Пример #1
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecZeroobj)
{  /*lint --e{715}*/

   SCIP_HEURDATA* heurdata;                  /* heuristic's data                    */
   SCIP_Longint nnodes;                 /* number of stalling nodes for the subproblem */

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

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

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

   /* reward zeroobj if it succeeded often */
   nnodes = (SCIP_Longint)(nnodes * 3.0 * (SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur) + 1.0));
   nnodes -= 100 * SCIPheurGetNCalls(heur);  /* count the setup costs for the sub-SCIP as 100 nodes */
   nnodes += heurdata->nodesofs;

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

   /* check whether we have enough nodes left to call subproblem solving */
   if( nnodes < heurdata->minnodes )
   {
      SCIPdebugMessage("skipping zeroobj: nnodes=%"SCIP_LONGINT_FORMAT", minnodes=%"SCIP_LONGINT_FORMAT"\n", nnodes, heurdata->minnodes);
      return SCIP_OKAY;
   }

   /* do not run zeroobj, if the problem does not have an objective function anyway */
   if( SCIPgetNObjVars(scip) == 0 )
   {
      SCIPdebugMessage("skipping zeroobj: pure feasibility problem anyway\n");
      return SCIP_OKAY;
   }

   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   SCIP_CALL( SCIPapplyZeroobj(scip, heur, result, heurdata->minimprove, nnodes) );

   return SCIP_OKAY;
}
Пример #2
0
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpIntobj)
{  /*lint --e{715}*/

   *result = SCIP_DIDNOTRUN;

   /* only call separator, if we are not close to terminating */
   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   /* only call separator, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call separator, if there are fractional variables */
   if( SCIPgetNLPBranchCands(scip) == 0 )
      return SCIP_OKAY;

   SCIP_CALL( separateCuts(scip, sepa, NULL, result) );

   return SCIP_OKAY;
}
Пример #3
0
/** perform randomized rounding of the given solution. Domain propagation is optionally applied after every rounding
 *  step
 */
static
SCIP_RETCODE performRandRounding(
   SCIP*                 scip,               /**< SCIP main data structure */
   SCIP_HEURDATA*        heurdata,           /**< heuristic data */
   SCIP_SOL*             sol,                /**< solution to round */
   SCIP_VAR**            cands,              /**< candidate variables */
   int                   ncands,             /**< number of candidates */
   SCIP_Bool             propagate,          /**< should the rounding be propagated? */
   SCIP_RESULT*          result              /**< pointer to store the result of the heuristic call */
   )
{
   int c;
   SCIP_Bool stored;
   SCIP_VAR** permutedcands;
   SCIP_Bool cutoff;

   assert(heurdata != NULL);

   /* start probing tree before rounding begins */
   if( propagate )
   {
      SCIP_CALL( SCIPstartProbing(scip) );
      SCIPenableVarHistory(scip);
   }

   /* copy and permute the candidate array */
   SCIP_CALL( SCIPduplicateBufferArray(scip, &permutedcands, cands, ncands) );

   assert(permutedcands != NULL);

   SCIPpermuteArray((void **)permutedcands, 0, ncands, &heurdata->randseed);
   cutoff = FALSE;

   /* loop over candidates and perform randomized rounding and optionally probing. */
   for (c = 0; c < ncands && !cutoff; ++c)
   {
      SCIP_VAR* var;
      SCIP_Real oldsolval;
      SCIP_Real newsolval;
      SCIP_Bool mayrounddown;
      SCIP_Bool mayroundup;
      SCIP_Longint ndomreds;
      SCIP_Real lb;
      SCIP_Real ub;
      SCIP_Real ceilval;
      SCIP_Real floorval;

      /* get next variable from permuted candidate array */
      var = permutedcands[c];
      oldsolval = SCIPgetSolVal(scip, sol, var);
      lb = SCIPvarGetLbLocal(var);
      ub = SCIPvarGetUbLocal(var);

      assert( ! SCIPisFeasIntegral(scip, oldsolval) );
      assert( SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN );

      mayrounddown = SCIPvarMayRoundDown(var);
      mayroundup = SCIPvarMayRoundUp(var);
      ceilval = SCIPfeasCeil(scip, oldsolval);
      floorval = SCIPfeasFloor(scip, oldsolval);

      SCIPdebugMessage("rand rounding heuristic: var <%s>, val=%g, rounddown=%u, roundup=%u\n",
         SCIPvarGetName(var), oldsolval, mayrounddown, mayroundup);

      /* abort if rounded ceil and floor value lie outside the variable domain. Otherwise, check if
       * bounds allow only one rounding direction, anyway */
      if( lb > ceilval + 0.5 || ub < floorval - 0.5 )
      {
         cutoff = TRUE;
         break;
      }
      else if( SCIPisFeasEQ(scip, lb, ceilval) )
      {
         /* only rounding up possible */
         assert(SCIPisFeasGE(scip, ub, ceilval));
         newsolval = ceilval;
      }
      else if( SCIPisFeasEQ(scip, ub, floorval) )
      {
         /* only rounding down possible */
         assert(SCIPisFeasLE(scip,lb, floorval));
         newsolval = floorval;
      }
      else if( !heurdata->usesimplerounding || !(mayroundup || mayrounddown) )
      {
         /* the standard randomized rounding */
         SCIP_Real randnumber;

         randnumber = SCIPgetRandomReal(0.0, 1.0, &heurdata->randseed);
         if( randnumber <= oldsolval - floorval )
            newsolval = ceilval;
         else
            newsolval = floorval;
      }
      /* choose rounding direction, if possible, or use the only direction guaranteed to be feasible */
      else if( mayrounddown && mayroundup )
      {
         /* we can round in both directions: round in objective function direction */
         if ( SCIPvarGetObj(var) >= 0.0 )
            newsolval = floorval;
         else
            newsolval = ceilval;
      }
      else if( mayrounddown )
         newsolval = floorval;
      else
      {
         assert(mayroundup);
         newsolval = ceilval;
      }

      assert(SCIPisFeasLE(scip, lb, newsolval));
      assert(SCIPisFeasGE(scip, ub, newsolval));

