Esempio n. 1
0
  void 
  LinearCutsGenerator::generateCuts(const OsiSolverInterface &solver, OsiCuts &cs,
                     const CglTreeInfo info) const {

    //const OsiTMINLPInterface * tmp = dynamic_cast<const OsiTMINLPInterface *>(&solver);
    OsiTMINLPInterface * nlp = dynamic_cast<OsiTMINLPInterface *>(solver.clone());//const_cast<OsiTMINLPInterface *>(tmp);
    assert(nlp);
    OuterApprox oa;
    //si.writeMps("toto");
    int numberRows = nlp->getNumRows();
    for(int i = 0 ; i < 5 ; i++){
      nlp->resolve();
      OsiClpSolverInterface si;
      oa(*nlp, &si, solver.getColSolution(), true); 
      si.resolve();
      OsiCuts cuts;
      for(std::list<Coin::SmartPtr<CuttingMethod> >::const_iterator i = methods_.begin() ;
          i != methods_.end() ; i++){
         (*i)->cgl->generateCuts(si, cuts, info);
      }
      std::vector<OsiRowCut *> mycuts(cuts.sizeRowCuts());
      for(int i = 0 ; i < cuts.sizeRowCuts() ; i++){
        mycuts[i] = cuts.rowCutPtr(i);
        cs.insert(*mycuts[i]);
      }
      nlp->applyRowCuts(mycuts.size(), const_cast<const OsiRowCut **> (&mycuts[0]));
    }

    // Take off slack cuts
    std::vector<int> kept;
    int numberRowsNow = nlp->getNumRows();
    int * del = new int [numberRowsNow-numberRows];
    nlp->resolve();
    
    const double * activity = nlp->getRowActivity();
    const double * lb = nlp->getRowLower();
    const double * ub = nlp->getRowUpper();
    CoinRelFltEq eq(1e-06);
    //int nDelete=0;
    for (int i=numberRowsNow -1;i>=numberRows;i--) {
      if ( !(eq(activity[i], lb[i]) || eq(activity[i], ub[i])) )
        cs.eraseRowCut(i - numberRows);
    }
    delete [] del;
    delete nlp;
  }
Esempio n. 2
0
// inner part of dive
int 
CbcHeuristicDive::solution(double & solutionValue, int & numberNodes,
			   int & numberCuts, OsiRowCut ** cuts,
			   CbcSubProblem ** & nodes,
			   double * newSolution)
{
#ifdef DIVE_DEBUG
    int nRoundInfeasible = 0;
    int nRoundFeasible = 0;
#endif
    int reasonToStop = 0;
    double time1 = CoinCpuTime();
    int numberSimplexIterations = 0;
    int maxSimplexIterations = (model_->getNodeCount()) ? maxSimplexIterations_
                               : maxSimplexIterationsAtRoot_;
    // but can't be exactly coin_int_max
    maxSimplexIterations = CoinMin(maxSimplexIterations,COIN_INT_MAX>>3);
    OsiSolverInterface * solver = cloneBut(6); // was model_->solver()->clone();
# ifdef COIN_HAS_CLP
    OsiClpSolverInterface * clpSolver
    = dynamic_cast<OsiClpSolverInterface *> (solver);
    if (clpSolver) {
      ClpSimplex * clpSimplex = clpSolver->getModelPtr();
      int oneSolveIts = clpSimplex->maximumIterations();
      oneSolveIts = CoinMin(1000+2*(clpSimplex->numberRows()+clpSimplex->numberColumns()),oneSolveIts);
      clpSimplex->setMaximumIterations(oneSolveIts);
      if (!nodes) {
        // say give up easily
        clpSimplex->setMoreSpecialOptions(clpSimplex->moreSpecialOptions() | 64);
      } else {
	// get ray
	int specialOptions = clpSimplex->specialOptions();
	specialOptions &= ~0x3100000;
	specialOptions |= 32;
        clpSimplex->setSpecialOptions(specialOptions);
        clpSolver->setSpecialOptions(clpSolver->specialOptions() | 1048576);
	if ((model_->moreSpecialOptions()&16777216)!=0) {
	  // cutoff is constraint
	  clpSolver->setDblParam(OsiDualObjectiveLimit, COIN_DBL_MAX);
	}
      }
    }
# endif
    const double * lower = solver->getColLower();
    const double * upper = solver->getColUpper();
    const double * rowLower = solver->getRowLower();
    const double * rowUpper = solver->getRowUpper();
    const double * solution = solver->getColSolution();
    const double * objective = solver->getObjCoefficients();
    double integerTolerance = model_->getDblParam(CbcModel::CbcIntegerTolerance);
    double primalTolerance;
    solver->getDblParam(OsiPrimalTolerance, primalTolerance);

