5,1.0*7.0); // to get cut in book
rowLower[3]=ub;
rowUpper[3]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 2
int rowBasis2[4]={-1,-1,-1,-1};
int colBasis2[6]={1,1,1,1,-1,-1};
warm.setSize(6,4);
for (i=0;i<4;i++) {
if (rowBasis2[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<6;i++) {
if (colBasis2[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 2
double colsol2[6]={2.0,0.5,1.0,5.5,0.0,0.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol2,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts-nOldCuts==2);
// cuts always <=
testCut=0; // test first cut as stronger
rhs=-1.0;
double testCut2[6]={0.0,0.0,0.0,0.0,-1.0,0.0};
cut = testCut2;
colsol = colsol2;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==1);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
// explicit slack
matrix.setDimensions(-1,7);
rpv.insert(6,1.0);
rowLower[4]=ub;
rowUpper[4]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 3
int rowBasis3[5]={-1,-1,-1,-1,-1};
int colBasis3[7]={1,1,1,1,1,-1,-1};
warm.setSize(7,5);
for (i=0;i<5;i++) {
if (rowBasis3[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<7;i++) {
if (colBasis3[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 3
double colsol3[7]={2.0,1.0,2.0,6.0,1.0,0.0,0.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol3,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==nOldCuts);
}
// Test with slacks
if (1) {
OsiCuts osicuts;
CglGomory test1;
int i;
int nOldCuts=0,nRowCuts;
// matrix data
//deliberate hiccup of 2 between 0 and 1
CoinBigIndex start[5]={0,4};
int length[5]={2,3};
int rows[11]={0,2,-1,-1,0,1,2};
double elements[11]={7.0,2.0,1.0e10,1.0e10,-2.0,1.0,-2.0};
CoinPackedMatrix matrix(true,3,2,5,elements,rows,start,length);
// rim data (objective not used just yet)
double rowLower[5]={-1.0e10,-1.0e10,-1.0e10,1.0e10,1.0e10};
double rowUpper[5]={14.0,3.0,3.0,-1.0e10,-1.0e10};
double colLower[2]={0.0,0.0};
double colUpper[2]={100.0,100.0};
// integer
char intVar[2]={2,2};
// basis 1
int rowBasis1[3]={-1,-1,1};
int colBasis1[2]={1,1};
CoinWarmStartBasis warm;
warm.setSize(2,3);
for (i=0;i<3;i++) {
if (rowBasis1[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis1[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 1
double colsol1[2]={20.0/7.0,3.0};
test1.generateCuts(NULL, osicuts, matrix,
/* objective,*/ colsol1,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==1);
// cuts always <=
int testCut=0; // test first cut as stronger
double rhs=2.0;
double testCut1[2]={1.0,0.0};
double * cut = testCut1;
double * colsol = colsol1;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==1);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
rowLower[3]=-1.0e100;
rowUpper[3]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 2
int rowBasis2[4]={1,1,-1,-1};
int colBasis2[2]={1,1};
warm.setSize(2,4);
for (i=0;i<4;i++) {
if (rowBasis2[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis2[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 2
double colsol2[2]={2.0,0.5};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol2,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts-nOldCuts==1);
// cuts always <=
testCut=0; // test first cut as stronger
rhs=1.0;
double testCut2[2]={1.0,-1.0};
cut = testCut2;
colsol = colsol2;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==2);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
rowLower[4]=-1.0e100;
rowUpper[4]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 3
int rowBasis3[5]={1,1,1,-1,-1};
int colBasis3[2]={1,1};
warm.setSize(2,5);
for (i=0;i<5;i++) {
if (rowBasis3[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis3[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 3
double colsol3[2]={2.0,1.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol3,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==nOldCuts);
}
// swap some rows to G
if (1) {
OsiCuts osicuts;
CglGomory test1;
int i;
int nOldCuts=0,nRowCuts;
// matrix data
//deliberate hiccup of 2 between 0 and 1
CoinBigIndex start[5]={0,4};
int length[5]={2,3};