      /* if propagation is enabled, fix the candidate variable to its rounded value and propagate the solution */
      if( propagate )
      {
         SCIP_Bool lbadjust;
         SCIP_Bool ubadjust;

         lbadjust = SCIPisGT(scip, newsolval, lb);
         ubadjust = SCIPisLT(scip, newsolval, ub);

         assert( lbadjust || ubadjust || SCIPisFeasEQ(scip, lb, ub));

         /* enter a new probing node if the variable was not already fixed before */
         if( lbadjust || ubadjust )
         {
            SCIP_RETCODE retcode;

            if( SCIPisStopped(scip) )
               break;

            retcode = SCIPnewProbingNode(scip);
            if( retcode == SCIP_MAXDEPTHLEVEL )
               break;

            SCIP_CALL( retcode );

            /* tighten the bounds to fix the variable for the probing node */
            if( lbadjust )
            {
               SCIP_CALL( SCIPchgVarLbProbing(scip, var, newsolval) );
            }
            if( ubadjust )
            {
               SCIP_CALL( SCIPchgVarUbProbing(scip, var, newsolval) );
            }

            /* call propagation routines for the reduced problem */
            SCIP_CALL( SCIPpropagateProbing(scip, heurdata->maxproprounds, &cutoff, &ndomreds) );
         }
      }
      /* store new solution value */
      SCIP_CALL( SCIPsetSolVal(scip, sol, var, newsolval) );
   }

   /* if no cutoff was detected, the solution is a candidate to be checked for feasibility */
   if( !cutoff && ! SCIPisStopped(scip) )
   {
      if( SCIPallColsInLP(scip) )
      {
         /* check solution for feasibility, and add it to solution store if possible
          * neither integrality nor feasibility of LP rows has to be checked, because all fractional
          * variables were already moved in feasible direction to the next integer
          */
         SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );
      }
      else
      {
         /* if there are variables which are not present in the LP, e.g., for
          * column generation, we need to check their bounds
          */
         SCIP_CALL( SCIPtrySol(scip, sol, FALSE, TRUE, FALSE, TRUE, &stored) );
      }

      if( stored )
      {
#ifdef SCIP_DEBUG
         SCIPdebugMessage("found feasible rounded solution:\n");
         SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) );
#endif
         *result = SCIP_FOUNDSOL;
      }
   }

   assert( !propagate || SCIPinProbing(scip) );

   /* exit probing mode and free locally allocated memory */
   if( propagate )
   {
      SCIP_CALL( SCIPendProbing(scip) );
   }

   SCIPfreeBufferArray(scip, &permutedcands);

   return SCIP_OKAY;
}
Пример #4
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecActconsdiving) /*lint --e{715}*/
{   /*lint --e{715}*/
    SCIP_HEURDATA* heurdata;
    SCIP_LPSOLSTAT lpsolstat;
    SCIP_VAR* var;
    SCIP_VAR** lpcands;
    SCIP_Real* lpcandssol;
    SCIP_Real* lpcandsfrac;
    SCIP_Real searchubbound;
    SCIP_Real searchavgbound;
    SCIP_Real searchbound;
    SCIP_Real objval;
    SCIP_Real oldobjval;
    SCIP_Real frac;
    SCIP_Real bestfrac;
    SCIP_Bool bestcandmayrounddown;
    SCIP_Bool bestcandmayroundup;
    SCIP_Bool bestcandroundup;
    SCIP_Bool mayrounddown;
    SCIP_Bool mayroundup;
    SCIP_Bool roundup;
    SCIP_Bool lperror;
    SCIP_Bool cutoff;
    SCIP_Bool backtracked;
    SCIP_Longint ncalls;
    SCIP_Longint nsolsfound;
    SCIP_Longint nlpiterations;
    SCIP_Longint maxnlpiterations;
    int nlpcands;
    int startnlpcands;
    int depth;
    int maxdepth;
    int maxdivedepth;
    int divedepth;
    SCIP_Real actscore;
    SCIP_Real downscore;
    SCIP_Real upscore;
    SCIP_Real bestactscore;
    int bestcand;
    int c;

    assert(heur != NULL);
    assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
    assert(scip != NULL);
    assert(result != NULL);
    assert(SCIPhasCurrentNodeLP(scip));

    *result = SCIP_DELAYED;

    /* do not call heuristic of node was already detected to be infeasible */
    if( nodeinfeasible )
        return SCIP_OKAY;

    /* only call heuristic, if an optimal LP solution is at hand */
    if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
        return SCIP_OKAY;

    /* only call heuristic, if the LP objective value is smaller than the cutoff bound */
    if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
        return SCIP_OKAY;

    /* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
    if( !SCIPisLPSolBasic(scip) )
        return SCIP_OKAY;

    /* don't dive two times at the same node */
    if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
        return SCIP_OKAY;

    *result = SCIP_DIDNOTRUN;

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

    /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
    depth = SCIPgetDepth(scip);
    maxdepth = SCIPgetMaxDepth(scip);
    maxdepth = MAX(maxdepth, 30);
    if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
        return SCIP_OKAY;

    /* calculate the maximal number of LP iterations until heuristic is aborted */
    nlpiterations = SCIPgetNNodeLPIterations(scip);
    ncalls = SCIPheurGetNCalls(heur);
    nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
    maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
    maxnlpiterations += heurdata->maxlpiterofs;

    /* don't try to dive, if we took too many LP iterations during diving */
    if( heurdata->nlpiterations >= maxnlpiterations )
        return SCIP_OKAY;

    /* allow at least a certain number of LP iterations in this dive */
    maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);

    /* get fractional variables that should be integral */
    SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );

    /* don't try to dive, if there are no fractional variables */
    if( nlpcands == 0 )
        return SCIP_OKAY;