    int numberRows = matrix_.getNumRows();
    assert (numberRows <= solver->getNumRows());
    int numberIntegers = model_->numberIntegers();
    const int * integerVariable = model_->integerVariable();
    double direction = solver->getObjSense(); // 1 for min, -1 for max
    double newSolutionValue = direction * solver->getObjValue();
    int returnCode = 0;
    // Column copy
    const double * element = matrix_.getElements();
    const int * row = matrix_.getIndices();
    const CoinBigIndex * columnStart = matrix_.getVectorStarts();
    const int * columnLength = matrix_.getVectorLengths();
#ifdef DIVE_FIX_BINARY_VARIABLES
    // Row copy
    const double * elementByRow = matrixByRow_.getElements();
    const int * column = matrixByRow_.getIndices();
    const CoinBigIndex * rowStart = matrixByRow_.getVectorStarts();
    const int * rowLength = matrixByRow_.getVectorLengths();
#endif

    // Get solution array for heuristic solution
    int numberColumns = solver->getNumCols();
    memcpy(newSolution, solution, numberColumns*sizeof(double));

    // vectors to store the latest variables fixed at their bounds
    int* columnFixed = new int [numberIntegers];
    double* originalBound = new double [numberIntegers+2*numberColumns];
    double * lowerBefore = originalBound+numberIntegers;
    double * upperBefore = lowerBefore+numberColumns;
    memcpy(lowerBefore,lower,numberColumns*sizeof(double));
    memcpy(upperBefore,upper,numberColumns*sizeof(double));
    double * lastDjs=newSolution+numberColumns;
    bool * fixedAtLowerBound = new bool [numberIntegers];
    PseudoReducedCost * candidate = new PseudoReducedCost [numberIntegers];
    double * random = new double [numberIntegers];

    int maxNumberAtBoundToFix = static_cast<int> (floor(percentageToFix_ * numberIntegers));
    assert (!maxNumberAtBoundToFix||!nodes);

    // count how many fractional variables
    int numberFractionalVariables = 0;
    for (int i = 0; i < numberIntegers; i++) {
        random[i] = randomNumberGenerator_.randomDouble() + 0.3;
        int iColumn = integerVariable[i];
        double value = newSolution[iColumn];
        if (fabs(floor(value + 0.5) - value) > integerTolerance) {
            numberFractionalVariables++;
        }
    }

    const double* reducedCost = NULL;
    // See if not NLP
    if (model_->solverCharacteristics()->reducedCostsAccurate())
        reducedCost = solver->getReducedCost();

    int iteration = 0;
    while (numberFractionalVariables) {
        iteration++;

        // initialize any data
        initializeData();

