Example #1
0
// 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;
}
Example #2
0
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;
}
Example #3
0
//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);
}