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

//.........这里部分代码省略.........
                        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;
		  }

  TNLPSolver::ReturnStatus LpBranchingSolver::
  solveFromHotStart(OsiTMINLPInterface* tminlp_interface)
  {
    TNLPSolver::ReturnStatus retstatus = TNLPSolver::solvedOptimal;

    // updated the bounds of the linear solver
    std::vector<int> diff_low_bnd_index;
    std::vector<double> diff_low_bnd_value;
    std::vector<int> diff_up_bnd_index;
    std::vector<double> diff_up_bnd_value;

    // Get the bounds.  We assume that the bounds in the linear solver
    // are always the original ones
    const int numCols = tminlp_interface->getNumCols();
    const double* colLow_orig = lin_->getColLower();
    const double* colUp_orig = lin_->getColUpper();
    const double* colLow = tminlp_interface->getColLower();
    const double* colUp = tminlp_interface->getColUpper();

    OsiSolverInterface * lin = lin_;
    // eventualy clone lin_
    if(warm_start_mode_ == Clone){
      lin = lin_->clone();
//      std::cout<<"Cloning it"<<std::endl;
    }
    // Set the bounds on the LP solver according to the changes in
    // tminlp_interface
    for (int i=0; i<numCols; i++) {
      const double& lo = colLow[i];
      if (colLow_orig[i] < lo) {
        if(warm_start_mode_ == Basis){
          diff_low_bnd_value.push_back(colLow_orig[i]);
          diff_low_bnd_index.push_back(i);
        }
        lin->setColLower(i,lo);
      }
      const double& up = colUp[i];
      if (colUp_orig[i] > up) {
        if(warm_start_mode_ == Basis){
          diff_up_bnd_index.push_back(i);
          diff_up_bnd_value.push_back(colUp_orig[i]);
        }
        lin->setColUpper(i,lo);
      }
    }

    if(warm_start_mode_ == Basis){
      lin->setWarmStart(warm_);
    }

    lin->resolve();

    double obj = lin->getObjValue();
    bool go_on = true;
    if (lin->isProvenPrimalInfeasible() || 
        lin->isDualObjectiveLimitReached()) {
      retstatus = TNLPSolver::provenInfeasible;
      go_on = false;
    }
    else if (lin->isIterationLimitReached()) {
      retstatus = TNLPSolver::iterationLimit;
      go_on = false;
    }
    else {
      if (maxCuttingPlaneIterations_ > 0 && go_on) {
        double violation;
        obj = ecp_->doEcpRounds(*lin, true, &violation);
        if (obj == COIN_DBL_MAX) {
          retstatus = TNLPSolver::provenInfeasible;
        }
        else if (violation <= 1e-8) {
          retstatus = TNLPSolver::solvedOptimal;
        }
      }
    }
    tminlp_interface->problem()->set_obj_value(obj);
    tminlp_interface->problem()->Set_x_sol(numCols, lin_->getColSolution());

    //restore the original bounds
    if(warm_start_mode_ == Basis){
      for (unsigned int i = 0; i < diff_low_bnd_index.size(); i++) {
        lin_->setColLower(diff_low_bnd_index[i],diff_low_bnd_value[i]);
      }
      for (unsigned int i = 0; i < diff_up_bnd_index.size(); i++) {
        lin_->setColUpper(diff_up_bnd_index[i],diff_up_bnd_value[i]);
      }
    }
    else {
      delete lin;
    }
    return retstatus;
  }

//.........这里部分代码省略.........
    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;
}

//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);
}

BlisReturnStatus
BlisStrongBranch(BlisModel *model, double objValue, int colInd, double x,
		 const double *saveLower, const double *saveUpper,
		 bool &downKeep, bool &downFinished, double &downDeg,
		 bool &upKeep, bool &upFinished, double &upDeg)
{
    BlisReturnStatus status = BlisReturnStatusOk;
    int lpStatus = 0;

    int j, numIntInfDown, numObjInfDown;

    double newObjValue;
    
    OsiSolverInterface * solver = model->solver();
    
    int numCols = solver->getNumCols();
    const double * lower = solver->getColLower();
    const double * upper = solver->getColUpper();

    // Restore bounds
    int numDiff = 0;

    BlisSolution* ksol = NULL;

    int ind = model->getIntObjIndices()[colInd];
    BlisObjectInt *intObj = dynamic_cast<BlisObjectInt *>(model->objects(ind));
    
#ifdef BLIS_DEBUG_MORE
    for (j = 0; j < numCols; ++j) {
	if (saveLower[j] != lower[j]) {
	    //solver->setColLower(j, saveLower[j]);
            ++numDiff;
	}
	if (saveUpper[j] != upper[j]) {
	    //solver->setColUpper(j, saveUpper[j]);
            ++numDiff;
	}
    }
    std::cout << "BEFORE: numDiff = " << numDiff << std::endl;
#endif	 
   
    //------------------------------------------------------
    // Branching down.
    //------------------------------------------------------

    solver->setColUpper(colInd, floor(x));
    solver->solveFromHotStart();
    
    newObjValue = solver->getObjSense() * solver->getObjValue();
    downDeg = newObjValue - objValue;
    
    if (solver->isProvenOptimal()) {
	lpStatus = 0; // optimal
#ifdef BLIS_DEBUG_MORE
        printf("STRONG: COL[%d]: downDeg=%g, x=%g\n", colInd, downDeg, x);
#endif
        // Update pseudocost
        intObj->pseudocost().update(-1, downDeg, x);
        model->setSharedObjectMark(ind);        

        // Check if ip feasible
        ksol = model->feasibleSolution(numIntInfDown, numObjInfDown);
        if (ksol) {
#ifdef BLIS_DEBUG_MORE
            printf("STRONG:Down:found a feasible solution\n");
#endif
            
            model->storeSolution(BlisSolutionTypeStrong, ksol);
	    downKeep = false;
        }
	else {
	    downKeep = true;
	}
	downFinished = true;
    }
    else if (solver->isIterationLimitReached() && 
	     !solver->isDualObjectiveLimitReached()) {
	lpStatus = 2;      // unknown 
	downKeep = true;
	downFinished = false;
    }
    else {
        downDeg = 1.0e20;
	lpStatus = 1; // infeasible
	downKeep = false;
	downFinished = false;
    }       
            
#ifdef BLIS_DEBUG_MORE
    std::cout << "Down: lpStatus = " << lpStatus << std::endl;
#endif
    
    // restore bounds
    numDiff = 0;
    for (j = 0; j < numCols; ++j) {
	if (saveLower[j] != lower[j]) {
	    solver->setColLower(j, saveLower[j]);
            ++numDiff;
	}
	if (saveUpper[j] != upper[j]) {
//.........这里部分代码省略.........