        // select a fractional variable to bound
        int bestColumn = -1;
        int bestRound; // -1 rounds down, +1 rounds up
        bool canRound = selectVariableToBranch(solver, newSolution,
                                               bestColumn, bestRound);
        // if the solution is not trivially roundable, we don't try to round;
        // if the solution is trivially roundable, we try to round. However,
        // if the rounded solution is worse than the current incumbent,
        // then we don't round and proceed normally. In this case, the
        // bestColumn will be a trivially roundable variable
        if (canRound) {
            // check if by rounding all fractional variables
            // we get a solution with an objective value
            // better than the current best integer solution
            double delta = 0.0;
            for (int i = 0; i < numberIntegers; i++) {
                int iColumn = integerVariable[i];
                double value = newSolution[iColumn];
                if (fabs(floor(value + 0.5) - value) > integerTolerance) {
                    assert(downLocks_[i] == 0 || upLocks_[i] == 0);
                    double obj = objective[iColumn];
                    if (downLocks_[i] == 0 && upLocks_[i] == 0) {
                        if (direction * obj >= 0.0)
                            delta += (floor(value) - value) * obj;
                        else
                            delta += (ceil(value) - value) * obj;
                    } else if (downLocks_[i] == 0)
                        delta += (floor(value) - value) * obj;
                    else
                        delta += (ceil(value) - value) * obj;
                }
            }
            if (direction*(solver->getObjValue() + delta) < solutionValue) {
#ifdef DIVE_DEBUG
                nRoundFeasible++;
#endif
		if (!nodes||bestColumn<0) {
		  // Round all the fractional variables
		  for (int i = 0; i < numberIntegers; i++) {
                    int iColumn = integerVariable[i];
                    double value = newSolution[iColumn];
                    if (fabs(floor(value + 0.5) - value) > integerTolerance) {
		      assert(downLocks_[i] == 0 || upLocks_[i] == 0);
		      if (downLocks_[i] == 0 && upLocks_[i] == 0) {
			if (direction * objective[iColumn] >= 0.0)
			  newSolution[iColumn] = floor(value);
			else
			  newSolution[iColumn] = ceil(value);
		      } else if (downLocks_[i] == 0)
			newSolution[iColumn] = floor(value);
		      else
			newSolution[iColumn] = ceil(value);
                    }
		  }
		  break;
		} else {
		  // can't round if going to use in branching
		  int i;
		  for (i = 0; i < numberIntegers; i++) {
		    int iColumn = integerVariable[i];
		    double value = newSolution[bestColumn];
		    if (fabs(floor(value + 0.5) - value) > integerTolerance) {
		      if (iColumn==bestColumn) {
			assert(downLocks_[i] == 0 || upLocks_[i] == 0);
			double obj = objective[bestColumn];
			if (downLocks_[i] == 0 && upLocks_[i] == 0) {
			  if (direction * obj >= 0.0)
                            bestRound=-1;
			  else
                            bestRound=1;
			} else if (downLocks_[i] == 0)
			  bestRound=-1;
			else
			  bestRound=1;
			break;
		      }
		    }
		  }
		}
	    }
#ifdef DIVE_DEBUG
            else
                nRoundInfeasible++;
#endif
        }

        // do reduced cost fixing
#ifdef DIVE_DEBUG
        int numberFixed = reducedCostFix(solver);
        std::cout << "numberReducedCostFixed = " << numberFixed << std::endl;
#else
        reducedCostFix(solver);
#endif

