Пример #1
0
/** main procedure of the RENS heuristic, creates and solves a subMIP */
SCIP_RETCODE SCIPapplyGcgrens(
   SCIP*                 scip,               /**< original SCIP data structure                                   */
   SCIP_HEUR*            heur,               /**< heuristic data structure                                       */
   SCIP_RESULT*          result,             /**< result data structure                                          */
   SCIP_Real             minfixingrate,      /**< minimum percentage of integer variables that have to be fixed  */
   SCIP_Real             minimprove,         /**< factor by which RENS should at least improve the incumbent     */
   SCIP_Longint          maxnodes,           /**< maximum number of  nodes for the subproblem                    */
   SCIP_Longint          nstallnodes,        /**< number of stalling nodes for the subproblem                    */
   SCIP_Bool             binarybounds,       /**< should general integers get binary bounds [floor(.),ceil(.)]?  */
   SCIP_Bool             uselprows           /**< should subproblem be created out of the rows in the LP rows?   */
   )
{
   SCIP* subscip;                            /* the subproblem created by RENS                  */
   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */
   SCIP_VAR** vars;                          /* original problem's variables                    */
   SCIP_VAR** subvars;                       /* subproblem's variables                          */

   SCIP_Real cutoff;                         /* objective cutoff for the subproblem             */
   SCIP_Real timelimit;
   SCIP_Real memorylimit;

   int nvars;
   int i;

   SCIP_Bool success;
   SCIP_RETCODE retcode;

   assert(scip != NULL);
   assert(heur != NULL);
   assert(result != NULL);

   assert(maxnodes >= 0);
   assert(nstallnodes >= 0);

   assert(0.0 <= minfixingrate && minfixingrate <= 1.0);
   assert(0.0 <= minimprove && minimprove <= 1.0);

   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* initialize the subproblem */
   SCIP_CALL( SCIPcreate(&subscip) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );

   if( uselprows )
   {
      char probname[SCIP_MAXSTRLEN];

      /* copy all plugins */
      SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );

      /* get name of the original problem and add the string "_gcgrenssub" */
      (void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_gcgrenssub", SCIPgetProbName(scip));

      /* create the subproblem */
      SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );

      /* copy all variables */
      SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
   }
   else
   {
      SCIP_Bool valid;
      SCIP_HEURDATA* heurdata;

      valid = FALSE;

      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "gcgrens", TRUE, FALSE, TRUE, &valid) ); /** @todo check for thread safeness */

      /* get heuristic's data */
      heurdata = SCIPheurGetData(heur);
      assert( heurdata != NULL );

      if( heurdata->copycuts )
      {
         /** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
         SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
      }

      SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
   }

   for( i = 0; i < nvars; i++ )
     subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);

   /* free hash map */
   SCIPhashmapFree(&varmapfw);

   /* create a new problem, which fixes variables with same value in bestsol and LP relaxation */
   SCIP_CALL( createSubproblem(scip, subscip, subvars, minfixingrate, binarybounds, uselprows, &success) );
   SCIPdebugMessage("RENS subproblem: %d vars, %d cons, success=%u\n", SCIPgetNVars(subscip), SCIPgetNConss(subscip), success);

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );

   /* check whether there is enough time and memory left */
   timelimit = 0.0;
   memorylimit = 0.0;
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
   if( !SCIPisInfinity(scip, memorylimit) )
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
   if( timelimit <= 0.0 || memorylimit <= 0.0 )
      goto TERMINATE;

   /* set limits for the subproblem */
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", nstallnodes) );
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", maxnodes) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );

   /* forbid recursive call of heuristics and separators solving sub-SCIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );

   /* use best estimate node selection */
   if( SCIPfindNodesel(scip, "estimate") != NULL )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
   }

   /* use inference branching */
   if( SCIPfindBranchrule(scip, "inference") != NULL )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
   }

   /* disable conflict analysis */
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
   SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );


#ifdef SCIP_DEBUG
   /* for debugging RENS, enable MIP output */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
   SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
#endif


   /* if the subproblem could not be created, free memory and return */
   if( !success )
   {
      *result = SCIP_DIDNOTRUN;
      SCIPfreeBufferArray(scip, &subvars);
      SCIP_CALL( SCIPfree(&subscip) );
      return SCIP_OKAY;
   }

   /* if there is already a solution, add an objective cutoff */
   if( SCIPgetNSols(scip) > 0 )
   {
      SCIP_Real upperbound;
      assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );

      upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);

      if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
      {
         cutoff = (1-minimprove)*SCIPgetUpperbound(scip) + minimprove*SCIPgetLowerbound(scip);
      }
      else
      {
         if( SCIPgetUpperbound ( scip ) >= 0 )
            cutoff = ( 1 - minimprove ) * SCIPgetUpperbound ( scip );
         else
            cutoff = ( 1 + minimprove ) * SCIPgetUpperbound ( scip );
      }
      cutoff = MIN(upperbound, cutoff);
      SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );
   }