int rows[11]={0,2,-1,-1,0,1,2};
double elements[11]={-7.0,-2.0,1.0e10,1.0e10,+2.0,1.0,+2.0};
CoinPackedMatrix matrix(true,3,2,5,elements,rows,start,length);
// rim data (objective not used just yet)
double rowUpper[5]={1.0e10,3.0,1.0e10,-1.0e10,-1.0e10};
double rowLower[5]={-14.0,-1.0e10,-3.0,1.0e10,1.0e10};
double colLower[2]={0.0,0.0};
double colUpper[2]={100.0,100.0};
// integer
char intVar[2]={2,2};
// basis 1
int rowBasis1[3]={-1,-1,1};
int colBasis1[2]={1,1};
CoinWarmStartBasis warm;
warm.setSize(2,3);
for (i=0;i<3;i++) {
if (rowBasis1[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis1[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 1
double colsol1[2]={20.0/7.0,3.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol1,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==1);
// cuts always <=
int testCut=0; // test first cut as stronger
double rhs=2.0;
double testCut1[2]={1.0,0.0};
double * cut = testCut1;
double * colsol = colsol1;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==1);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
rowLower[3]=-1.0e100;
rowUpper[3]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 2
int rowBasis2[4]={1,1,-1,-1};
int colBasis2[2]={1,1};
warm.setSize(2,4);
for (i=0;i<4;i++) {
if (rowBasis2[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis2[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 2
double colsol2[2]={2.0,0.5};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol2,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts-nOldCuts==1);
// cuts always <=
testCut=0; // test first cut as stronger
rhs=1.0;
double testCut2[2]={1.0,-1.0};
cut = testCut2;
colsol = colsol2;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==2);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
rowLower[4]=-1.0e100;
rowUpper[4]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 3
int rowBasis3[5]={1,1,1,-1,-1};
int colBasis3[2]={1,1};
warm.setSize(2,5);
for (i=0;i<5;i++) {
if (rowBasis3[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis3[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 3
double colsol3[2]={2.0,1.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol3,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==nOldCuts);
}
// NOW mixed integer gomory cuts
// Test explicit form - (pg 130 Wolsey)
// Some arrays left same size as previously although not used in full
if (1) {
OsiCuts osicuts;
CglGomory test1;
int i;
int nOldCuts=0,nRowCuts;
// matrix data
//deliberate hiccup of 2 between 0 and 1
CoinBigIndex start[5]={0,4,7,8,9};
int length[5]={2,3,1,1,1};
int rows[11]={0,2,-1,-1,0,1,2,0,1,2};
double elements[11]={7.0,2.0,1.0e10,1.0e10,-2.0,1.0,-2.0,1,1,1};
CoinPackedMatrix matrix(true,3,5,8,elements,rows,start,length);
// rim data (objective not used just yet)
double rowLower[5]={14.0,3.0,3.0,1.0e10,1.0e10};
double rowUpper[5]={14.0,3.0,3.0,-1.0e10,-1.0e10};
double colLower[7]={0.0,0.0,0.0,0.0,0.0,0.0,0.0};
double colUpper[7]={100.0,100.0,100.0,100.0,100.0,100.0,100.0};
// integer
char intVar[7]={2,0,0,0,0,0,0};
// basis 1
int rowBasis1[3]={-1,-1,-1};
int colBasis1[5]={1,1,-1,-1,1};
CoinWarmStartBasis warm;
warm.setSize(5,3);
for (i=0;i<3;i++) {
if (rowBasis1[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<5;i++) {
if (colBasis1[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 1
double colsol1[5]={20.0/7.0,3.0,0.0,0.0,23.0/7.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol1,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==1);
// cuts always <=
int testCut=0; // test first cut as stronger
double rhs=-6.0/7.0;
double testCut1[5]={0.0,0.0,-1.0/7.0,-2.0/7.0,0.0};
double * cut = testCut1;
double * colsol = colsol1;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==2);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
// explicit slack
matrix.setDimensions(-1,6);
rpv.insert(5,1.0); // to get cut in book
rowLower[3]=ub;
rowUpper[3]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 2
int rowBasis2[4]={-1,-1,-1,-1};
int colBasis2[6]={1,1,1,1,-1,-1};