        int numberAtBoundFixed = 0;
#ifdef DIVE_FIX_BINARY_VARIABLES
        // fix binary variables based on pseudo reduced cost
        if (binVarIndex_.size()) {
            int cnt = 0;
            int n = static_cast<int>(binVarIndex_.size());
            for (int j = 0; j < n; j++) {
                int iColumn1 = binVarIndex_[j];
                double value = newSolution[iColumn1];
                if (fabs(value) <= integerTolerance &&
                        lower[iColumn1] != upper[iColumn1]) {
                    double maxPseudoReducedCost = 0.0;
#ifdef DIVE_DEBUG
                    std::cout << "iColumn1 = " << iColumn1 << ", value = " << value << std::endl;
#endif
                    int iRow = vbRowIndex_[j];
                    double chosenValue = 0.0;
                    for (int k = rowStart[iRow]; k < rowStart[iRow] + rowLength[iRow]; k++) {
                        int iColumn2 = column[k];
#ifdef DIVE_DEBUG
                        std::cout << "iColumn2 = " << iColumn2 << std::endl;
#endif
                        if (iColumn1 != iColumn2) {
                            double pseudoReducedCost = fabs(reducedCost[iColumn2] *
                                                            elementByRow[k]);
#ifdef DIVE_DEBUG
                            int k2;
                            for (k2 = rowStart[iRow]; k2 < rowStart[iRow] + rowLength[iRow]; k2++) {
                                if (column[k2] == iColumn1)
                                    break;
                            }
                            std::cout << "reducedCost[" << iColumn2 << "] = "
                                      << reducedCost[iColumn2]
                                      << ", elementByRow[" << iColumn2 << "] = " << elementByRow[k]
                                      << ", elementByRow[" << iColumn1 << "] = " << elementByRow[k2]
                                      << ", pseudoRedCost = " << pseudoReducedCost
                                      << std::endl;
#endif
                            if (pseudoReducedCost > maxPseudoReducedCost)
                                maxPseudoReducedCost = pseudoReducedCost;
                        } else {
                            // save value
                            chosenValue = fabs(elementByRow[k]);
                        }
                    }
                    assert (chosenValue);
                    maxPseudoReducedCost /= chosenValue;
#ifdef DIVE_DEBUG
                    std::cout << ", maxPseudoRedCost = " << maxPseudoReducedCost << std::endl;
#endif
                    candidate[cnt].var = iColumn1;
                    candidate[cnt++].pseudoRedCost = maxPseudoReducedCost;
                }
            }
#ifdef DIVE_DEBUG
            std::cout << "candidates for rounding = " << cnt << std::endl;
#endif
            std::sort(candidate, candidate + cnt, compareBinaryVars);
            for (int i = 0; i < cnt; i++) {
                int iColumn = candidate[i].var;
                if (numberAtBoundFixed < maxNumberAtBoundToFix) {
                    columnFixed[numberAtBoundFixed] = iColumn;
                    originalBound[numberAtBoundFixed] = upper[iColumn];
                    fixedAtLowerBound[numberAtBoundFixed] = true;
                    solver->setColUpper(iColumn, lower[iColumn]);
                    numberAtBoundFixed++;
                    if (numberAtBoundFixed == maxNumberAtBoundToFix)
                        break;
                }
            }
        }
#endif