   /* presolve the subproblem */
   retcode = SCIPpresolve(subscip);

   /* Errors in solving the subproblem should not kill the overall solving process
    * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
    */
   if( retcode != SCIP_OKAY )
   {
#ifndef NDEBUG
      SCIP_CALL( retcode );
#endif
      SCIPwarningMessage(scip, "Error while presolving subproblem in GCG RENS heuristic; sub-SCIP terminated with code <%d>\n",retcode);
   }

   SCIPdebugMessage("GCG RENS presolved subproblem: %d vars, %d cons, success=%u\n", SCIPgetNVars(subscip), SCIPgetNConss(subscip), success);

   /* after presolving, we should have at least reached a certain fixing rate over ALL variables (including continuous)
    * to ensure that not only the MIP but also the LP relaxation is easy enough
    */
   if( ( nvars - SCIPgetNVars(subscip) ) / (SCIP_Real)nvars >= minfixingrate / 2.0 )
   {
      SCIP_SOL** subsols;
      int nsubsols;

      /* solve the subproblem */
      SCIPdebugMessage("solving subproblem: nstallnodes=%"SCIP_LONGINT_FORMAT", maxnodes=%"SCIP_LONGINT_FORMAT"\n", nstallnodes, maxnodes);
      retcode = SCIPsolve(subscip);

      /* Errors in solving the subproblem should not kill the overall solving process
       * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
       */
      if( retcode != SCIP_OKAY )
      {
#ifndef NDEBUG
         SCIP_CALL( retcode );
#endif
         SCIPwarningMessage(scip, "Error while solving subproblem in GCG RENS heuristic; sub-SCIP terminated with code <%d>\n",retcode);
      }

      /* check, whether a solution was found;
       * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
       */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      success = FALSE;
      for( i = 0; i < nsubsols && !success; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
      }
      if( success )
         *result = SCIP_FOUNDSOL;
   }

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
/** reduced cost pricing method of variable pricer for feasible LPs */
static
SCIP_DECL_PRICERREDCOST(pricerRedcostBinpacking) { /*lint --e{715}*/
    SCIP* subscip;
    SCIP_PRICERDATA* pricerdata;
    SCIP_CONS** conss;
    SCIP_VAR** vars;
    int* ids;
    SCIP_Bool addvar;

    SCIP_SOL** sols;
    int nsols;
    int s;

    int nitems;
    SCIP_Longint* values;
    SCIP_Longint* weights;
    SCIP_Longint* capacities;
    int nbins;
    int b;

    SCIP_Real timelimit;
    SCIP_Real memorylimit;

    SCIP_Real dualHallBound;

    assert(scip != NULL);
    assert(pricer != NULL);

    (*result) = SCIP_DIDNOTRUN;

    /* get the pricer data */
    pricerdata = SCIPpricerGetData(pricer);
    assert(pricerdata != NULL);

    capacities = pricerdata->capacities;
    conss = pricerdata->conss;
    ids = pricerdata->ids;
    values = pricerdata->values;
    weights = pricerdata->weights;
    nitems = pricerdata->nitems;
    nbins = pricerdata->nbins;

    dualHallBound = 0.0;

    // run pricing problem for each bin
    for (b = 0; b < nbins; ++b) {

        // assert(SCIPgetDualsolLinear(scip, conss[nitems+b])<= 0);
        // TODO edit if correct objsense
        dualHallBound -= SCIPgetDualsolLinear(scip, conss[nitems+b]);

        if (b < nbins-1 && capacities[b+1] == capacities[b])
            continue;

        /* get the remaining time and memory limit */
        SCIP_CALL(SCIPgetRealParam(scip, "limits/time", &timelimit));
        if (!SCIPisInfinity(scip, timelimit))
            timelimit -= SCIPgetSolvingTime(scip);
        SCIP_CALL(SCIPgetRealParam(scip, "limits/memory", &memorylimit));
        if (!SCIPisInfinity(scip, memorylimit))
            memorylimit -= SCIPgetMemUsed(scip) / 1048576.0;

        /* initialize SCIP */
        SCIP_CALL(SCIPcreate(&subscip));
        SCIP_CALL(SCIPincludeDefaultPlugins(subscip));

        /* free sub SCIP */
        SCIP_CALL(SCIPcreateProb(subscip, "pricing", NULL, NULL, NULL, NULL, NULL, NULL, NULL));
        SCIP_CALL(SCIPsetObjsense(subscip, SCIP_OBJSENSE_MAXIMIZE));

        /* do not abort subproblem on CTRL-C */
        SCIP_CALL(SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE));

        /* disable output to console */
        SCIP_CALL(SCIPsetIntParam(subscip, "display/verblevel", 0));

        /* set time and memory limit */
        SCIP_CALL(SCIPsetRealParam(subscip, "limits/time", timelimit));
        SCIP_CALL(SCIPsetRealParam(subscip, "limits/memory", memorylimit));

        SCIP_CALL(SCIPallocMemoryArray(subscip, &vars, nitems));