warm.setSize(6,4);
for (i=0;i<4;i++) {
if (rowBasis2[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<6;i++) {
if (colBasis2[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 2
double colsol2[6]={2.0,0.5,1.0,2.5,0.0,0.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol2,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==nOldCuts);
}
// Test explicit form - this time with x4 flipped
if (1) {
OsiCuts osicuts;
CglGomory test1;
int i;
int nOldCuts=0,nRowCuts;
// matrix data
//deliberate hiccup of 2 between 0 and 1
CoinBigIndex start[5]={0,4,7,8,9};
int length[5]={2,3,1,1,1};
int rows[11]={0,2,-1,-1,0,1,2,0,1,2};
double elements[11]={7.0,2.0,1.0e10,1.0e10,-2.0,1.0,-2.0,1,-1,1};
CoinPackedMatrix matrix(true,3,5,8,elements,rows,start,length);
// rim data (objective not used just yet)
double rowLower[5]={14.0,-5.0,3.0,1.0e10,1.0e10};
double rowUpper[5]={14.0,-5.0,3.0,-1.0e10,-1.0e10};
double colLower[7]={0.0,0.0,0.0,0.0,0.0,0.0,0.0};
double colUpper[7]={100.0,100.0,100.0,8.0,100.0,100.0,100.0};
// integer
char intVar[7]={2,0,0,0,0,0,0};
// basis 1
int rowBasis1[3]={-1,-1,-1};
int colBasis1[5]={1,1,-1,-1,1};
CoinWarmStartBasis warm;
warm.setSize(5,3);
for (i=0;i<3;i++) {
if (rowBasis1[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<5;i++) {
if (colBasis1[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 1
double colsol1[5]={20.0/7.0,3.0,0.0,8.0,23.0/7.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol1,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==1);
// cuts always <=
int testCut=0;
double rhs=10.0/7.0;
double testCut1[5]={0.0,0.0,-1.0/7.0,2.0/7.0,0.0};
double * cut = testCut1;
double * colsol = colsol1;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==2);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
// explicit slack
matrix.setDimensions(-1,6);
rpv.insert(5,1.0); // to get cut in book
rowLower[3]=ub;
rowUpper[3]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 2
int rowBasis2[4]={-1,-1,-1,-1};
int colBasis2[6]={1,1,1,1,-1,-1};
warm.setSize(6,4);
for (i=0;i<4;i++) {
if (rowBasis2[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<6;i++) {
if (colBasis2[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 2
double colsol2[6]={2.0,0.5,1.0,5.5,0.0,0.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol2,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==nOldCuts);
}
// Test with slacks
if (1) {
OsiCuts osicuts;
CglGomory test1;
int i;
int nOldCuts=0,nRowCuts;
// matrix data
//deliberate hiccup of 2 between 0 and 1
CoinBigIndex start[5]={0,4};
int length[5]={2,3};
int rows[11]={0,2,-1,-1,0,1,2};
double elements[11]={7.0,2.0,1.0e10,1.0e10,-2.0,1.0,-2.0};
CoinPackedMatrix matrix(true,3,2,5,elements,rows,start,length);
// rim data (objective not used just yet)
double rowLower[5]={-1.0e10,-1.0e10,-1.0e10,1.0e10,1.0e10};
double rowUpper[5]={14.0,3.0,3.0,-1.0e10,-1.0e10};
double colLower[2]={0.0,0.0};
double colUpper[2]={100.0,100.0};
// integer
char intVar[2]={2,0};
// basis 1
int rowBasis1[3]={-1,-1,1};
int colBasis1[2]={1,1};
CoinWarmStartBasis warm;
warm.setSize(2,3);
for (i=0;i<3;i++) {
if (rowBasis1[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis1[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 1
double colsol1[2]={20.0/7.0,3.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol1,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==1);
// cuts always <=
int testCut=0; // test first cut as stronger
double rhs=2.0;
double testCut1[2]={1.0,0.0};
double * cut = testCut1;
double * colsol = colsol1;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==1);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
rowLower[3]=-1.0e100;
rowUpper[3]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 2
int rowBasis2[4]={1,1,-1,-1};
int colBasis2[2]={1,1};
warm.setSize(2,4);
for (i=0;i<4;i++) {
if (rowBasis2[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis2[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 2