        // fix other integer variables that are at their bounds
        int cnt = 0;
#ifdef GAP
        double gap = 1.0e30;
#endif
        if (reducedCost && true) {
#ifndef JJF_ONE
            cnt = fixOtherVariables(solver, solution, candidate, random);
#else
#ifdef GAP
            double cutoff = model_->getCutoff() ;
            if (cutoff < 1.0e20 && false) {
                double direction = solver->getObjSense() ;
                gap = cutoff - solver->getObjValue() * direction ;
                gap *= 0.1; // Fix more if plausible
                double tolerance;
                solver->getDblParam(OsiDualTolerance, tolerance) ;
                if (gap <= 0.0)
                    gap = tolerance;
                gap += 100.0 * tolerance;
            }
            int nOverGap = 0;
#endif
            int numberFree = 0;
            int numberFixed = 0;
            for (int i = 0; i < numberIntegers; i++) {
                int iColumn = integerVariable[i];
                if (upper[iColumn] > lower[iColumn]) {
                    numberFree++;
                    double value = newSolution[iColumn];
                    if (fabs(floor(value + 0.5) - value) <= integerTolerance) {
                        candidate[cnt].var = iColumn;
                        candidate[cnt++].pseudoRedCost =
                            fabs(reducedCost[iColumn] * random[i]);
#ifdef GAP
                        if (fabs(reducedCost[iColumn]) > gap)
                            nOverGap++;
#endif
                    }
                } else {
                    numberFixed++;
                }
            }
#ifdef GAP
            int nLeft = maxNumberAtBoundToFix - numberAtBoundFixed;
#ifdef CLP_INVESTIGATE4
            printf("cutoff %g obj %g nover %d - %d free, %d fixed\n",
                   cutoff, solver->getObjValue(), nOverGap, numberFree, numberFixed);
#endif
            if (nOverGap > nLeft && true) {
                nOverGap = CoinMin(nOverGap, nLeft + maxNumberAtBoundToFix / 2);
                maxNumberAtBoundToFix += nOverGap - nLeft;
            }
#else
#ifdef CLP_INVESTIGATE4
            printf("cutoff %g obj %g - %d free, %d fixed\n",
                   model_->getCutoff(), solver->getObjValue(), numberFree, numberFixed);
#endif
#endif
#endif
        } else {
            for (int i = 0; i < numberIntegers; i++) {
                int iColumn = integerVariable[i];
                if (upper[iColumn] > lower[iColumn]) {
                    double value = newSolution[iColumn];
                    if (fabs(floor(value + 0.5) - value) <= integerTolerance) {
                        candidate[cnt].var = iColumn;
                        candidate[cnt++].pseudoRedCost = numberIntegers - i;
                    }
                }
            }
        }
        std::sort(candidate, candidate + cnt, compareBinaryVars);
        for (int i = 0; i < cnt; i++) {
            int iColumn = candidate[i].var;
            if (upper[iColumn] > lower[iColumn]) {
                double value = newSolution[iColumn];
                if (fabs(floor(value + 0.5) - value) <= integerTolerance &&
                        numberAtBoundFixed < maxNumberAtBoundToFix) {
                    // fix the variable at one of its bounds
                    if (fabs(lower[iColumn] - value) <= integerTolerance) {
                        columnFixed[numberAtBoundFixed] = iColumn;
                        originalBound[numberAtBoundFixed] = upper[iColumn];
                        fixedAtLowerBound[numberAtBoundFixed] = true;
                        solver->setColUpper(iColumn, lower[iColumn]);
                        numberAtBoundFixed++;
                    } else if (fabs(upper[iColumn] - value) <= integerTolerance) {
                        columnFixed[numberAtBoundFixed] = iColumn;
                        originalBound[numberAtBoundFixed] = lower[iColumn];
                        fixedAtLowerBound[numberAtBoundFixed] = false;
                        solver->setColLower(iColumn, upper[iColumn]);
                        numberAtBoundFixed++;
                    }
                    if (numberAtBoundFixed == maxNumberAtBoundToFix)
                        break;
                }
            }
        }
#ifdef DIVE_DEBUG
        std::cout << "numberAtBoundFixed = " << numberAtBoundFixed << std::endl;
#endif

        double originalBoundBestColumn;
        double bestColumnValue;
	int whichWay;
        if (bestColumn >= 0) {
	    bestColumnValue = newSolution[bestColumn];
            if (bestRound < 0) {
                originalBoundBestColumn = upper[bestColumn];
                solver->setColUpper(bestColumn, floor(bestColumnValue));
		whichWay=0;
            } else {
                originalBoundBestColumn = lower[bestColumn];
                solver->setColLower(bestColumn, ceil(bestColumnValue));
		whichWay=1;
            }
        } else {
            break;
        }
        int originalBestRound = bestRound;
        int saveModelOptions = model_->specialOptions();
	
        while (1) {

            model_->setSpecialOptions(saveModelOptions | 2048);
            solver->resolve();
            model_->setSpecialOptions(saveModelOptions);
            if (!solver->isAbandoned()&&!solver->isIterationLimitReached()) {
                numberSimplexIterations += solver->getIterationCount();
            } else {
                numberSimplexIterations = maxSimplexIterations + 1;
		reasonToStop += 100;
                break;
            }