        /* initialization local pricing problem */
        SCIP_CALL(initPricing(scip, pricerdata, subscip, vars, b));

        SCIPdebugMessage("solve pricer problem\n");

        /* solve sub SCIP */
        SCIP_CALL(SCIPsolve(subscip));

        sols = SCIPgetSols(subscip);
        nsols = SCIPgetNSols(subscip);
        addvar = FALSE;

        /* loop over all solutions and create the corresponding column to master if the reduced cost are negative for master,
         * that is the objective value i greater than 1.0
         */
        for (s = 0; s < nsols; ++s) {
            SCIP_Bool feasible;
            SCIP_SOL* sol;

            /* the soultion should be sorted w.r.t. the objective function value */
            assert(s == 0 || SCIPisFeasGE(subscip, SCIPgetSolOrigObj(subscip, sols[s - 1]), SCIPgetSolOrigObj(subscip, sols[s])));

            sol = sols[s];
            assert(sol != NULL);

            /* check if solution is feasible in original sub SCIP */
            SCIP_CALL(SCIPcheckSolOrig(subscip, sol, &feasible, FALSE, FALSE));

            if (!feasible) {
                SCIPwarningMessage("solution in pricing problem (capacity <%d>) is infeasible\n", capacities[b]);
                continue;
            }

            /* check if the solution has a value greater than 1.0 */
            // First subscip?
            if (SCIPisFeasGT(scip, SCIPgetSolOrigObj(subscip, sol), dualHallBound)) {
                SCIP_VAR* var;
                SCIP_VARDATA* vardata;
                int* consids;
                char strtmp[SCIP_MAXSTRLEN];
                char name[SCIP_MAXSTRLEN];
                int nconss;
                int o;
                int v;
                SCIP_Longint totalvalue;
                SCIP_Longint totalweight;

                SCIPdebug(SCIP_CALL(SCIPprintSol(subscip, sol, NULL, FALSE)));

                nconss = 0;
                totalvalue = 0.0;
                totalweight = 0.0;
                (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "items");

                SCIP_CALL(SCIPallocBufferArray(scip, &consids, nitems));

                /* check which variables are fixed -> which item belongs to this packing */
                for (o = 0, v = 0; o < nitems; ++o) {
                    if (!SCIPconsIsEnabled(conss[o]))
                        continue;

                    assert(SCIPgetNFixedonesSetppc(scip, conss[o]) == 0);

                    if (SCIPgetSolVal(subscip, sol, vars[v]) > 0.5) {
                        (void) SCIPsnprintf(strtmp, SCIP_MAXSTRLEN, "_%d", ids[o]);
                        strcat(name, strtmp);

                        consids[nconss] = o;
                        totalvalue+= values[o];
                        totalweight += weights[o];
                        nconss++;
                    } else
                        assert(SCIPisFeasEQ(subscip, SCIPgetSolVal(subscip, sol, vars[v]), 0.0));

                    v++;
                }

                SCIP_CALL(SCIPvardataCreateBinpacking(scip, &vardata, consids, nconss));

                /* create variable for a new column with objective function coefficient 0.0 */
                SCIP_CALL(SCIPcreateVarBinpacking(scip, &var, name, -totalvalue, FALSE, TRUE, vardata));

                /* add the new variable to the pricer store */
                SCIP_CALL(SCIPaddPricedVar(scip, var, 1.0));
                addvar = TRUE;

                /* change the upper bound of the binary variable to lazy since the upper bound is already enforced due to
                 * the objective function the set covering constraint; The reason for doing is that, is to avoid the bound
                 * of x <= 1 in the LP relaxation since this bound constraint would produce a dual variable which might have
                 * a positive reduced cost
                 */
                SCIP_CALL(SCIPchgVarUbLazy(scip, var, 1.0));

                /* check which variable are fixed -> which orders belong to this packing */
                for (v = 0; v < nconss; v++) {
                    assert(SCIPconsIsEnabled(conss[consids[v]]));
                    SCIP_CALL(SCIPaddCoefSetppc(scip, conss[consids[v]], var));
                }

                /* add variable to hall constraints */
                for (v = 0; v <= b; v++) {
                    SCIP_CALL(SCIPaddCoefLinear(scip, conss[nitems+v], var, 1.0));
                    if (totalweight <= capacities[v] && v < b && capacities[b] != capacities[b+1])
                        break;
                }

                SCIPdebug(SCIPprintVar(scip, var, NULL));
                SCIP_CALL(SCIPreleaseVar(scip, &var));

                SCIPfreeBufferArray(scip, &consids);
            } else
                break;
        }

        /* free pricer MIP */
        SCIPfreeMemoryArray(subscip, &vars);

        if (addvar || SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL)
            (*result) = SCIP_SUCCESS;

        /* free sub SCIP */
        SCIP_CALL(SCIPfree(&subscip));
    }

    return SCIP_OKAY;
}
Пример #3
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecLocalbranching)
{  /*lint --e{715}*/
   SCIP_Longint maxnnodes;                   /* maximum number of subnodes                            */
   SCIP_Longint nsubnodes;                   /* nodelimit for subscip                                 */