double colsol2[2]={2.0,0.5};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol2,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==nOldCuts);
}
// swap some rows to G
if (1) {
OsiCuts osicuts;
CglGomory test1;
int i;
int nOldCuts=0,nRowCuts;
// matrix data
//deliberate hiccup of 2 between 0 and 1
CoinBigIndex start[5]={0,4};
int length[5]={2,3};
int rows[11]={0,2,-1,-1,0,1,2};
double elements[11]={-7.0,-2.0,1.0e10,1.0e10,+2.0,1.0,+2.0};
CoinPackedMatrix matrix(true,3,2,5,elements,rows,start,length);
// rim data (objective not used just yet)
double rowUpper[5]={1.0e10,3.0,1.0e10,-1.0e10,-1.0e10};
double rowLower[5]={-14.0,-1.0e10,-3.0,1.0e10,1.0e10};
double colLower[2]={0.0,0.0};
double colUpper[2]={100.0,100.0};
// integer
char intVar[2]={2,0};
// basis 1
int rowBasis1[3]={-1,-1,1};
int colBasis1[2]={1,1};
CoinWarmStartBasis warm;
warm.setSize(2,3);
for (i=0;i<3;i++) {
if (rowBasis1[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis1[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 1
double colsol1[2]={20.0/7.0,3.0};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol1,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==1);
// cuts always <=
int testCut=0; // test first cut as stronger
double rhs=2.0;
double testCut1[2]={1.0,0.0};
double * cut = testCut1;
double * colsol = colsol1;
for (i=nOldCuts; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
double ub=rcut.ub();
#ifdef CGL_DEBUG
double lb=rcut.lb();
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
#endif
if (i-nOldCuts==testCut) {
assert( eq(rhs,ub));
assert(n==1);
for (k=0; k<n; k++){
int column=indices[k];
assert (eq(cut[column],elements[k]));
}
// add cut
rowLower[3]=-1.0e100;
rowUpper[3]=ub;
matrix.appendRow(rpv);
}
}
nOldCuts=nRowCuts;
// basis 2
int rowBasis2[4]={1,1,-1,-1};
int colBasis2[2]={1,1};
warm.setSize(2,4);
for (i=0;i<4;i++) {
if (rowBasis2[i]<0) {
warm.setArtifStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setArtifStatus(i,CoinWarmStartBasis::basic);
}
}
for (i=0;i<2;i++) {
if (colBasis2[i]<0) {
warm.setStructStatus(i,CoinWarmStartBasis::atLowerBound);
} else {
warm.setStructStatus(i,CoinWarmStartBasis::basic);
}
}
// solution 2
double colsol2[2]={2.0,0.5};
test1.generateCuts(NULL, osicuts, matrix,
/*objective,*/ colsol2,
colLower, colUpper,
rowLower, rowUpper, intVar, &warm);
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" gomory cuts"<<std::endl;
assert (nRowCuts==nOldCuts);
}
// Miplib3 problem p0033
if (1) {
// Setup
OsiSolverInterface * siP = baseSiP->clone();
std::string fn(mpsDir+"p0033");
siP->readMps(fn.c_str(),"mps");
siP->activateRowCutDebugger("p0033");
CglGomory test;
// Solve the LP relaxation of the model and
// print out ofv for sake of comparison
siP->initialSolve();
double lpRelaxBefore=siP->getObjValue();
std::cout<<"Initial LP value: "<<lpRelaxBefore<<std::endl;
assert( eq(lpRelaxBefore, 2520.5717391304347) );
// Fails with OsiCpx, OsiXpr:
/**********
double mycs[] = {0, 1, 0, 0, -2.0837010502455788e-19, 1, 0, 0, 1,
0.021739130434782594, 0.35652173913043478,
-6.7220534694101275e-18, 5.3125906451789717e-18,
1, 0, 1.9298798670241979e-17, 0, 0, 0,
7.8875708048320448e-18, 0.5, 0,
0.85999999999999999, 1, 1, 0.57999999999999996,
1, 0, 1, 0, 0.25, 0, 0.67500000000000004};
siP->setColSolution(mycs);
****/
OsiCuts cuts;
// Test generateCuts method
test.generateCuts(*siP,cuts);
int nRowCuts = cuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" Gomory cuts"<<std::endl;
assert(cuts.sizeRowCuts() > 0);
OsiSolverInterface::ApplyCutsReturnCode rc = siP->applyCuts(cuts);
siP->resolve();
double lpRelaxAfter=siP->getObjValue();
std::cout<<"LP value with cuts: "<<lpRelaxAfter<<std::endl;
//assert( eq(lpRelaxAfter, 2592.1908295194507) );
assert( lpRelaxAfter> 2550.0 );
assert( lpRelaxBefore < lpRelaxAfter );
assert(lpRelaxAfter < 3089.1);
delete siP;
}
}
//-----------------------------------------------------------------------------
// 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;
}
//--------------------------------------------------------------------------
// test EKKsolution methods.