    /* calculate the objective search bound */
    if( SCIPgetNSolsFound(scip) == 0 )
    {
        if( heurdata->maxdiveubquotnosol > 0.0 )
            searchubbound = SCIPgetLowerbound(scip)
                            + heurdata->maxdiveubquotnosol * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
        else
            searchubbound = SCIPinfinity(scip);
        if( heurdata->maxdiveavgquotnosol > 0.0 )
            searchavgbound = SCIPgetLowerbound(scip)
                             + heurdata->maxdiveavgquotnosol * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
        else
            searchavgbound = SCIPinfinity(scip);
    }
    else
    {
        if( heurdata->maxdiveubquot > 0.0 )
            searchubbound = SCIPgetLowerbound(scip)
                            + heurdata->maxdiveubquot * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
        else
            searchubbound = SCIPinfinity(scip);
        if( heurdata->maxdiveavgquot > 0.0 )
            searchavgbound = SCIPgetLowerbound(scip)
                             + heurdata->maxdiveavgquot * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
        else
            searchavgbound = SCIPinfinity(scip);
    }
    searchbound = MIN(searchubbound, searchavgbound);
    if( SCIPisObjIntegral(scip) )
        searchbound = SCIPceil(scip, searchbound);

    /* calculate the maximal diving depth: 10 * min{number of integer variables, max depth} */
    maxdivedepth = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
    maxdivedepth = MIN(maxdivedepth, maxdepth);
    maxdivedepth *= 10;

    *result = SCIP_DIDNOTFIND;

    /* start diving */
    SCIP_CALL( SCIPstartProbing(scip) );

    /* enables collection of variable statistics during probing */
    SCIPenableVarHistory(scip);

    /* get LP objective value */
    lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
    objval = SCIPgetLPObjval(scip);

    SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing actconsdiving heuristic: depth=%d, %d fractionals, dualbound=%g, avgbound=%g, cutoffbound=%g, searchbound=%g\n",
                     SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), SCIPgetAvgDualbound(scip),
                     SCIPretransformObj(scip, SCIPgetCutoffbound(scip)), SCIPretransformObj(scip, searchbound));

    /* dive as long we are in the given objective, depth and iteration limits and fractional variables exist, but
     * - if possible, we dive at least with the depth 10
     * - if the number of fractional variables decreased at least with 1 variable per 2 dive depths, we continue diving
     */
    lperror = FALSE;
    cutoff = FALSE;
    divedepth = 0;
    bestcandmayrounddown = FALSE;
    bestcandmayroundup = FALSE;
    startnlpcands = nlpcands;
    while( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0
            && (divedepth < 10
                || nlpcands <= startnlpcands - divedepth/2
                || (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations && objval < searchbound))
            && !SCIPisStopped(scip) )
    {
        divedepth++;
        SCIP_CALL( SCIPnewProbingNode(scip) );

        /* choose variable fixing:
         * - prefer variables that may not be rounded without destroying LP feasibility:
         *   - of these variables, round variable with least number of locks in corresponding direction
         * - if all remaining fractional variables may be rounded without destroying LP feasibility:
         *   - round variable with least number of locks in opposite of its feasible rounding direction
         */
        bestcand = -1;
        bestactscore = -1.0;
        bestfrac = SCIP_INVALID;
        bestcandmayrounddown = TRUE;
        bestcandmayroundup = TRUE;
        bestcandroundup = FALSE;
        for( c = 0; c < nlpcands; ++c )
        {
            var = lpcands[c];
            mayrounddown = SCIPvarMayRoundDown(var);
            mayroundup = SCIPvarMayRoundUp(var);
            frac = lpcandsfrac[c];
            if( mayrounddown || mayroundup )
            {
                /* the candidate may be rounded: choose this candidate only, if the best candidate may also be rounded */
                if( bestcandmayrounddown || bestcandmayroundup )
                {
                    /* choose rounding direction:
                     * - if variable may be rounded in both directions, round corresponding to the fractionality
                     * - otherwise, round in the infeasible direction, because feasible direction is tried by rounding
                     *   the current fractional solution
                     */
                    if( mayrounddown && mayroundup )
                        roundup = (frac > 0.5);
                    else
                        roundup = mayrounddown;

                    if( roundup )
                        frac = 1.0 - frac;
                    actscore = getNActiveConsScore(scip, var, &downscore, &upscore);

                    /* penalize too small fractions */
                    if( frac < 0.01 )
                        actscore *= 0.01;

                    /* prefer decisions on binary variables */
                    if( !SCIPvarIsBinary(var) )
                        actscore *= 0.01;

                    /* check, if candidate is new best candidate */
                    assert(0.0 < frac && frac < 1.0);
                    if( SCIPisGT(scip, actscore, bestactscore) || (SCIPisGE(scip, actscore, bestactscore) && frac < bestfrac) )
                    {
                        bestcand = c;
                        bestactscore = actscore;
                        bestfrac = frac;
                        bestcandmayrounddown = mayrounddown;
                        bestcandmayroundup = mayroundup;
                        bestcandroundup = roundup;
                    }
                }
            }
            else
            {
                /* the candidate may not be rounded */
                actscore = getNActiveConsScore(scip, var, &downscore, &upscore);
                roundup = (downscore < upscore);
                if( roundup )
                    frac = 1.0 - frac;

                /* penalize too small fractions */
                if( frac < 0.01 )
                    actscore *= 0.01;

                /* prefer decisions on binary variables */
                if( !SCIPvarIsBinary(var) )
                    actscore *= 0.01;

                /* check, if candidate is new best candidate: prefer unroundable candidates in any case */
                assert(0.0 < frac && frac < 1.0);
                if( bestcandmayrounddown || bestcandmayroundup || SCIPisGT(scip, actscore, bestactscore) ||
                        (SCIPisGE(scip, actscore, bestactscore) && frac < bestfrac) )
                {
                    bestcand = c;
                    bestactscore = actscore;
                    bestfrac = frac;
                    bestcandmayrounddown = FALSE;
                    bestcandmayroundup = FALSE;
                    bestcandroundup = roundup;
                }
                assert(bestfrac < SCIP_INVALID);
            }
        }
        assert(bestcand != -1);

        /* if all candidates are roundable, try to round the solution */
        if( bestcandmayrounddown || bestcandmayroundup )
        {
            SCIP_Bool success;