   SCIP_HEURDATA* heurdata;
   SCIP* subscip;                            /* the subproblem created by localbranching              */
   SCIP_VAR** subvars;                       /* subproblem's variables                                */
   SCIP_SOL* bestsol;                        /* best solution so far                                  */
   SCIP_EVENTHDLR*       eventhdlr;          /* event handler for LP events                     */

   SCIP_Real timelimit;                      /* timelimit for subscip (equals remaining time of scip) */
   SCIP_Real cutoff;                         /* objective cutoff for the subproblem                   */
   SCIP_Real upperbound;
   SCIP_Real memorylimit;

   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */
   SCIP_VAR** vars;

   int nvars;
   int i;

   SCIP_Bool success;

   SCIP_RETCODE retcode;

   assert(heur != NULL);
   assert(scip != NULL);
   assert(result != NULL);

   *result = SCIP_DIDNOTRUN;

   /* get heuristic's data */
   heurdata = SCIPheurGetData(heur);
   assert( heurdata != NULL );

   /* there should be enough binary variables that a local branching constraint makes sense */
   if( SCIPgetNBinVars(scip) < 2*heurdata->neighborhoodsize )
      return SCIP_OKAY;

   *result = SCIP_DELAYED;

   /* only call heuristic, if an IP solution is at hand */
   if( SCIPgetNSols(scip) <= 0  )
      return SCIP_OKAY;

   bestsol = SCIPgetBestSol(scip);
   assert(bestsol != NULL);

   /* only call heuristic, if the best solution comes from transformed problem */
   if( SCIPsolIsOriginal(bestsol) )
      return SCIP_OKAY;

   /* only call heuristic, if enough nodes were processed since last incumbent */
   if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip, bestsol)  < heurdata->nwaitingnodes)
      return SCIP_OKAY;

   /* only call heuristic, if the best solution does not come from trivial heuristic */
   if( SCIPsolGetHeur(bestsol) != NULL && strcmp(SCIPheurGetName(SCIPsolGetHeur(bestsol)), "trivial") == 0 )
      return SCIP_OKAY;

   /* reset neighborhood and minnodes, if new solution was found */
   if( heurdata->lastsol != bestsol )
   {
      heurdata->curneighborhoodsize = heurdata->neighborhoodsize;
      heurdata->curminnodes = heurdata->minnodes;
      heurdata->emptyneighborhoodsize = 0;
      heurdata->callstatus = EXECUTE;
      heurdata->lastsol = bestsol;
   }

   /* if no new solution was found and local branching also seems to fail, just keep on waiting */
   if( heurdata->callstatus == WAITFORNEWSOL )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

   /* calculate the maximal number of branching nodes until heuristic is aborted */
   maxnnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));

   /* reward local branching if it succeeded often */
   maxnnodes = (SCIP_Longint)(maxnnodes * (1.0 + 2.0*(SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur)+1.0)));
   maxnnodes -= 100 * SCIPheurGetNCalls(heur);  /* count the setup costs for the sub-MIP as 100 nodes */
   maxnnodes += heurdata->nodesofs;

   /* determine the node limit for the current process */
   nsubnodes = maxnnodes - heurdata->usednodes;
   nsubnodes = MIN(nsubnodes, heurdata->maxnodes);

   /* check whether we have enough nodes left to call sub problem solving */
   if( nsubnodes < heurdata->curminnodes )
      return SCIP_OKAY;

   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   SCIPdebugMessage("running localbranching heuristic ...\n");

   /* get the data of the variables and the best solution */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* initializing the subproblem */
   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
   SCIP_CALL( SCIPcreate(&subscip) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   success = FALSE;
   eventhdlr = NULL;

   if( heurdata->uselprows )
   {
      char probname[SCIP_MAXSTRLEN];

      /* copy all plugins */
      SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );

      /* get name of the original problem and add the string "_localbranchsub" */
      (void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_localbranchsub", SCIPgetProbName(scip));

      /* create the subproblem */
      SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );

      /* copy all variables */
      SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
   }
   else
   {
      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "localbranchsub", TRUE, FALSE, TRUE, &success) );

      if( heurdata->copycuts )
      {
         /* copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
         SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
      }

      /* create event handler for LP events */
      SCIP_CALL( SCIPincludeEventhdlrBasic(subscip, &eventhdlr, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecLocalbranching, NULL) );
      if( eventhdlr == NULL )
      {
         SCIPerrorMessage("event handler for "HEUR_NAME" heuristic not found.\n");
         return SCIP_PLUGINNOTFOUND;
      }
   }
   SCIPdebugMessage("Copying the plugins was %ssuccessful.\n", success ? "" : "not ");

   for (i = 0; i < nvars; ++i)
      subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);

   /* free hash map */
   SCIPhashmapFree(&varmapfw);

