C++ OsiSolverInterface::setColSolution方法代码示例

// Restore result
void OsiSolverResult::restoreResult(OsiSolverInterface &solver) const
{
  //solver.setObjValue(objectiveValue_)*solver.getObjSense();
  solver.setWarmStart(&basis_);
  solver.setColSolution(primalSolution_);
  solver.setRowPrice(dualSolution_);
  fixed_.applyBounds(solver, -1);
}

//.........这里部分代码省略.........
            else if (!downKeep) {
                // Down branch can be fathomed.
                lbInd[numLowerTightens] = colInd;
                newLB[numLowerTightens++] = ceil(lpX);
            }
            else if (!upKeep) {
                // Up branch can be fathomed.
                ubInd[numUpperTightens] = colInd;
                newUB[numUpperTightens++] = floor(lpX);
            }
        }

        //--------------------------------------------------
        // Set new bounds in lp solver for resolving
        //--------------------------------------------------
        
        if (bStatus != -2) {
            if (numUpperTightens > 0) {
                bStatus = -1;
                for (i = 0; i < numUpperTightens; ++i) {
                    solver->setColUpper(ubInd[i], newUB[i]);
                }
            }
            if (numLowerTightens > 0) {
                bStatus = -1;
                for (i = 0; i < numLowerTightens; ++i) {
                    solver->setColLower(lbInd[i], newLB[i]);
                }
            }
        }
	
        //--------------------------------------------------
        // Unmark hotstart and recover LP solver.
        //--------------------------------------------------
        
        solver->unmarkHotStart();
        solver->setColSolution(saveSolution);
        solver->setIntParam(OsiMaxNumIterationHotStart, saveLimit);
        solver->setWarmStart(ws);
        delete ws;
    }
    
    if (bStatus < 0) {
	goto TERM_CREATE;
    }
    else {
        // Create a set of candidate branching objects. 
        numBranchObjects_ = numInfs;
        branchObjects_ = new BcpsBranchObject* [numInfs];        
        
        // NOTE: it set model->savedLpSolution.
        
        sumDeg = 0.0;
	
        for (i = 0; i < numInfs; ++i) {

            if (infObjects[i]->pseudocost().getUpCost() < 
                infObjects[i]->pseudocost().getDownCost()) {
                preferDir = 1;
            }
            else {
                preferDir = -1;
            }
            
            branchObjects_[i] = infObjects[i]->createBranchObject(model,
                                                                  preferDir);
            score = infObjects[i]->pseudocost().getScore();
            branchObjects_[i]->setUpScore(score);
            sumDeg += score;
            

#ifdef BLIS_DEBUG_MORE
            std::cout << "col[" << infObjects[i]->columnIndex() << "]: score="
                      << score << ", dir=" << branchObjects_[i]->getDirection()
                      << ", up=" << infObjects[i]->pseudocost().getUpCost()
                      << ", down=" << infObjects[i]->pseudocost().getDownCost()
                      << std::endl;
#endif
        }
        
        model->setSolEstimate(objValue + sumDeg);
    }
    

 TERM_CREATE:
    
    //------------------------------------------------------
    // Cleanup.
    //------------------------------------------------------

    delete [] lbInd;
    delete [] ubInd;
    delete [] newLB;
    delete [] newUB;
    delete [] saveSolution;
    delete [] saveLower;
    delete [] saveUpper;

    return bStatus;
}

//.........这里部分代码省略.........
    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);

//.........这里部分代码省略.........
            // Update pseudocost.
            if(downGood) {
                firstObjects[i]->pseudocost().update(-1, downDeg, lpX);
            }
            if(downGood) {
                firstObjects[i]->pseudocost().update(1, upDeg, lpX);
            }
        }

        //--------------------------------------------------
        // Set new bounds in lp solver for resolving
        //--------------------------------------------------

        if (bStatus != -2) {
            if (numUpperTightens > 0) {
                bStatus = -1;
                for (i = 0; i < numUpperTightens; ++i) {
                    solver->setColUpper(ubInd[i], newUB[i]);
                }
            }
            if (numLowerTightens > 0) {
                bStatus = -1;
                for (i = 0; i < numLowerTightens; ++i) {
                    solver->setColLower(lbInd[i], newLB[i]);
                }
            }
        }

        //--------------------------------------------------
        // Unmark hotstart and recover LP solver.
        //--------------------------------------------------

        solver->unmarkHotStart();
        solver->setColSolution(saveSolution);
        solver->setIntParam(OsiMaxNumIterationHotStart, saveLimit);
        solver->setWarmStart(ws);
        delete ws;
    }

    //std::cout << "REL: bStatus = " << bStatus << std::endl;

    if (bStatus < 0) {
        // Infeasible or monotone.
        goto TERM_CREATE;
    }
    else {
        // All object's pseudocost have been initialized.
        // Sort them, and do strong branch for the unreliable one
        // NOTE: it set model->savedLpSolution.
        // model->feasibleSolution(numIntegerInfs, numObjectInfs);

        sumDeg = 0.0;

        for (i = 0; i < numInfs; ++i) {
            score = infObjects[i]->pseudocost().getScore();
            sumDeg += score;

            std::pair<const double, BlisObjectInt*> sa(score, infObjects[i]);
            sortedObjects.insert(sa);

#ifdef BLIS_DEBUG_MORE
            std::cout << "col[" << infObjects[i]->columnIndex() << "]="
                      << score << ", "<< std::endl;
#endif
        }

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
//.........这里部分代码省略.........