C++ OsiClpSolverInterface::getNumRows方法代码示例

/*
  Randomized Rounding Heuristic
  Returns 1 if solution, 0 if not
*/
int
CbcHeuristicRandRound::solution(double & solutionValue,
                                double * betterSolution)
{
    // rlh: Todo: Memory Cleanup

    //  std::cout << "Entering the Randomized Rounding Heuristic" << std::endl;

    setWhen(1);  // setWhen(1) didn't have the effect I expected (e.g., run once).

    // Run only once.
    //
    //    See if at root node
    bool atRoot = model_->getNodeCount() == 0;
    int passNumber = model_->getCurrentPassNumber();
    //    Just do once
    if (!atRoot || passNumber > 1) {
        // std::cout << "Leaving the Randomized Rounding Heuristic" << std::endl;
        return 0;
    }

    std::cout << "Entering the Randomized Rounding Heuristic" << std::endl;
    typedef struct {
        int numberSolutions;
        int maximumSolutions;
        int numberColumns;
        double ** solution;
        int * numberUnsatisfied;
    } clpSolution;

    double start = CoinCpuTime();
    numCouldRun_++; //
#ifdef HEURISTIC_INFORM
    printf("Entering heuristic %s - nRuns %d numCould %d when %d\n",
	   heuristicName(),numRuns_,numCouldRun_,when_);
#endif
    // Todo: Ask JJHF what "number of times
    // the heuristic could run" means.

    OsiSolverInterface * solver = model_->solver()->clone();
    double primalTolerance ;
    solver->getDblParam(OsiPrimalTolerance, primalTolerance) ;
    OsiClpSolverInterface * clpSolver = dynamic_cast<OsiClpSolverInterface *> (solver);
    assert (clpSolver);
    ClpSimplex * simplex = clpSolver->getModelPtr();

    // Initialize the structure holding the solutions for the Simplex iterations
    clpSolution solutions;
    // Set typeStruct field of ClpTrustedData struct to 1 to indicate
    // desired behavior for  RandRound heuristic (which is what?)
    ClpTrustedData trustedSolutions;
    trustedSolutions.typeStruct = 1;
    trustedSolutions.data = &solutions;
    solutions.numberSolutions = 0;
    solutions.maximumSolutions = 0;
    solutions.numberColumns = simplex->numberColumns();
    solutions.solution = NULL;
    solutions.numberUnsatisfied = NULL;
    simplex->setTrustedUserPointer(&trustedSolutions);

    // Solve from all slack to get some points
    simplex->allSlackBasis();

    // Calling primal() invalidates pointers to some rim vectors,
    // like...row sense (!)
    simplex->primal();

    // 1. Okay - so a workaround would be to copy the data I want BEFORE
    // calling primal.
    // 2. Another approach is to ask the simplex solvers NOT to mess up my
    // rims.
    // 3. See freeCachedResults() for what is getting
    // deleted. Everything else points into the structure.
    // ...or use collower and colupper rather than rowsense.
    // ..store address of where one of these

    // Store the basic problem information
    // -Get the number of columns, rows and rhs vector
    int numCols = clpSolver->getNumCols();
    int numRows = clpSolver->getNumRows();

    // Find the integer variables (use columnType(?))
    // One if not continuous, that is binary or general integer)
    // columnType() = 0 continuous
    //              = 1 binary
    //              = 2 general integer
    bool * varClassInt = new bool[numCols];
    const char* columnType = clpSolver->columnType();
    int numGenInt = 0;
    for (int i = 0; i < numCols; i++) {
        if (clpSolver->isContinuous(i))
            varClassInt[i] = 0;
        else
            varClassInt[i] = 1;
        if (columnType[i] == 2) numGenInt++;
    }
//.........这里部分代码省略.........

//.........这里部分代码省略.........
  CglRedSplit generator4;
  // try larger limit
  generator4.setLimit(200);

  CglClique generator5;
  generator5.setStarCliqueReport(false);
  generator5.setRowCliqueReport(false);

  CglMixedIntegerRounding2 mixedGen;
  CglFlowCover flowGen;
  
  // Add in generators
  // Experiment with -1 and -99 etc
  model.addCutGenerator(&generator1,-1,"Probing");
  model.addCutGenerator(&generator2,-1,"Gomory");
  model.addCutGenerator(&generator3,-1,"Knapsack");
  // model.addCutGenerator(&generator4,-1,"RedSplit");
  model.addCutGenerator(&generator5,-1,"Clique");
  model.addCutGenerator(&flowGen,-1,"FlowCover");
  model.addCutGenerator(&mixedGen,-1,"MixedIntegerRounding");
  // Say we want timings
  int numberGenerators = model.numberCutGenerators();
  int iGenerator;
  for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
    CbcCutGenerator * generator = model.cutGenerator(iGenerator);
    generator->setTiming(true);
  }
  OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (model.solver());
  // go faster stripes
  if (osiclp) {
    // Turn this off if you get problems
    // Used to be automatically set
    osiclp->setSpecialOptions(128);
    if(osiclp->getNumRows()<300&&osiclp->getNumCols()<500) {
      //osiclp->setupForRepeatedUse(2,0);
      osiclp->setupForRepeatedUse(0,0);
    }
  } 
  // Uncommenting this should switch off all CBC messages
  // model.messagesPointer()->setDetailMessages(10,10000,NULL);
  // Allow rounding heuristic