   /* if the subproblem could not be created, free memory and return */
   if( !success )
   {
      *result = SCIP_DIDNOTRUN;
      goto TERMINATE;
   }

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

#ifndef SCIP_DEBUG
   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
#endif

   /* check whether there is enough time and memory left */
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );

   /* substract the memory already used by the main SCIP and the estimated memory usage of external software */
   if( !SCIPisInfinity(scip, memorylimit) )
   {
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
      memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
   }

   /* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
   if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
      goto TERMINATE;

   /* set limits for the subproblem */
   heurdata->nodelimit = nsubnodes;
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nsubnodes) );
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", MAX(10, nsubnodes/10)) );
   SCIP_CALL( SCIPsetIntParam(subscip, "limits/bestsol", 3) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );

   /* forbid recursive call of heuristics and separators solving subMIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );

   /* use best estimate node selection */
   if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
   }

   /* use inference branching */
   if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
   }

   /* disable conflict analysis */
   if( !SCIPisParamFixed(subscip, "conflict/useprop") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usesb") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
   }

   /* employ a limit on the number of enforcement rounds in the quadratic constraint handler; this fixes the issue that
    * sometimes the quadratic constraint handler needs hundreds or thousands of enforcement rounds to determine the
    * feasibility status of a single node without fractional branching candidates by separation (namely for uflquad
    * instances); however, the solution status of the sub-SCIP might get corrupted by this; hence no deductions shall be
    * made for the original SCIP
    */
   if( SCIPfindConshdlr(subscip, "quadratic") != NULL && !SCIPisParamFixed(subscip, "constraints/quadratic/enfolplimit") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "constraints/quadratic/enfolplimit", 500) );
   }

   /* copy the original problem and add the local branching constraint */
   if( heurdata->uselprows )
   {
      SCIP_CALL( createSubproblem(scip, subscip, subvars) );
   }
   SCIP_CALL( addLocalBranchingConstraint(scip, subscip, subvars, heurdata) );

   /* add an objective cutoff */
   cutoff = SCIPinfinity(scip);
   assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );

   upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
   if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
   {
      cutoff = (1-heurdata->minimprove)*SCIPgetUpperbound(scip) + heurdata->minimprove*SCIPgetLowerbound(scip);
   }
   else
   {
      if( SCIPgetUpperbound ( scip ) >= 0 )
         cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
      else
         cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
   }
   cutoff = MIN(upperbound, cutoff );
   SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );

   /* catch LP events of sub-SCIP */
   if( !heurdata->uselprows )
   {
      assert(eventhdlr != NULL);

      SCIP_CALL( SCIPtransformProb(subscip) );
      SCIP_CALL( SCIPcatchEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, NULL) );
   }

   /* solve the subproblem */
   SCIPdebugMessage("solving local branching subproblem with neighborhoodsize %d and maxnodes %"SCIP_LONGINT_FORMAT"\n",
      heurdata->curneighborhoodsize, nsubnodes);
   retcode = SCIPsolve(subscip);

   /* drop LP events of sub-SCIP */
   if( !heurdata->uselprows )
   {
      assert(eventhdlr != NULL);

      SCIP_CALL( SCIPdropEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, -1) );
   }

   /* Errors in solving the subproblem should not kill the overall solving process
    * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
    */
   if( retcode != SCIP_OKAY )
   {
#ifndef NDEBUG
      SCIP_CALL( retcode );
#endif
      SCIPwarningMessage(scip, "Error while solving subproblem in local branching heuristic; sub-SCIP terminated with code <%d>\n",retcode);
   }

   /* print solving statistics of subproblem if we are in SCIP's debug mode */
   SCIPdebug( SCIP_CALL( SCIPprintStatistics(subscip, NULL) ) );

   heurdata->usednodes += SCIPgetNNodes(subscip);
   SCIPdebugMessage("local branching used %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT" nodes\n",
      SCIPgetNNodes(subscip), nsubnodes);

   /* check, whether a solution was found */
   if( SCIPgetNSols(subscip) > 0 )
   {
      SCIP_SOL** subsols;
      int nsubsols;

      /* check, whether a solution was found;
       * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
       */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      success = FALSE;
      for( i = 0; i < nsubsols && !success; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
      }
      if( success )
      {
         SCIPdebugMessage("-> accepted solution of value %g\n", SCIPgetSolOrigObj(subscip, subsols[i]));
         *result = SCIP_FOUNDSOL;
      }
   }