            if (!solver->isProvenOptimal()) {
	        if (nodes) {
		  if (solver->isProvenPrimalInfeasible()) {
		    if (maxSimplexIterationsAtRoot_!=COIN_INT_MAX) {
		      // stop now
		      printf("stopping on first infeasibility\n");
		      break;
		    } else if (cuts) {
		      // can do conflict cut
		      printf("could do intermediate conflict cut\n");
		      bool localCut;
		      OsiRowCut * cut = model_->conflictCut(solver,localCut);
		      if (cut) {
			if (!localCut) {
			  model_->makePartialCut(cut,solver);
			  cuts[numberCuts++]=cut;
			} else {
			  delete cut;
			}
		      }
		    }
		  } else {
		    reasonToStop += 10;
		    break;
		  }
		}
                if (numberAtBoundFixed > 0) {
                    // Remove the bound fix for variables that were at bounds
                    for (int i = 0; i < numberAtBoundFixed; i++) {
                        int iColFixed = columnFixed[i];
                        if (fixedAtLowerBound[i])
                            solver->setColUpper(iColFixed, originalBound[i]);
                        else
                            solver->setColLower(iColFixed, originalBound[i]);
                    }
                    numberAtBoundFixed = 0;
                } else if (bestRound == originalBestRound) {
                    bestRound *= (-1);
		    whichWay |=2;
                    if (bestRound < 0) {
                        solver->setColLower(bestColumn, originalBoundBestColumn);
                        solver->setColUpper(bestColumn, floor(bestColumnValue));
                    } else {
                        solver->setColLower(bestColumn, ceil(bestColumnValue));
                        solver->setColUpper(bestColumn, originalBoundBestColumn);
                    }
                } else
                    break;
            } else
                break;
        }

        if (!solver->isProvenOptimal() ||
                direction*solver->getObjValue() >= solutionValue) {
            reasonToStop += 1;
        } else if (iteration > maxIterations_) {
            reasonToStop += 2;
        } else if (CoinCpuTime() - time1 > maxTime_) {
            reasonToStop += 3;
        } else if (numberSimplexIterations > maxSimplexIterations) {
            reasonToStop += 4;
            // also switch off
#ifdef CLP_INVESTIGATE
            printf("switching off diving as too many iterations %d, %d allowed\n",
                   numberSimplexIterations, maxSimplexIterations);
#endif
            when_ = 0;
        } else if (solver->getIterationCount() > 1000 && iteration > 3 && !nodes) {
            reasonToStop += 5;
            // also switch off
#ifdef CLP_INVESTIGATE
            printf("switching off diving one iteration took %d iterations (total %d)\n",
                   solver->getIterationCount(), numberSimplexIterations);
#endif
            when_ = 0;
        }