  CbcRounding heuristic1(model);
  model.addHeuristic(&heuristic1);

  // And local search when new solution found

  CbcHeuristicLocal heuristic2(model);
  model.addHeuristic(&heuristic2);

  // Redundant definition of default branching (as Default == User)
  CbcBranchUserDecision branch;
  model.setBranchingMethod(&branch);

  // Definition of node choice
  CbcCompareUser compare;
  model.setNodeComparison(compare);

  // Do initial solve to continuous
  model.initialSolve();

  // Could tune more
  double objValue = model.solver()->getObjSense()*model.solver()->getObjValue();
  double minimumDropA=CoinMin(1.0,fabs(objValue)*1.0e-3+1.0e-4);
  double minimumDrop= fabs(objValue)*1.0e-4+1.0e-4;
  printf("min drop %g (A %g)\n",minimumDrop,minimumDropA);

//.........这里部分代码省略.........

  CglGomory generator2;
  // try larger limit
  generator2.setLimit(300);

  CglKnapsackCover generator3;

  CglRedSplit generator4;
  // try larger limit
  generator4.setLimit(200);

  CglClique generator5;
  generator5.setStarCliqueReport(false);
  generator5.setRowCliqueReport(false);

  CglMixedIntegerRounding2 mixedGen;
  CglFlowCover flowGen;
  
  // Add in generators
  // Experiment with -1 and -99 etc
  model.addCutGenerator(&generator1,-1,"Probing");
  model.addCutGenerator(&generator2,-1,"Gomory");
  model.addCutGenerator(&generator3,-1,"Knapsack");
  // model.addCutGenerator(&generator4,-1,"RedSplit");
  model.addCutGenerator(&generator5,-1,"Clique");
  model.addCutGenerator(&flowGen,-1,"FlowCover");
  model.addCutGenerator(&mixedGen,-1,"MixedIntegerRounding");
  OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (model.solver());
  // go faster stripes
  if (osiclp) {
    // Turn this off if you get problems
    // Used to be automatically set
    osiclp->setSpecialOptions(128);
    if(osiclp->getNumRows()<300&&osiclp->getNumCols()<500) {
      //osiclp->setupForRepeatedUse(2,1);
      osiclp->setupForRepeatedUse(0,1);
    }
  } 
  // Uncommenting this should switch off most CBC messages
  //model.messagesPointer()->setDetailMessages(10,5,5000);
  // Allow rounding heuristic

  CbcRounding heuristic1(model);
  model.addHeuristic(&heuristic1);

  // And local search when new solution found

  CbcHeuristicLocal heuristic2(model);
  model.addHeuristic(&heuristic2);

  // Redundant definition of default branching (as Default == User)
  CbcBranchUserDecision branch;
  model.setBranchingMethod(&branch);

  // Definition of node choice
  CbcCompareUser compare;
  model.setNodeComparison(compare);

  // Do initial solve to continuous
  model.initialSolve();

  // Could tune more
  double objValue = model.solver()->getObjSense()*model.solver()->getObjValue();
  double minimumDropA=CoinMin(1.0,fabs(objValue)*1.0e-3+1.0e-4);
  double minimumDrop= fabs(objValue)*1.0e-4+1.0e-4;
  printf("min drop %g (A %g)\n",minimumDrop,minimumDropA);

//.........这里部分代码省略.........
  //generator1.createCliques(*model.solver(),2,1000,true);
  //generator1.setMode(0);

  CglGomory generator2;
  // try larger limit
  generator2.setLimit(300);

  CglKnapsackCover generator3;

  CglOddHole generator4;
  generator4.setMinimumViolation(0.005);
  generator4.setMinimumViolationPer(0.00002);
  // try larger limit
  generator4.setMaximumEntries(200);

  CglClique generator5;
  generator5.setStarCliqueReport(false);
  generator5.setRowCliqueReport(false);

  CglMixedIntegerRounding mixedGen;
  CglFlowCover flowGen;
  
  // Add in generators
  model.addCutGenerator(&generator1,-1,"Probing");
  model.addCutGenerator(&generator2,-1,"Gomory");
  model.addCutGenerator(&generator3,-1,"Knapsack");
  model.addCutGenerator(&generator4,-1,"OddHole");
  model.addCutGenerator(&generator5,-1,"Clique");
  model.addCutGenerator(&flowGen,-1,"FlowCover");
  model.addCutGenerator(&mixedGen,-1,"MixedIntegerRounding");

  OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (model.solver());
  // go faster stripes
  if (osiclp->getNumRows()<300&&osiclp->getNumCols()<500) {
    osiclp->setupForRepeatedUse(2,0);
    printf("trying slightly less reliable but faster version (? Gomory cuts okay?)\n");
    printf("may not be safe if doing cuts in tree which need accuracy (level 2 anyway)\n");
  }

  // Allow rounding heuristic

  CbcRounding heuristic1(model);
  model.addHeuristic(&heuristic1);

  // And local search when new solution found

  CbcHeuristicLocal heuristic2(model);
  model.addHeuristic(&heuristic2);

  // Redundant definition of default branching (as Default == User)
  CbcBranchUserDecision branch;
  model.setBranchingMethod(&branch);

  // Definition of node choice
  CbcCompareUser compare;
  model.setNodeComparison(compare);

  // Do initial solve to continuous
  model.initialSolve();

  // Could tune more
  model.setMinimumDrop(CoinMin(1.0,
			     fabs(model.getMinimizationObjValue())*1.0e-3+1.0e-4));

  if (model.getNumCols()<500)
    model.setMaximumCutPassesAtRoot(-100); // always do 100 if possible

int main (int argc, const char *argv[])
{

  // Define your favorite OsiSolver
  
  OsiClpSolverInterface solver1;

  // Read in model using argv[1]
  // and assert that it is a clean model
  std::string mpsFileName;
#if defined(SAMPLEDIR)
  mpsFileName = SAMPLEDIR "/p0033.mps";
#else
  if (argc < 2) {
    fprintf(stderr, "Do not know where to find sample MPS files.\n");
    exit(1);
  }
#endif
  if (argc>=2) mpsFileName = argv[1];
  int numMpsReadErrors = solver1.readMps(mpsFileName.c_str(),"");
  assert(numMpsReadErrors==0);
  double time1 = CoinCpuTime();
  OsiClpSolverInterface solverSave = solver1;

  /* Options are:
     preprocess to do preprocessing
     time in minutes
     if 2 parameters and numeric taken as time
  */
  bool preProcess=false;
  double minutes=-1.0;
  int nGoodParam=0;
  for (int iParam=2; iParam<argc;iParam++) {
    if (!strcmp(argv[iParam],"preprocess")) {
      preProcess=true;
      nGoodParam++;
    } else if (!strcmp(argv[iParam],"time")) {
      if (iParam+1<argc&&isdigit(argv[iParam+1][0])) {
        minutes=atof(argv[iParam+1]);
        if (minutes>=0.0) {
          nGoodParam+=2;
          iParam++; // skip time
        }
      }
    }
  }
  if (nGoodParam==0&&argc==3&&isdigit(argv[2][0])) {
    // If time is given then stop after that number of minutes
    minutes = atof(argv[2]);
    if (minutes>=0.0) 
      nGoodParam=1;
  }
  if (nGoodParam!=argc-2&&argc>=2) {
    printf("Usage <file> [preprocess] [time <minutes>] or <file> <minutes>\n");
    exit(1);
  }
  // Reduce printout
  solver1.setHintParam(OsiDoReducePrint,true,OsiHintTry);
  // See if we want preprocessing
  OsiSolverInterface * solver2=&solver1;
  CglPreProcess process;
  // Never do preprocessing until dual tests out as can fix incorrectly
  preProcess=false;
  if (preProcess) {
    /* Do not try and produce equality cliques and
       do up to 5 passes */
    solver2 = process.preProcess(solver1,false,5);
    if (!solver2) {
      printf("Pre-processing says infeasible\n");
      exit(2);
    }
    solver2->resolve();
  }
  // Turn L rows into cuts
  CglStoredUser stored;
 {
  int numberRows = solver2->getNumRows();

  int * whichRow = new int[numberRows];
  // get row copy
  const CoinPackedMatrix * rowCopy = solver2->getMatrixByRow();
  const int * column = rowCopy->getIndices();
  const int * rowLength = rowCopy->getVectorLengths();
  const CoinBigIndex * rowStart = rowCopy->getVectorStarts();
  const double * rowLower = solver2->getRowLower();
  const double * rowUpper = solver2->getRowUpper();
  const double * element = rowCopy->getElements();
  int iRow,nDelete=0;
  for (iRow=0;iRow<numberRows;iRow++) {
    if (rowLower[iRow]<-1.0e20||rowUpper[iRow]>1.0e20) {
      // take out
      whichRow[nDelete++]=iRow;
    }
  }
  // leave some rows to avoid empty problem (Gomory does not like)
  nDelete = CoinMax(CoinMin(nDelete,numberRows-5),0);
  for (int jRow=0;jRow<nDelete;jRow++) {
    iRow=whichRow[jRow];
    int start = rowStart[iRow];
    stored.addCut(rowLower[iRow],rowUpper[iRow],rowLength[iRow],
//.........这里部分代码省略.........