   /* check the status of the sub-MIP */
   switch( SCIPgetStatus(subscip) )
   {
   case SCIP_STATUS_OPTIMAL:
   case SCIP_STATUS_BESTSOLLIMIT:
      heurdata->callstatus = WAITFORNEWSOL; /* new solution will immediately be installed at next call */
      SCIPdebugMessage(" -> found new solution\n");
      break;

   case SCIP_STATUS_NODELIMIT:
   case SCIP_STATUS_STALLNODELIMIT:
   case SCIP_STATUS_TOTALNODELIMIT:
      heurdata->callstatus = EXECUTE;
      heurdata->curneighborhoodsize = (heurdata->emptyneighborhoodsize + heurdata->curneighborhoodsize)/2;
      heurdata->curminnodes *= 2;
      SCIPdebugMessage(" -> node limit reached: reduced neighborhood to %d, increased minnodes to %d\n",
         heurdata->curneighborhoodsize, heurdata->curminnodes);
      if( heurdata->curneighborhoodsize <= heurdata->emptyneighborhoodsize )
      {
         heurdata->callstatus = WAITFORNEWSOL;
         SCIPdebugMessage(" -> new neighborhood was already proven to be empty: wait for new solution\n");
      }
      break;

   case SCIP_STATUS_INFEASIBLE:
   case SCIP_STATUS_INFORUNBD:
      heurdata->emptyneighborhoodsize = heurdata->curneighborhoodsize;
      heurdata->curneighborhoodsize += heurdata->curneighborhoodsize/2;
      heurdata->curneighborhoodsize = MAX(heurdata->curneighborhoodsize, heurdata->emptyneighborhoodsize + 2);
      heurdata->callstatus = EXECUTE;
      SCIPdebugMessage(" -> neighborhood is empty: increased neighborhood to %d\n", heurdata->curneighborhoodsize);
      break;

   case SCIP_STATUS_UNKNOWN:
   case SCIP_STATUS_USERINTERRUPT:
   case SCIP_STATUS_TIMELIMIT:
   case SCIP_STATUS_MEMLIMIT:
   case SCIP_STATUS_GAPLIMIT:
   case SCIP_STATUS_SOLLIMIT:
   case SCIP_STATUS_UNBOUNDED:
   default:
      heurdata->callstatus = WAITFORNEWSOL;
      SCIPdebugMessage(" -> unexpected sub-MIP status <%d>: waiting for new solution\n", SCIPgetStatus(subscip));
      break;
   }

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecCrossover)
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;                  /* primal heuristic data                               */
   SCIP* subscip;                            /* the subproblem created by crossover                 */
   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */

   SCIP_VAR** vars;                          /* original problem's variables                        */
   SCIP_VAR** subvars;                       /* subproblem's variables                              */
   SCIP_SOL** sols;

   SCIP_Real memorylimit;                    /* memory limit for the subproblem                     */
   SCIP_Real timelimit;                      /* time limit for the subproblem                       */
   SCIP_Real cutoff;                         /* objective cutoff for the subproblem                 */
   SCIP_Real upperbound;
   SCIP_Bool success;

   SCIP_Longint nstallnodes;                 /* node limit for the subproblem                       */

   int* selection;                           /* pool of solutions crossover uses                    */
   int nvars;                                /* number of original problem's variables              */
   int nbinvars;
   int nintvars;
   int nusedsols;
   int i;

   SCIP_RETCODE retcode;

   assert(heur != NULL);
   assert(scip != NULL);
   assert(result != NULL);

   /* get heuristic's data */
   heurdata = SCIPheurGetData(heur);
   assert(heurdata != NULL);
   nusedsols = heurdata->nusedsols;

   *result = SCIP_DELAYED;

   /* only call heuristic, if enough solutions are at hand */
   if( SCIPgetNSols(scip) < nusedsols  )
      return SCIP_OKAY;

   sols = SCIPgetSols(scip);
   assert(sols != NULL);

   /* if one good solution was found, heuristic should not be delayed any longer */
   if( sols[nusedsols-1] != heurdata->prevlastsol )
   {
      heurdata->nextnodenumber = SCIPgetNNodes(scip);
      if( sols[0] != heurdata->prevbestsol )
         heurdata->nfailures = 0;
   }
   /* in nonrandomized mode: only recall heuristic, if at least one new good solution was found in the meantime */
   else if( !heurdata->randomization )
      return SCIP_OKAY;

   /* if heuristic should be delayed, wait until certain number of nodes is reached */
   if( SCIPgetNNodes(scip) < heurdata->nextnodenumber )
      return SCIP_OKAY;

   /* only call heuristic, if enough nodes were processed since last incumbent */
   if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip))  < heurdata->nwaitingnodes
      && (SCIPgetDepth(scip) > 0 || !heurdata->dontwaitatroot) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

   /* calculate the maximal number of branching nodes until heuristic is aborted */
   nstallnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));

   /* reward Crossover if it succeeded often */
   nstallnodes = (SCIP_Longint)
      (nstallnodes * (1.0 + 2.0*(SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur)+1.0)));

   /* count the setup costs for the sub-MIP as 100 nodes */
   nstallnodes -= 100 * SCIPheurGetNCalls(heur);
   nstallnodes += heurdata->nodesofs;

   /* determine the node limit for the current process */
   nstallnodes -= heurdata->usednodes;
   nstallnodes = MIN(nstallnodes, heurdata->maxnodes);

   /* check whether we have enough nodes left to call subproblem solving */
   if( nstallnodes < heurdata->minnodes )
      return SCIP_OKAY;

   if( SCIPisStopped(scip) )
     return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
   assert(nvars > 0);