            /* create solution from diving LP and try to round it */
            SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
            SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );

            if( success )
            {
                SCIPdebugMessage("actconsdiving found roundable primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));

                /* try to add solution to SCIP */
                SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

                /* check, if solution was feasible and good enough */
                if( success )
                {
                    SCIPdebugMessage(" -> solution was feasible and good enough\n");
                    *result = SCIP_FOUNDSOL;
                }
            }
        }
        assert(bestcand != -1);
        var = lpcands[bestcand];

        backtracked = FALSE;
        do
        {
            /* if the variable is already fixed or if the solution value is outside the domain, numerical troubles may have
             * occured or variable was fixed by propagation while backtracking => Abort diving!
             */
            if( SCIPvarGetLbLocal(var) >= SCIPvarGetUbLocal(var) - 0.5 )
            {
                SCIPdebugMessage("Selected variable <%s> already fixed to [%g,%g] (solval: %.9f), diving aborted \n",
                                 SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), lpcandssol[bestcand]);
                cutoff = TRUE;
                break;
            }
            if( SCIPisFeasLT(scip, lpcandssol[bestcand], SCIPvarGetLbLocal(var)) || SCIPisFeasGT(scip, lpcandssol[bestcand], SCIPvarGetUbLocal(var)) )
            {
                SCIPdebugMessage("selected variable's <%s> solution value is outside the domain [%g,%g] (solval: %.9f), diving aborted\n",
                                 SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), lpcandssol[bestcand]);
                assert(backtracked);
                break;
            }

            /* apply rounding of best candidate */
            if( bestcandroundup == !backtracked )
            {
                /* round variable up */
                SCIPdebugMessage("  dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, oldbounds=[%g,%g], newbounds=[%g,%g]\n",
                                 divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
                                 SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
                                 lpcandssol[bestcand], SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var),
                                 SCIPfeasCeil(scip, lpcandssol[bestcand]), SCIPvarGetUbLocal(var));
                SCIP_CALL( SCIPchgVarLbProbing(scip, var, SCIPfeasCeil(scip, lpcandssol[bestcand])) );
            }
            else
            {
                /* round variable down */
                SCIPdebugMessage("  dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, oldbounds=[%g,%g], newbounds=[%g,%g]\n",
                                 divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
                                 SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
                                 lpcandssol[bestcand], SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var),
                                 SCIPvarGetLbLocal(var), SCIPfeasFloor(scip, lpcandssol[bestcand]));
                SCIP_CALL( SCIPchgVarUbProbing(scip, lpcands[bestcand], SCIPfeasFloor(scip, lpcandssol[bestcand])) );
            }

            /* apply domain propagation */
            SCIP_CALL( SCIPpropagateProbing(scip, 0, &cutoff, NULL) );
            if( !cutoff )
            {
                /* resolve the diving LP */
                /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
                 * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
                 */
#ifdef NDEBUG
                SCIP_RETCODE retstat;
                nlpiterations = SCIPgetNLPIterations(scip);
                retstat = SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff);
                if( retstat != SCIP_OKAY )
                {
                    SCIPwarningMessage(scip, "Error while solving LP in Actconsdiving heuristic; LP solve terminated with code <%d>\n",retstat);
                }
#else
                nlpiterations = SCIPgetNLPIterations(scip);
                SCIP_CALL( SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff) );
#endif

                if( lperror )
                    break;

                /* update iteration count */
                heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations;

                /* get LP solution status, objective value, and fractional variables, that should be integral */
                lpsolstat = SCIPgetLPSolstat(scip);
                assert(cutoff || (lpsolstat != SCIP_LPSOLSTAT_OBJLIMIT && lpsolstat != SCIP_LPSOLSTAT_INFEASIBLE &&
                                  (lpsolstat != SCIP_LPSOLSTAT_OPTIMAL || SCIPisLT(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)))));
            }

            /* perform backtracking if a cutoff was detected */
            if( cutoff && !backtracked && heurdata->backtrack )
            {
                SCIPdebugMessage("  *** cutoff detected at level %d - backtracking\n", SCIPgetProbingDepth(scip));
                SCIP_CALL( SCIPbacktrackProbing(scip, SCIPgetProbingDepth(scip)-1) );
                SCIP_CALL( SCIPnewProbingNode(scip) );
                backtracked = TRUE;
            }
            else
                backtracked = FALSE;
        }
        while( backtracked );

        if( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
        {
            /* get new objective value */
            oldobjval = objval;
            objval = SCIPgetLPObjval(scip);

            /* update pseudo cost values */
            if( SCIPisGT(scip, objval, oldobjval) )
            {
                if( bestcandroundup )
                {
                    SCIP_CALL( SCIPupdateVarPseudocost(scip, lpcands[bestcand], 1.0-lpcandsfrac[bestcand],
                                                       objval - oldobjval, 1.0) );
                }
                else
                {
                    SCIP_CALL( SCIPupdateVarPseudocost(scip, lpcands[bestcand], 0.0-lpcandsfrac[bestcand],
                                                       objval - oldobjval, 1.0) );
                }
            }

            /* get new fractional variables */
            SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );
        }
        SCIPdebugMessage("   -> lpsolstat=%d, objval=%g/%g, nfrac=%d\n", lpsolstat, objval, searchbound, nlpcands);
    }

    /* check if a solution has been found */
    if( nlpcands == 0 && !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
    {
        SCIP_Bool success;

        /* create solution from diving LP */
        SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
        SCIPdebugMessage("actconsdiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));

        /* try to add solution to SCIP */
        SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

        /* check, if solution was feasible and good enough */
        if( success )
        {
            SCIPdebugMessage(" -> solution was feasible and good enough\n");
            *result = SCIP_FOUNDSOL;
        }
    }

    /* end diving */
    SCIP_CALL( SCIPendProbing(scip) );

    if( *result == SCIP_FOUNDSOL )
        heurdata->nsuccess++;

    SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") finished actconsdiving heuristic: %d fractionals, dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT", objval=%g/%g, lpsolstat=%d, cutoff=%u\n",
                     SCIPgetNNodes(scip), nlpcands, divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
                     SCIPretransformObj(scip, objval), SCIPretransformObj(scip, searchbound), lpsolstat, cutoff);

    return SCIP_OKAY;
}
Пример #5
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecObjpscostdiving) /*lint --e{715}*/
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_LPSOLSTAT lpsolstat;
   SCIP_VAR* var;
   SCIP_VAR** lpcands;
   SCIP_Real* lpcandssol;
   SCIP_Real* lpcandsfrac;
   SCIP_Real primsol;
   SCIP_Real frac;
   SCIP_Real pscostquot;
   SCIP_Real bestpscostquot;
   SCIP_Real oldobj;
   SCIP_Real newobj;
   SCIP_Real objscale;
   SCIP_Bool bestcandmayrounddown;
   SCIP_Bool bestcandmayroundup;
   SCIP_Bool bestcandroundup;
   SCIP_Bool mayrounddown;
   SCIP_Bool mayroundup;
   SCIP_Bool roundup;
   SCIP_Bool lperror;
   SCIP_Longint ncalls;
   SCIP_Longint nsolsfound;
   SCIP_Longint nlpiterations;
   SCIP_Longint maxnlpiterations;
   int* roundings;
   int nvars;
   int varidx;
   int nlpcands;
   int startnlpcands;
   int depth;
   int maxdepth;
   int maxdivedepth;
   int divedepth;
   int bestcand;
   int c;

   assert(heur != NULL);
   assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);
   assert(SCIPhasCurrentNodeLP(scip));

   *result = SCIP_DELAYED;

   /* do not call heuristic of node was already detected to be infeasible */
   if( nodeinfeasible )
      return SCIP_OKAY;

   /* only call heuristic, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call heuristic, if the LP objective value is smaller than the cutoff bound */
   if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
      return SCIP_OKAY;

   /* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* don't dive two times at the same node */
   if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

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

   /* only apply heuristic, if only a few solutions have been found */
   if( heurdata->maxsols >= 0 && SCIPgetNSolsFound(scip) >= heurdata->maxsols )
      return SCIP_OKAY;

   /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
   depth = SCIPgetDepth(scip);
   maxdepth = SCIPgetMaxDepth(scip);
   maxdepth = MAX(maxdepth, 30);
   if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
      return SCIP_OKAY;

   /* calculate the maximal number of LP iterations until heuristic is aborted */
   nlpiterations = SCIPgetNNodeLPIterations(scip);
   ncalls = SCIPheurGetNCalls(heur);
   nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
   maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
   maxnlpiterations += heurdata->maxlpiterofs;

   /* don't try to dive, if we took too many LP iterations during diving */
   if( heurdata->nlpiterations >= maxnlpiterations )
      return SCIP_OKAY;

   /* allow at least a certain number of LP iterations in this dive */
   maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);

   /* get fractional variables that should be integral */
   SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );

   /* don't try to dive, if there are no fractional variables */
   if( nlpcands == 0 )
      return SCIP_OKAY;

   /* calculate the maximal diving depth */
   nvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
   if( SCIPgetNSolsFound(scip) == 0 )
      maxdivedepth = (int)(heurdata->depthfacnosol * nvars);
   else
      maxdivedepth = (int)(heurdata->depthfac * nvars);
   maxdivedepth = MIN(maxdivedepth, 10*maxdepth);


   *result = SCIP_DIDNOTFIND;

   /* get temporary memory for remembering the current soft roundings */
   SCIP_CALL( SCIPallocBufferArray(scip, &roundings, nvars) );
   BMSclearMemoryArray(roundings, nvars);

   /* start diving */
   SCIP_CALL( SCIPstartDive(scip) );

   SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing objpscostdiving heuristic: depth=%d, %d fractionals, dualbound=%g, maxnlpiterations=%"SCIP_LONGINT_FORMAT", maxdivedepth=%d\n",
      SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), maxnlpiterations, maxdivedepth);

   /* dive as long we are in the given diving depth and iteration limits and fractional variables exist, but
    * - if the last objective change was in a direction, that corresponds to a feasible rounding, we continue in any case
    * - if possible, we dive at least with the depth 10
    * - if the number of fractional variables decreased at least with 1 variable per 2 dive depths, we continue diving
    */
   lperror = FALSE;
   lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
   divedepth = 0;
   bestcandmayrounddown = FALSE;
   bestcandmayroundup = FALSE;
   startnlpcands = nlpcands;
   while( !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0
      && (divedepth < 10
         || nlpcands <= startnlpcands - divedepth/2
         || (divedepth < maxdivedepth && nlpcands <= startnlpcands - divedepth/10
            && heurdata->nlpiterations < maxnlpiterations)) && !SCIPisStopped(scip) )
   {
      SCIP_RETCODE retcode;

      divedepth++;

      /* choose variable for objective change:
       * - prefer variables that may not be rounded without destroying LP feasibility:
       *   - of these variables, change objective value of variable with largest rel. difference of pseudo cost values
       * - if all remaining fractional variables may be rounded without destroying LP feasibility:
       *   - change objective value of variable with largest rel. difference of pseudo cost values
       */
      bestcand = -1;
      bestpscostquot = -1.0;
      bestcandmayrounddown = TRUE;
      bestcandmayroundup = TRUE;
      bestcandroundup = FALSE;
      for( c = 0; c < nlpcands; ++c )
      {
         var = lpcands[c];
         mayrounddown = SCIPvarMayRoundDown(var);
         mayroundup = SCIPvarMayRoundUp(var);
         primsol = lpcandssol[c];
         frac = lpcandsfrac[c];
         if( mayrounddown || mayroundup )
         {
            /* the candidate may be rounded: choose this candidate only, if the best candidate may also be rounded */
            if( bestcandmayrounddown || bestcandmayroundup )
            {
               /* choose rounding direction:
                * - if variable may be rounded in both directions, round corresponding to the pseudo cost values
                * - otherwise, round in the infeasible direction, because feasible direction is tried by rounding
                *   the current fractional solution
                */
               roundup = FALSE;
               if( mayrounddown && mayroundup )
                  calcPscostQuot(scip, var, primsol, frac, 0, &pscostquot, &roundup);
               else if( mayrounddown )
                  calcPscostQuot(scip, var, primsol, frac, +1, &pscostquot, &roundup);
               else
                  calcPscostQuot(scip, var, primsol, frac, -1, &pscostquot, &roundup);