void
CglProbingUnitTest(
const OsiSolverInterface * baseSiP,
const std::string mpsDir )
{
# ifdef CGL_DEBUG
int i ; // define just once
# endif
CoinRelFltEq eq(0.000001);
// Test default constructor
{
CglProbing aGenerator;
}
// Test copy & assignment
{
CglProbing rhs;
{
CglProbing bGenerator;
CglProbing cGenerator(bGenerator);
rhs=bGenerator;
}
}
{
OsiCuts osicuts;
CglProbing test1;
OsiSolverInterface * siP = baseSiP->clone();
int nColCuts;
int nRowCuts;
std::string fn = mpsDir+"p0033";
siP->readMps(fn.c_str(),"mps");
siP->initialSolve();
// just unsatisfied variables
test1.generateCuts(*siP,osicuts);
nColCuts = osicuts.sizeColCuts();
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" probing cuts"<<std::endl;
{
std::cout<<"there are "<<nColCuts<<" probing column cuts"<<std::endl;
#ifdef CGL_DEBUG
const double * lo = siP->getColLower();
const double * up = siP->getColUpper();
for (i=0; i<nColCuts; i++){
OsiColCut ccut;
CoinPackedVector cpv;
ccut = osicuts.colCut(i);
cpv = ccut.lbs();
int n = cpv.getNumElements();
int j;
const int * indices = cpv.getIndices();
double* elements = cpv.getElements();
for (j=0;j<n;j++) {
int icol=indices[j];
if (elements[j]>lo[icol])
std::cout<<"Can increase lb on "<<icol<<" from "<<lo[icol]<<
" to "<<elements[j]<<std::endl;
}
cpv = ccut.ubs();
n = cpv.getNumElements();
indices = cpv.getIndices();
elements = cpv.getElements();
for (j=0;j<n;j++) {
int icol=indices[j];
if (elements[j]<up[icol])
std::cout<<"Can decrease ub on "<<icol<<" from "<<up[icol]<<
" to "<<elements[j]<<std::endl;
}
}
#endif
}
#ifdef CGL_DEBUG
for (i=0; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
const double * colsol = siP->getColSolution();
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
double lb=rcut.lb();
double ub=rcut.ub();
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
}
#endif
if (nRowCuts==1) {
CoinPackedVector check;
int index[] = {6,32};
double el[] = {1,1};
check.setVector(2,index,el);
// sort Elements in increasing order
CoinPackedVector rpv=osicuts.rowCut(0).row();
assert (rpv.getNumElements()==2);
rpv.sortIncrIndex();
assert (check==rpv);
assert (osicuts.rowCut(0).lb()==1.0);
}
// now all variables
osicuts=OsiCuts();
test1.setMode(2);
test1.setRowCuts(3);
test1.generateCuts(*siP,osicuts);
nColCuts = osicuts.sizeColCuts();
nRowCuts = osicuts.sizeRowCuts();
std::cout<<"There are "<<nRowCuts<<" probing cuts"<<std::endl;
{
std::cout<<"there are "<<nColCuts<<" probing column cuts"<<std::endl;
#ifdef CGL_DEBUG
const double * lo = siP->getColLower();
const double * up = siP->getColUpper();
for (i=0; i<nColCuts; i++){
OsiColCut ccut;
CoinPackedVector cpv;
ccut = osicuts.colCut(i);
cpv = ccut.lbs();
int n = cpv.getNumElements();
int j;
const int * indices = cpv.getIndices();
double* elements = cpv.getElements();
for (j=0;j<n;j++) {
int icol=indices[j];
if (elements[j]>lo[icol])
std::cout<<"Can increase lb on "<<icol<<" from "<<lo[icol]<<
" to "<<elements[j]<<std::endl;
}
cpv = ccut.ubs();
n = cpv.getNumElements();
indices = cpv.getIndices();
elements = cpv.getElements();
for (j=0;j<n;j++) {
int icol=indices[j];
if (elements[j]<up[icol])
std::cout<<"Can decrease ub on "<<icol<<" from "<<up[icol]<<
" to "<<elements[j]<<std::endl;
}
}
#endif
}
#ifdef CGL_DEBUG
for (i=0; i<nRowCuts; i++){
OsiRowCut rcut;
CoinPackedVector rpv;
const double * colsol = siP->getColSolution();
rcut = osicuts.rowCut(i);
rpv = rcut.row();
const int n = rpv.getNumElements();
const int * indices = rpv.getIndices();
double* elements = rpv.getElements();
double sum2=0.0;
int k=0;
double lb=rcut.lb();
double ub=rcut.ub();
for (k=0; k<n; k++){
int column=indices[k];
sum2 += colsol[column]*elements[k];
}
if (sum2 >ub + 1.0e-7 ||sum2 < lb - 1.0e-7) {