   /* check whether discrete variables are available */
   if( nbinvars == 0 && nintvars == 0 )
      return SCIP_OKAY;

   /* initializing the subproblem */
   SCIP_CALL( SCIPcreate(&subscip) );

   /* create the variable mapping hash map */
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   success = FALSE;

   if( heurdata->uselprows )
   {
      char probname[SCIP_MAXSTRLEN];

      /* copy all plugins */
      SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );

      /* get name of the original problem and add the string "_crossoversub" */
      (void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_crossoversub", SCIPgetProbName(scip));

      /* create the subproblem */
      SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );

      /* copy all variables */
      SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
   }
   else
   {
      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "crossover", TRUE, FALSE, TRUE, &success) );

      if( heurdata->copycuts )
      {
         /** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
         SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
      }
   }

   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &selection, nusedsols) );

   for( i = 0; i < nvars; i++ )
     subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);

   /* free hash map */
   SCIPhashmapFree(&varmapfw);

   success = FALSE;

   /* create a new problem, which fixes variables with same value in a certain set of solutions */
   SCIP_CALL( setupSubproblem(scip, subscip, subvars, selection, heurdata, &success) );

   heurdata->prevbestsol = SCIPgetBestSol(scip);
   heurdata->prevlastsol = sols[heurdata->nusedsols-1];

   /* if creation of sub-SCIP was aborted (e.g. due to number of fixings), free sub-SCIP and abort */
   if( !success )
   {
      *result = SCIP_DIDNOTRUN;

      /* this run will be counted as a failure since no new solution tuple could be generated or the neighborhood of the
       * solution was not fruitful in the sense that it was too big
       */
      updateFailureStatistic(scip, heurdata);

      goto TERMINATE;
   }

   /* do not abort subproblem on CTRL-C */
   SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );

   /* disable output to console */
   SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );

   /* check whether there is enough time and memory left */
   SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
   if( !SCIPisInfinity(scip, timelimit) )
      timelimit -= SCIPgetSolvingTime(scip);
   SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );

   /* substract the memory already used by the main SCIP and the estimated memory usage of external software */
   if( !SCIPisInfinity(scip, memorylimit) )
   {
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
      memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
   }

   /* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
   if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
      goto TERMINATE;

   /* set limits for the subproblem */
   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nstallnodes) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );

   /* forbid recursive call of heuristics and separators solving subMIPs */
   SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );

   /* disable cutting plane separation */
   SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );

   /* disable expensive presolving */
   SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );

   /* use best estimate node selection */
   if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
   }

   /* use inference branching */
   if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
   }

   /* disable conflict analysis */
   if( !SCIPisParamFixed(subscip, "conflict/useprop") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usesb") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
   }
   if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
   {
      SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
   }

   /* add an objective cutoff */
   cutoff = SCIPinfinity(scip);
   assert(!SCIPisInfinity(scip, SCIPgetUpperbound(scip)));

   upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
   if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
   {
      cutoff = (1-heurdata->minimprove)*SCIPgetUpperbound(scip) + heurdata->minimprove*SCIPgetLowerbound(scip);
   }
   else
   {
      if( SCIPgetUpperbound ( scip ) >= 0 )
         cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
      else
         cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
   }
   cutoff = MIN(upperbound, cutoff );
   SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );

   /* permute the subproblem to increase diversification */
   if( heurdata->permute )
   {
      SCIP_CALL( SCIPpermuteProb(subscip, (unsigned int) SCIPheurGetNCalls(heur), TRUE, TRUE, TRUE, TRUE, TRUE) );
   }

   /* solve the subproblem */
   SCIPdebugMessage("Solve Crossover subMIP\n");
   retcode = SCIPsolve(subscip);

   /* Errors in solving the subproblem should not kill the overall solving process.
    * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop. */
   if( retcode != SCIP_OKAY )
   {
#ifndef NDEBUG
      SCIP_CALL( retcode );
#endif
      SCIPwarningMessage(scip, "Error while solving subproblem in Crossover heuristic; sub-SCIP terminated with code <%d>\n", retcode);
   }

   heurdata->usednodes += SCIPgetNNodes(subscip);

   /* check, whether a solution was found */
   if( SCIPgetNSols(subscip) > 0 )
   {
      SCIP_SOL** subsols;
      int nsubsols;
      int solindex;                             /* index of the solution created by crossover          */

      /* check, whether a solution was found;
       * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      success = FALSE;
      solindex = -1;
      for( i = 0; i < nsubsols && !success; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &solindex, &success) );
      }

      if( success )
      {
         int tmp;

         assert(solindex != -1);

         *result = SCIP_FOUNDSOL;

         /* insert all crossings of the new solution and (nusedsols-1) of its parents into the hashtable
          * in order to avoid incest ;)
          */
         for( i = 0; i < nusedsols; i++ )
         {
            SOLTUPLE* elem;
            tmp = selection[i];
            selection[i] = solindex;