               /* prefer variables, that have already been soft rounded but failed to get integral */
               varidx = SCIPvarGetProbindex(var);
               assert(0 <= varidx && varidx < nvars);
               if( roundings[varidx] != 0 )
                  pscostquot *= 1000.0;

               /* check, if candidate is new best candidate */
               if( pscostquot > bestpscostquot )
               {
                  bestcand = c;
                  bestpscostquot = pscostquot;
                  bestcandmayrounddown = mayrounddown;
                  bestcandmayroundup = mayroundup;
                  bestcandroundup = roundup;
               }
            }
         }
         else
         {
            /* the candidate may not be rounded: calculate pseudo cost quotient and preferred direction */
            calcPscostQuot(scip, var, primsol, frac, 0, &pscostquot, &roundup);

            /* prefer variables, that have already been soft rounded but failed to get integral */
            varidx = SCIPvarGetProbindex(var);
            assert(0 <= varidx && varidx < nvars);
            if( roundings[varidx] != 0 )
               pscostquot *= 1000.0;

            /* check, if candidate is new best candidate: prefer unroundable candidates in any case */
            if( bestcandmayrounddown || bestcandmayroundup || pscostquot > bestpscostquot )
            {
               bestcand = c;
               bestpscostquot = pscostquot;
               bestcandmayrounddown = FALSE;
               bestcandmayroundup = FALSE;
               bestcandroundup = roundup;
            }
         }
      }
      assert(bestcand != -1);

      /* if all candidates are roundable, try to round the solution */
      if( bestcandmayrounddown || bestcandmayroundup )
      {
         SCIP_Bool success;

         /* create solution from diving LP and try to round it */
         SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
         SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );

         if( success )
         {
            SCIPdebugMessage("objpscostdiving found roundable primal solution: obj=%g\n",
               SCIPgetSolOrigObj(scip, heurdata->sol));

            /* try to add solution to SCIP */
            SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

            /* check, if solution was feasible and good enough */
            if( success )
            {
               SCIPdebugMessage(" -> solution was feasible and good enough\n");
               *result = SCIP_FOUNDSOL;
            }
         }
      }

      var = lpcands[bestcand];

      /* check, if the best candidate was already subject to soft rounding */
      varidx = SCIPvarGetProbindex(var);
      assert(0 <= varidx && varidx < nvars);
      if( roundings[varidx] == +1 )
      {
         /* variable was already soft rounded upwards: hard round it downwards */
         SCIP_CALL( SCIPchgVarUbDive(scip, var, SCIPfeasFloor(scip, lpcandssol[bestcand])) );
         SCIPdebugMessage("  dive %d/%d: var <%s>, round=%u/%u, sol=%g, was already soft rounded upwards -> bounds=[%g,%g]\n",
            divedepth, maxdivedepth, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
            lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var));
      }
      else if( roundings[varidx] == -1 )
      {
         /* variable was already soft rounded downwards: hard round it upwards */
         SCIP_CALL( SCIPchgVarLbDive(scip, var, SCIPfeasCeil(scip, lpcandssol[bestcand])) );
         SCIPdebugMessage("  dive %d/%d: var <%s>, round=%u/%u, sol=%g, was already soft rounded downwards -> bounds=[%g,%g]\n",
            divedepth, maxdivedepth, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
            lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var));
      }
      else
      {
         assert(roundings[varidx] == 0);

         /* apply soft rounding of best candidate via a change in the objective value */
         objscale = divedepth * 1000.0;
         oldobj = SCIPgetVarObjDive(scip, var);
         if( bestcandroundup )
         {
            /* soft round variable up: make objective value (more) negative */
            if( oldobj < 0.0 )
               newobj = objscale * oldobj;
            else
               newobj = -objscale * oldobj;
            newobj = MIN(newobj, -objscale);

            /* remember, that this variable was soft rounded upwards */
            roundings[varidx] = +1;
         }
         else
         {
            /* soft round variable down: make objective value (more) positive */
            if( oldobj > 0.0 )
               newobj = objscale * oldobj;
            else
               newobj = -objscale * oldobj;
            newobj = MAX(newobj, objscale);

            /* remember, that this variable was soft rounded downwards */
            roundings[varidx] = -1;
         }
         SCIP_CALL( SCIPchgVarObjDive(scip, var, newobj) );
         SCIPdebugMessage("  dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, bounds=[%g,%g], obj=%g, newobj=%g\n",
            divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
            SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
            lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var), oldobj, newobj);
      }

      /* resolve the diving LP */
      nlpiterations = SCIPgetNLPIterations(scip);
      retcode =  SCIPsolveDiveLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, NULL);
      lpsolstat = SCIPgetLPSolstat(scip);

      /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
       * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
       */
      if( retcode != SCIP_OKAY )
      {
#ifndef NDEBUG
         if( lpsolstat != SCIP_LPSOLSTAT_UNBOUNDEDRAY )
         {
            SCIP_CALL( retcode );
         }
#endif
         SCIPwarningMessage(scip, "Error while solving LP in Objpscostdiving heuristic; LP solve terminated with code <%d>\n", retcode);
         SCIPwarningMessage(scip, "This does not affect the remaining solution procedure --> continue\n");
      }

      if( lperror )
         break;

      /* update iteration count */
      heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations;

      /* get LP solution status  and fractional variables, that should be integral */
      if( lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
      {
         /* get new fractional variables */
         SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );
      }
      SCIPdebugMessage("   -> lpsolstat=%d, nfrac=%d\n", lpsolstat, nlpcands);
   }

   /* check if a solution has been found */
   if( nlpcands == 0 && !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
   {
      SCIP_Bool success;

      /* create solution from diving LP */
      SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
      SCIPdebugMessage("objpscostdiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));

      /* try to add solution to SCIP */
      SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