std::cout<<"Cut "<<i<<" lb "<<lb<<" solution "<<sum2<<" ub "<<ub<<std::endl;
for (k=0; k<n; k++){
int column=indices[k];
std::cout<<"(col="<<column<<",el="<<elements[k]<<",sol="<<
colsol[column]<<") ";
}
std::cout <<std::endl;
}
}
#endif
assert (osicuts.sizeRowCuts()>=4);
delete siP;
}
}
int main( int argc, char **argv )
{
if ( argc < 2 )
{
printf("Invalid number of parameters!\n");
exit( EXIT_FAILURE );
}
char problemName[ 256 ];
getFileName( problemName, argv[1] );
clock_t start = clock();
OsiClpSolverInterface *realSolver = new OsiClpSolverInterface();
realSolver->getModelPtr()->setPerturbation(50); /* makes CLP faster for hard instances */
OsiSolverInterface *solver = (OsiSolverInterface*) realSolver;
parseParameters( argc, argv );
readLP( solver, argv[1] );
FILE *log = NULL;
if(!output.empty())
{
log = fopen(output.c_str(), "a");
if(!log)
{
printf("Could not open the file!\n");
exit(EXIT_FAILURE);
}
}
const int numCols = solver->getNumCols(), numRows = solver->getNumRows();
int pass = 0, newCuts = 0, totalCuts = 0;
double pTime, opt, cgTime;
CGraph *cgraph = NULL;
if(sepMethod == Npsep)
cgraph = build_cgraph_osi( solver );
if(!optFile.empty())
{
getOptimals();
if(optimals.find(problemName) == optimals.end())
{
fprintf(stderr, "ERROR: optimal value not found!\n");
exit(EXIT_FAILURE);
}
opt = optimals[problemName];
}
solver->initialSolve();
if (!solver->isProvenOptimal())
{
if (solver->isAbandoned())
{
fprintf( stderr, "LP solver abandoned due to numerical dificulties.\n" );
exit( EXIT_FAILURE );
}
if (solver->isProvenPrimalInfeasible())
{
fprintf( stderr, "LP solver says PRIMAL INFEASIBLE.\n" );
exit( EXIT_FAILURE );
}
if (solver->isProvenDualInfeasible())
{
fprintf( stderr, "LP solver says DUAL INFEASIBLE.\n" );
exit( EXIT_FAILURE );
}
if (solver->isPrimalObjectiveLimitReached())
{
fprintf( stderr, "LP solver says isPrimalObjectiveLimitReached.\n" );
exit( EXIT_FAILURE );
}
if (solver->isDualObjectiveLimitReached())
{
fprintf( stderr, "LP solver says isDualObjectiveLimitReached.\n" );
exit( EXIT_FAILURE );
}
if (solver->isIterationLimitReached())
{
fprintf( stderr, "LP solver says isIterationLimitReached.\n" );
exit( EXIT_FAILURE );
}
fprintf( stderr, "ERROR: Could not solve LP relaxation to optimality. Checking status...\n" );
exit( EXIT_FAILURE );
}
double initialBound = solver->getObjValue();
printf("%.2lf %d %d %.7lf", ((double)(clock()-start)) / ((double)CLOCKS_PER_SEC), pass, 0, solver->getObjValue());
if(!optFile.empty())
{
printf(" %.7lf %.7lf", opt, abs_mip_gap(solver->getObjValue(), opt));
}
printf("\n");
do
{
clock_t startSep = clock();
newCuts = 0;
switch (sepMethod)
{
case Npsep:
{
CglEClique cliqueGen;
OsiCuts cuts;
CglTreeInfo info;
info.level = 0;
info.pass = 1;
vector<string> varNames = getVarNames(solver->getColNames(), numCols);
cliqueGen.parseParameters( argc, (const char**)argv );
cliqueGen.setCGraph( cgraph );
cliqueGen.setGenOddHoles( true ); //allow (or not) inserting odd hole cuts
cliqueGen.colNames = &varNames;
cliqueGen.generateCuts( *solver, cuts, info );
newCuts = cuts.sizeCuts();
solver->applyCuts( cuts );
}
break;
case CglSepM:
{
CglClique cliqueGen;
OsiCuts cuts;
CglTreeInfo info;
info.level = 0;
info.pass = 1;
cliqueGen.setMinViolation( MIN_VIOLATION );
cliqueGen.setStarCliqueReport(false);
cliqueGen.setRowCliqueReport(false);
cliqueGen.generateCuts( *solver, cuts, info );
newCuts = cuts.sizeCuts();
solver->applyCuts( cuts );
}
break;
Default:
{
fprintf( stderr, "Separation Method does not recognized!\n" );
exit( EXIT_FAILURE );
}
}
pTime = ((double)(clock()-start)) / ((double)CLOCKS_PER_SEC);
if(pTime > MAX_TIME) break;
totalCuts += newCuts;
++pass;
if (newCuts)
{
solver->resolve();
if (!solver->isProvenOptimal())
{
if (solver->isAbandoned())
{