            SCIP_CALL( createSolTuple(scip, &elem, selection, nusedsols, heurdata) );
            SCIP_CALL( SCIPhashtableInsert(heurdata->hashtable, elem) );
            selection[i] = tmp;
         }

         /* if solution was among the best ones, crossover should not be called until another good solution was found */
         if( !heurdata->randomization )
         {
            heurdata->prevbestsol = SCIPgetBestSol(scip);
            heurdata->prevlastsol = SCIPgetSols(scip)[heurdata->nusedsols-1];
         }
      }

      /* if solution is not better then incumbent or could not be added to problem => run is counted as a failure */
      if( !success || solindex != SCIPsolGetIndex(SCIPgetBestSol(scip)) )
         updateFailureStatistic(scip, heurdata);
   }
   else
   {
      /* if no new solution was found, run was a failure */
      updateFailureStatistic(scip, heurdata);
   }

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &selection);
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );

   return SCIP_OKAY;
}
Пример #5
0
static
SCIP_RETCODE run(
   const char*                nlfile,        /**< name of AMPL .nl file */
   const char*                setfile,       /**< SCIP settings file, or NULL to try default scip.set */
   SCIP_Bool                  interactive    /**< whether to start SCIP interactive shell instead of solving command */
)
{
   SCIP* scip;
   char buffer[SCIP_MAXSTRLEN];
   SCIP_Bool printstat;

   assert(nlfile != NULL);

   /* setup SCIP and print version information */
   SCIP_CALL( SCIPcreate(&scip) );

   SCIPprintVersion(scip, NULL);
   SCIPinfoMessage(scip, NULL, "\n");

   SCIP_CALL( SCIPincludeDefaultPlugins(scip) );
   SCIP_CALL( SCIPincludeReaderNl(scip) );

   SCIP_CALL( SCIPaddBoolParam(scip, "display/statistics",
      "whether to print statistics on a solve",
      NULL, FALSE, FALSE, NULL, NULL) );

   SCIPprintExternalCodes(scip, NULL);
   SCIPinfoMessage(scip, NULL, "\n");

   /* read setting file */
   if( setfile != NULL )
   {
      SCIP_CALL( SCIPreadParams(scip, setfile) );
   }

   SCIP_CALL( SCIPgetBoolParam(scip, "display/statistics", &printstat) );

   /* setup commands to be executed by SCIP */

   SCIP_CALL( SCIPaddDialogInputLine(scip, "display param") );

   /* add .nl extension, if not given */
   (void) SCIPsnprintf(buffer, SCIP_MAXSTRLEN, "read %s%s", nlfile, (strlen(nlfile) < 3 || strcmp(nlfile+(strlen(nlfile)-3), ".nl") != 0) ? ".nl" : "");
   SCIP_CALL( SCIPaddDialogInputLine(scip, buffer) );

   if( !interactive )
   {
      /* SCIP_CALL( SCIPaddDialogInputLine(scip, "display problem") ); */

      SCIP_CALL( SCIPaddDialogInputLine(scip, "optimize") );

      SCIP_CALL( SCIPaddDialogInputLine(scip, "write amplsol") );

      if( printstat )
      {
         SCIP_CALL( SCIPaddDialogInputLine(scip, "display statistics") );
      }

      SCIP_CALL( SCIPaddDialogInputLine(scip, "quit") );
   }

   /* run SCIP */
   SCIP_CALL( SCIPstartInteraction(scip) );

   SCIP_CALL( SCIPfree(&scip) );

   return SCIP_OKAY;
}
Пример #6
0
/** creates a SCIP instance with default plugins, evaluates command line parameters, runs SCIP appropriately,
 *  and frees the SCIP instance
 */
static
SCIP_RETCODE runSCIP(
   int                        argc,               /**< number of shell parameters */
   char**                     argv                /**< array with shell parameters */
   )
{
   SCIP* scip = NULL;


   /***********************
    * Version information *
    ***********************/

   SCIPprintVersion(NULL);
   std::cout << std::endl;


   /*********
    * Setup *
    *********/

   /* initialize SCIP */
   SCIP_CALL( SCIPcreate(&scip) );


   /* include default SCIP plugins */
   SCIP_CALL( SCIPincludeDefaultPlugins(scip) );


   /**************
    * Parameters *
    **************/

   if( argc >= 3 )
   {
      SCIP_CALL( readParams(scip, argv[2]) );
   }
   else
   {
      SCIP_CALL( readParams(scip, NULL) );
   }
   /*CHECK_OKAY( SCIPwriteParams(scip, "scipmip.set", TRUE) );*/


   /**************
    * Start SCIP *
    **************/

   if( argc >= 2 )
   {
      SCIP_CALL( fromCommandLine(scip, argv[1]) );
   }
   else
   {
      printf("\n");

      SCIP_CALL( interactive(scip) );
   }

   
   /********************
    * Deinitialization *
    ********************/

   SCIP_CALL( SCIPfree(&scip) );

   BMScheckEmptyMemory();

   return SCIP_OKAY;
}