      /* check, if solution was feasible and good enough */
      if( success )
      {
         SCIPdebugMessage(" -> solution was feasible and good enough\n");
         *result = SCIP_FOUNDSOL;
      }
   }

   /* end diving */
   SCIP_CALL( SCIPendDive(scip) );

   if( *result == SCIP_FOUNDSOL )
      heurdata->nsuccess++;

   /* free temporary memory for remembering the current soft roundings */
   SCIPfreeBufferArray(scip, &roundings);

   SCIPdebugMessage("objpscostdiving heuristic finished\n");

   return SCIP_OKAY;
}
Пример #6
0
/** execution method of presolver */
static
SCIP_DECL_PRESOLEXEC(presolExecDualagg)
{  /*lint --e{715}*/
   SCIPMILPMATRIX* matrix;
   SCIP_Bool initialized;
   SCIP_Bool complete;

   assert(result != NULL);
   *result = SCIP_DIDNOTRUN;

   if( (SCIPgetStage(scip) != SCIP_STAGE_PRESOLVING) || SCIPinProbing(scip) || SCIPisNLPEnabled(scip) )
      return SCIP_OKAY;

   if( SCIPisStopped(scip) || SCIPgetNActivePricers(scip) > 0 )
      return SCIP_OKAY;

   if( SCIPgetNBinVars(scip) == 0 )
      return SCIP_OKAY;

   if( !SCIPallowDualReds(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   matrix = NULL;
   SCIP_CALL( SCIPmatrixCreate(scip, &matrix, &initialized, &complete) );

   /* we only work on pure MIPs currently */
   if( initialized && complete )
   {
      AGGRTYPE* aggtypes;
      SCIP_VAR** binvars;
      int nvaragg;
      int ncols;

      ncols = SCIPmatrixGetNColumns(matrix);
      nvaragg = 0;

      SCIP_CALL( SCIPallocBufferArray(scip, &aggtypes, ncols) );
      BMSclearMemoryArray(aggtypes, ncols);

      SCIP_CALL( SCIPallocBufferArray(scip, &binvars, ncols) );
      SCIPdebug( BMSclearMemoryArray(binvars, ncols) );

      /* search for aggregations */
      SCIP_CALL( findUplockAggregations(scip, matrix, &nvaragg, aggtypes, binvars) );
      SCIP_CALL( findDownlockAggregations(scip, matrix, &nvaragg, aggtypes, binvars) );

      /* apply aggregations, if we found any */
      if( nvaragg > 0 )
      {
         int v;

         for( v = 0; v < ncols; v++ )
         {
            if( aggtypes[v] != NOAGG )
            {
               SCIP_Bool infeasible;
               SCIP_Bool redundant;
               SCIP_Bool aggregated;
               SCIP_Real ub;
               SCIP_Real lb;

               ub = SCIPmatrixGetColUb(matrix, v);
               lb = SCIPmatrixGetColLb(matrix, v);

               /* aggregate variable */
               assert(binvars[v] != NULL);
               if( aggtypes[v] == BIN0UBOUND )
               {
                  SCIP_CALL( SCIPaggregateVars(scip, SCIPmatrixGetVar(matrix, v), binvars[v], 1.0, ub-lb,
                        ub, &infeasible, &redundant, &aggregated) );
               }
               else
               {
                  assert(aggtypes[v] == BIN0LBOUND);
                  SCIP_CALL( SCIPaggregateVars(scip, SCIPmatrixGetVar(matrix, v), binvars[v], 1.0, lb-ub,
                        lb, &infeasible, &redundant, &aggregated) );
               }

               /* infeasible aggregation */
               if( infeasible )
               {
                  SCIPdebugMessage(" -> infeasible aggregation\n");
                  *result = SCIP_CUTOFF;
                  return SCIP_OKAY;
               }

               if( aggregated )
                  (*naggrvars)++;
            }
         }

         /* set result pointer */
         if( (*naggrvars) > 0 )
            *result = SCIP_SUCCESS;
      }

      SCIPfreeBufferArray(scip, &binvars);
      SCIPfreeBufferArray(scip, &aggtypes);
   }

   SCIPmatrixFree(scip, &matrix);

   return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecRootsoldiving) /*lint --e{715}*/
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_VAR** vars;
   SCIP_Real* rootsol;
   SCIP_Real* objchgvals;
   int* softroundings;
   int* intvalrounds;
   int nvars;
   int nbinvars;
   int nintvars;
   int nlpcands;
   SCIP_LPSOLSTAT lpsolstat;
   SCIP_Real absstartobjval;
   SCIP_Real objstep;
   SCIP_Real alpha;
   SCIP_Real oldobj;
   SCIP_Real newobj;
   SCIP_Bool lperror;
   SCIP_Bool lpsolchanged;
   SCIP_Longint nsolsfound;
   SCIP_Longint ncalls;
   SCIP_Longint nlpiterations;
   SCIP_Longint maxnlpiterations;
   int depth;
   int maxdepth;
   int maxdivedepth;
   int divedepth;
   int startnlpcands;
   int ncycles;
   int i;

   assert(heur != NULL);
   assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);
   assert(SCIPhasCurrentNodeLP(scip));

   *result = SCIP_DELAYED;

   /* only call heuristic, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* don't dive two times at the same node */
   if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

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

   /* only apply heuristic, if only a few solutions have been found */
   if( heurdata->maxsols >= 0 && SCIPgetNSolsFound(scip) >= heurdata->maxsols )
      return SCIP_OKAY;

   /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
   depth = SCIPgetDepth(scip);
   maxdepth = SCIPgetMaxDepth(scip);
   maxdepth = MAX(maxdepth, 30);
   if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
      return SCIP_OKAY;

   /* calculate the maximal number of LP iterations until heuristic is aborted */
   nlpiterations = SCIPgetNNodeLPIterations(scip);
   ncalls = SCIPheurGetNCalls(heur);
   nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
   maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
   maxnlpiterations += heurdata->maxlpiterofs;

   /* don't try to dive, if we took too many LP iterations during diving */
   if( heurdata->nlpiterations >= maxnlpiterations )
      return SCIP_OKAY;