fprintf( stderr, "LP solver abandoned due to numerical dificulties.\n" );
exit( EXIT_FAILURE );
}
if (solver->isProvenPrimalInfeasible())
{
fprintf( stderr, "LP solver says PRIMAL INFEASIBLE.\n" );
exit( EXIT_FAILURE );
}
if (solver->isProvenDualInfeasible())
{
fprintf( stderr, "LP solver says DUAL INFEASIBLE.\n" );
exit( EXIT_FAILURE );
}
if (solver->isPrimalObjectiveLimitReached())
{
fprintf( stderr, "LP solver says isPrimalObjectiveLimitReached.\n" );
exit( EXIT_FAILURE );
}
if (solver->isDualObjectiveLimitReached())
{
fprintf( stderr, "LP solver says isDualObjectiveLimitReached.\n" );
exit( EXIT_FAILURE );
}
if (solver->isIterationLimitReached())
{
fprintf( stderr, "LP solver says isIterationLimitReached.\n" );
exit( EXIT_FAILURE );
}
fprintf( stderr, "ERROR: Could not solve LP relaxation. Exiting.\n" );
exit( EXIT_FAILURE );
}
pTime = ((double)(clock()-start)) / ((double)CLOCKS_PER_SEC);
if(pTime > MAX_TIME) break;
double sepTime = ((double)(clock()-startSep)) / ((double)CLOCKS_PER_SEC);
printf("%.2lf %d %d %.7lf", sepTime, pass, newCuts, solver->getObjValue());
if(!optFile.empty())
printf(" %.7lf %.7lf", opt, abs_mip_gap(solver->getObjValue(), opt));
printf("\n");
}
}
while ( (newCuts>0) && (pass<MAX_PASSES) ) ;
if(log)
{
double totalTime = ((double)(clock()-start)) / ((double)CLOCKS_PER_SEC);
fprintf(log, "%s %.2lf %d %d %.7lf", problemName, totalTime, pass - 1, totalCuts, solver->getObjValue());
if(!optFile.empty())
fprintf(log, " %.7lf", abs_mip_gap(solver->getObjValue(), opt));
fprintf(log, "\n");
}
if(cgraph)
cgraph_free( &cgraph );
delete realSolver;
return EXIT_SUCCESS;
}
int
CbcHeuristicNaive::solution(double & solutionValue,
double * betterSolution)
{
numCouldRun_++;
// See if to do
bool atRoot = model_->getNodeCount() == 0;
int passNumber = model_->getCurrentPassNumber();
if (!when() || (when() == 1 && model_->phase() != 1) || !atRoot || passNumber != 1)
return 0; // switched off
// Don't do if it was this heuristic which found solution!
if (this == model_->lastHeuristic())
return 0;
numRuns_++;
double cutoff;
model_->solver()->getDblParam(OsiDualObjectiveLimit, cutoff);
double direction = model_->solver()->getObjSense();
cutoff *= direction;
cutoff = CoinMin(cutoff, solutionValue);
OsiSolverInterface * solver = model_->continuousSolver();
if (!solver)
solver = model_->solver();
const double * colLower = solver->getColLower();
const double * colUpper = solver->getColUpper();
const double * objective = solver->getObjCoefficients();
int numberColumns = model_->getNumCols();
int numberIntegers = model_->numberIntegers();
const int * integerVariable = model_->integerVariable();
int i;
bool solutionFound = false;
CoinWarmStartBasis saveBasis;
CoinWarmStartBasis * basis =
dynamic_cast<CoinWarmStartBasis *>(solver->getWarmStart()) ;
if (basis) {
saveBasis = * basis;
delete basis;
}
// First just fix all integers as close to zero as possible
OsiSolverInterface * newSolver = cloneBut(7); // wassolver->clone();
for (i = 0; i < numberIntegers; i++) {
int iColumn = integerVariable[i];
double lower = colLower[iColumn];
double upper = colUpper[iColumn];
double value;
if (lower > 0.0)
value = lower;
else if (upper < 0.0)
value = upper;
else
value = 0.0;
newSolver->setColLower(iColumn, value);
newSolver->setColUpper(iColumn, value);
}
newSolver->initialSolve();
if (newSolver->isProvenOptimal()) {
double solValue = newSolver->getObjValue() * direction ;
if (solValue < cutoff) {
// we have a solution
solutionFound = true;
solutionValue = solValue;
memcpy(betterSolution, newSolver->getColSolution(),
numberColumns*sizeof(double));
COIN_DETAIL_PRINT(printf("Naive fixing close to zero gave solution of %g\n", solutionValue));
cutoff = solValue - model_->getCutoffIncrement();
}
}