        memcpy(newSolution, solution, numberColumns*sizeof(double));
        numberFractionalVariables = 0;
	double sumFractionalVariables=0.0;
        for (int i = 0; i < numberIntegers; i++) {
            int iColumn = integerVariable[i];
            double value = newSolution[iColumn];
	    double away = fabs(floor(value + 0.5) - value);
            if (away > integerTolerance) {
                numberFractionalVariables++;
		sumFractionalVariables += away;
            }
        }
	if (nodes) {
	  // save information
	  //branchValues[numberNodes]=bestColumnValue;
	  //statuses[numberNodes]=whichWay+(bestColumn<<2);
	  //bases[numberNodes]=solver->getWarmStart();
	  ClpSimplex * simplex = clpSolver->getModelPtr();
	  CbcSubProblem * sub =
	    new CbcSubProblem(clpSolver,lowerBefore,upperBefore,
			  simplex->statusArray(),numberNodes);
	  nodes[numberNodes]=sub;
	  // other stuff
	  sub->branchValue_=bestColumnValue;
	  sub->problemStatus_=whichWay;
	  sub->branchVariable_=bestColumn;
	  sub->objectiveValue_ = simplex->objectiveValue();
	  sub->sumInfeasibilities_ = sumFractionalVariables;
	  sub->numberInfeasibilities_ = numberFractionalVariables;
	  printf("DiveNode %d column %d way %d bvalue %g obj %g\n",
		 numberNodes,sub->branchVariable_,sub->problemStatus_,
		 sub->branchValue_,sub->objectiveValue_);
	  numberNodes++;
	  if (solver->isProvenOptimal()) {
	    memcpy(lastDjs,solver->getReducedCost(),numberColumns*sizeof(double));
	    memcpy(lowerBefore,lower,numberColumns*sizeof(double));
	    memcpy(upperBefore,upper,numberColumns*sizeof(double));
	  }
	}
	if (!numberFractionalVariables||reasonToStop)
	  break;
    }
    if (nodes) {
      printf("Exiting dive for reason %d\n",reasonToStop);
      if (reasonToStop>1) {
	printf("problems in diving\n");
	int whichWay=nodes[numberNodes-1]->problemStatus_;
	CbcSubProblem * sub;
	if ((whichWay&2)==0) {
	  // leave both ways
	  sub = new CbcSubProblem(*nodes[numberNodes-1]);
	  nodes[numberNodes++]=sub;
	} else {
	  sub = nodes[numberNodes-1];
	}
	if ((whichWay&1)==0)
	  sub->problemStatus_=whichWay|1;
	else
	  sub->problemStatus_=whichWay&~1;
      }
      if (!numberNodes) {
	// was good at start! - create fake
	clpSolver->resolve();
	ClpSimplex * simplex = clpSolver->getModelPtr();
	CbcSubProblem * sub =
	  new CbcSubProblem(clpSolver,lowerBefore,upperBefore,
			    simplex->statusArray(),numberNodes);
	nodes[numberNodes]=sub;
	// other stuff
	sub->branchValue_=0.0;
	sub->problemStatus_=0;
	sub->branchVariable_=-1;
	sub->objectiveValue_ = simplex->objectiveValue();
	sub->sumInfeasibilities_ = 0.0;
	sub->numberInfeasibilities_ = 0;
	printf("DiveNode %d column %d way %d bvalue %g obj %g\n",
	       numberNodes,sub->branchVariable_,sub->problemStatus_,
	       sub->branchValue_,sub->objectiveValue_);
	numberNodes++;
	assert (solver->isProvenOptimal());
      }
      nodes[numberNodes-1]->problemStatus_ |= 256*reasonToStop;
      // use djs as well
      if (solver->isProvenPrimalInfeasible()&&cuts) {
	// can do conflict cut and re-order
	printf("could do final conflict cut\n");
	bool localCut;
	OsiRowCut * cut = model_->conflictCut(solver,localCut);
	if (cut) {
	  printf("cut - need to use conflict and previous djs\n");
	  if (!localCut) {
	    model_->makePartialCut(cut,solver);
	    cuts[numberCuts++]=cut;
	  } else {
	    delete cut;
	  }
	} else {
	  printf("bad conflict - just use previous djs\n");
	}
      }
    }
    
    // re-compute new solution value
    double objOffset = 0.0;
    solver->getDblParam(OsiObjOffset, objOffset);
    newSolutionValue = -objOffset;
    for (int i = 0 ; i < numberColumns ; i++ )
      newSolutionValue += objective[i] * newSolution[i];
    newSolutionValue *= direction;
    //printf("new solution value %g %g\n",newSolutionValue,solutionValue);
    if (newSolutionValue < solutionValue && !reasonToStop) {
      double * rowActivity = new double[numberRows];
      memset(rowActivity, 0, numberRows*sizeof(double));
      // paranoid check
      memset(rowActivity, 0, numberRows*sizeof(double));
      for (int i = 0; i < numberColumns; i++) {
	int j;
	double value = newSolution[i];
	if (value) {
	  for (j = columnStart[i];
	       j < columnStart[i] + columnLength[i]; j++) {
	    int iRow = row[j];
	    rowActivity[iRow] += value * element[j];
	  }
	}
      }
      // check was approximately feasible
      bool feasible = true;
      for (int i = 0; i < numberRows; i++) {
	if (rowActivity[i] < rowLower[i]) {
	  if (rowActivity[i] < rowLower[i] - 1000.0*primalTolerance)
	    feasible = false;
	} else if (rowActivity[i] > rowUpper[i]) {
	  if (rowActivity[i] > rowUpper[i] + 1000.0*primalTolerance)
	    feasible = false;
	}
      }
      for (int i = 0; i < numberIntegers; i++) {
	int iColumn = integerVariable[i];
	double value = newSolution[iColumn];
	if (fabs(floor(value + 0.5) - value) > integerTolerance) {
	  feasible = false;
	  break;
	}
      }
      if (feasible) {
	// new solution
	solutionValue = newSolutionValue;
	//printf("** Solution of %g found by CbcHeuristicDive\n",newSolutionValue);
	//if (cuts)
	//clpSolver->getModelPtr()->writeMps("good8.mps", 2);
	returnCode = 1;
      } else {
	// Can easily happen
	//printf("Debug CbcHeuristicDive giving bad solution\n");
      }
      delete [] rowActivity;
    }