// Now fix all integers as close to zero if zero or large cost
int nFix = 0;
for (i = 0; i < numberIntegers; i++) {
int iColumn = integerVariable[i];
double lower = colLower[iColumn];
double upper = colUpper[iColumn];
double value;
if (fabs(objective[i]) > 0.0 && fabs(objective[i]) < large_) {
nFix++;
if (lower > 0.0)
value = lower;
else if (upper < 0.0)
value = upper;
else
value = 0.0;
newSolver->setColLower(iColumn, value);
newSolver->setColUpper(iColumn, value);
} else {
// set back to original
newSolver->setColLower(iColumn, lower);
newSolver->setColUpper(iColumn, upper);
}
}
const double * solution = solver->getColSolution();
if (nFix) {
newSolver->setWarmStart(&saveBasis);
newSolver->setColSolution(solution);
newSolver->initialSolve();
if (newSolver->isProvenOptimal()) {
double solValue = newSolver->getObjValue() * direction ;
if (solValue < cutoff) {
// try branch and bound
double * newSolution = new double [numberColumns];
COIN_DETAIL_PRINT(printf("%d fixed after fixing costs\n", nFix));
int returnCode = smallBranchAndBound(newSolver,
numberNodes_, newSolution,
solutionValue,
solutionValue, "CbcHeuristicNaive1");
if (returnCode < 0)
returnCode = 0; // returned on size
if ((returnCode&2) != 0) {
// could add cut
returnCode &= ~2;
}
if (returnCode == 1) {
// solution
solutionFound = true;
memcpy(betterSolution, newSolution,
numberColumns*sizeof(double));
COIN_DETAIL_PRINT(printf("Naive fixing zeros gave solution of %g\n", solutionValue));
cutoff = solutionValue - model_->getCutoffIncrement();
}
delete [] newSolution;
}
}
}
#if 1
newSolver->setObjSense(-direction); // maximize
newSolver->setWarmStart(&saveBasis);
newSolver->setColSolution(solution);
for (int iColumn = 0; iColumn < numberColumns; iColumn++) {
double value = solution[iColumn];
double lower = colLower[iColumn];
double upper = colUpper[iColumn];
double newLower;
double newUpper;
if (newSolver->isInteger(iColumn)) {
newLower = CoinMax(lower, floor(value) - 2.0);
newUpper = CoinMin(upper, ceil(value) + 2.0);
} else {
newLower = CoinMax(lower, value - 1.0e5);
newUpper = CoinMin(upper, value + 1.0e-5);
}
newSolver->setColLower(iColumn, newLower);
newSolver->setColUpper(iColumn, newUpper);
}
newSolver->initialSolve();
if (newSolver->isProvenOptimal()) {
double solValue = newSolver->getObjValue() * direction ;
if (solValue < cutoff) {
nFix = 0;
newSolver->setObjSense(direction); // correct direction
//const double * thisSolution = newSolver->getColSolution();
for (int iColumn = 0; iColumn < numberColumns; iColumn++) {
double value = solution[iColumn];
double lower = colLower[iColumn];
double upper = colUpper[iColumn];
double newLower = lower;
double newUpper = upper;
if (newSolver->isInteger(iColumn)) {
if (value < lower + 1.0e-6) {
nFix++;
newUpper = lower;
} else if (value > upper - 1.0e-6) {
nFix++;
newLower = upper;
} else {
newLower = CoinMax(lower, floor(value) - 2.0);
newUpper = CoinMin(upper, ceil(value) + 2.0);
}
}
newSolver->setColLower(iColumn, newLower);
newSolver->setColUpper(iColumn, newUpper);
}
// try branch and bound
double * newSolution = new double [numberColumns];
COIN_DETAIL_PRINT(printf("%d fixed after maximizing\n", nFix));
int returnCode = smallBranchAndBound(newSolver,
numberNodes_, newSolution,
solutionValue,
solutionValue, "CbcHeuristicNaive1");
if (returnCode < 0)
returnCode = 0; // returned on size
if ((returnCode&2) != 0) {
// could add cut
returnCode &= ~2;
}
if (returnCode == 1) {
// solution
solutionFound = true;
memcpy(betterSolution, newSolution,
numberColumns*sizeof(double));
COIN_DETAIL_PRINT(printf("Naive maximizing gave solution of %g\n", solutionValue));
cutoff = solutionValue - model_->getCutoffIncrement();
}
delete [] newSolution;
}
}
#endif
delete newSolver;
return solutionFound ? 1 : 0;
}