#ifdef DIVE_DEBUG
    std::cout << "nRoundInfeasible = " << nRoundInfeasible
              << ", nRoundFeasible = " << nRoundFeasible
              << ", returnCode = " << returnCode
              << ", reasonToStop = " << reasonToStop
              << ", simplexIts = " << numberSimplexIterations
              << ", iterations = " << iteration << std::endl;
#endif

    delete [] columnFixed;
    delete [] originalBound;
    delete [] fixedAtLowerBound;
    delete [] candidate;
    delete [] random;
    delete [] downArray_;
    downArray_ = NULL;
    delete [] upArray_;
    upArray_ = NULL;
    delete solver;
    return returnCode;
}
Esempio n. 3
0
int main(int argc, char **argv) 
{
  char *f_name_lp, *last_dot_pos, f_name[256], *f_name_pos;
  int i, ncol;

  if((argc < 2) || (argc > 2)) {
    printf("### ERROR: main(): Usage: One of the following\ncgl_data_test input_file_name.mps\ncgl_data_test input_file_name.lp\n");
    exit(1);
  }

  f_name_lp = strdup(argv[1]);
  f_name_pos = strrchr(f_name_lp, '/');
  if(f_name_pos != NULL) {
    strcpy(f_name, &(f_name_pos[1]));
  }
  else {
    strcpy(f_name, f_name_lp);
  }
  last_dot_pos = strrchr(f_name, '.');
  if(last_dot_pos != NULL) {
    last_dot_pos = '\0';
  }

  OsiClpSolverInterface *clp = new OsiClpSolverInterface;
  clp->messageHandler()->setLogLevel(0);
  if(strcmp(&(f_name_lp[strlen(f_name_lp)-3]), ".lp") == 0) {
    clp->readLp(f_name_lp);    
  }
  else {
    if(strcmp(&(f_name_lp[strlen(f_name_lp)-4]), ".mps") == 0) {
      clp->readMps(f_name_lp);    
    }
    else {
      printf("### ERROR: unrecognized file type\n");
      exit(1);
    }
  }
  ncol = clp->getNumCols();
  clp->initialSolve();

  printf("LP value: %12.2f\n", clp->getObjValue());

  OsiCuts cuts;

  // Define parameters for CglRedSplit generator
  CglParam cpar;
  cpar.setMAX_SUPPORT(ncol+1);
  CglRedSplitParam rspar(cpar);

  // Create a cut generator with the given parameters
  CglRedSplit cutGen(rspar);

  char *colType = new char[ncol];
  for(i=0; i<ncol; i++) {
    if(clp->isContinuous(i)) {
      colType[i] = 'C';
    }
    else {
      colType[i] = 'I';
    }
  }

  int round, max_rounds = 10;
  for(round=0; round<max_rounds; round++) {
    cutGen.generateCuts(*clp, cuts);

    int ncuts = cuts.sizeRowCuts();

    const OsiRowCut **newRowCuts = new const OsiRowCut * [ncuts];
    for(i=0; i<ncuts; i++) {
      newRowCuts[i] = &cuts.rowCut(i); 
    }
    clp->applyRowCuts(ncuts, newRowCuts);
    delete[] newRowCuts;

    printf("round %4d: %4d generated cuts  new objective value: %12.2f\n", 
	   round, ncuts, clp->getObjValue());

    clp->resolve();  

    if(clp->isAbandoned()) {
      printf("###ERROR: Numerical difficulties in Solver\n");
      exit(1);
    }
  
    if(clp->isProvenPrimalInfeasible()) {
      printf("### WARNING: Problem is infeasible\n");
      exit(1);
    }
  }

  delete clp;
  free(f_name_lp);
  delete[] colType;

  return(0);
}