   /* allow at least a certain number of LP iterations in this dive */
   maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);

   /* get number of fractional variables, that should be integral */
   nlpcands = SCIPgetNLPBranchCands(scip);

   /* don't try to dive, if there are no fractional variables */
   if( nlpcands == 0 )
      return SCIP_OKAY;

   /* calculate the maximal diving depth */
   nvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
   if( SCIPgetNSolsFound(scip) == 0 )
      maxdivedepth = (int)(heurdata->depthfacnosol * nvars);
   else
      maxdivedepth = (int)(heurdata->depthfac * nvars);
   maxdivedepth = MAX(maxdivedepth, 10);

   *result = SCIP_DIDNOTFIND;

   /* get all variables of LP */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );

   /* get root solution value of all binary and integer variables */
   SCIP_CALL( SCIPallocBufferArray(scip, &rootsol, nbinvars + nintvars) );
   for( i = 0; i < nbinvars + nintvars; i++ )
      rootsol[i] = SCIPvarGetRootSol(vars[i]);

   /* get current LP objective value, and calculate length of a single step in an objective coefficient */
   absstartobjval = SCIPgetLPObjval(scip);
   absstartobjval = ABS(absstartobjval);
   absstartobjval = MAX(absstartobjval, 1.0);
   objstep = absstartobjval / 10.0;

   /* initialize array storing the preferred soft rounding directions and counting the integral value rounds */
   SCIP_CALL( SCIPallocBufferArray(scip, &softroundings, nbinvars + nintvars) );
   BMSclearMemoryArray(softroundings, nbinvars + nintvars);
   SCIP_CALL( SCIPallocBufferArray(scip, &intvalrounds, nbinvars + nintvars) );
   BMSclearMemoryArray(intvalrounds, nbinvars + nintvars);

   /* allocate temporary memory for buffering objective changes */
   SCIP_CALL( SCIPallocBufferArray(scip, &objchgvals, nbinvars + nintvars) );

   /* start diving */
   SCIP_CALL( SCIPstartDive(scip) );

   SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing rootsoldiving heuristic: depth=%d, %d fractionals, dualbound=%g, maxnlpiterations=%"SCIP_LONGINT_FORMAT", maxdivedepth=%d, LPobj=%g, objstep=%g\n",
      SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), maxnlpiterations, maxdivedepth,
      SCIPgetLPObjval(scip), objstep);

   lperror = FALSE;
   divedepth = 0;
   lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
   alpha = heurdata->alpha;
   ncycles = 0;
   lpsolchanged = TRUE;
   startnlpcands = nlpcands;
   while( !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0 && ncycles < 10
      && (divedepth < 10
         || nlpcands <= startnlpcands - divedepth/2
         || (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations))
      && !SCIPisStopped(scip) )
   {
      SCIP_Bool success;
      int hardroundingidx;
      int hardroundingdir;
      SCIP_Real hardroundingoldbd;
      SCIP_Real hardroundingnewbd;
      SCIP_Bool boundschanged;

      SCIP_RETCODE retcode;

      /* create solution from diving LP and try to round it */
      SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
      SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );

      if( success )
      {
         SCIPdebugMessage("rootsoldiving found roundable primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));

         /* try to add solution to SCIP */
         SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

         /* check, if solution was feasible and good enough */
         if( success )
         {
            SCIPdebugMessage(" -> solution was feasible and good enough\n");
            *result = SCIP_FOUNDSOL;
         }
      }

      divedepth++;
      hardroundingidx = -1;
      hardroundingdir = 0;
      hardroundingoldbd = 0.0;
      hardroundingnewbd = 0.0;
      boundschanged = FALSE;

      SCIPdebugMessage("dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT":\n", divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations);

      /* round solution x* from diving LP:
       *   - x~_j = down(x*_j)    if x*_j is integer or binary variable and x*_j <= root solution_j
       *   - x~_j = up(x*_j)      if x*_j is integer or binary variable and x*_j  > root solution_j
       *   - x~_j = x*_j          if x*_j is continuous variable
       * change objective function in diving LP:
       *   - if x*_j is integral, or j is a continuous variable, set obj'_j = alpha * obj_j
       *   - otherwise, set obj'_j = alpha * obj_j + sign(x*_j - x~_j)
       */
      for( i = 0; i < nbinvars + nintvars; i++ )
      {
         SCIP_VAR* var;
         SCIP_Real solval;

         var = vars[i];
         oldobj = SCIPgetVarObjDive(scip, var);
         newobj = oldobj;

         solval =  SCIPvarGetLPSol(var);
         if( SCIPisFeasIntegral(scip, solval) )
         {
            /* if the variable became integral after a soft rounding, count the rounds; after a while, fix it to its
             * current integral value;
             * otherwise, fade out the objective value
             */
            if( softroundings[i] != 0 && lpsolchanged )
            {
               intvalrounds[i]++;
               if( intvalrounds[i] == 5 && SCIPgetVarLbDive(scip, var) < SCIPgetVarUbDive(scip, var) - 0.5 )
               {
                  /* use exact integral value, if the variable is only integral within numerical tolerances */
                  solval = SCIPfloor(scip, solval+0.5);
                  SCIPdebugMessage(" -> fixing <%s> = %g\n", SCIPvarGetName(var), solval);
                  SCIP_CALL( SCIPchgVarLbDive(scip, var, solval) );
                  SCIP_CALL( SCIPchgVarUbDive(scip, var, solval) );
                  boundschanged = TRUE;
               }
            }
            else
               newobj = alpha * oldobj;
         }
         else if( solval <= rootsol[i] )
         {
            /* if the variable was soft rounded most of the time downwards, round it downwards by changing the bounds;
             * otherwise, apply soft rounding by changing the objective value
             */
            softroundings[i]--;
            if( softroundings[i] <= -10 && hardroundingidx == -1 )
            {
               SCIPdebugMessage(" -> hard rounding <%s>[%g] <= %g\n",
                  SCIPvarGetName(var), solval, SCIPfeasFloor(scip, solval));
               hardroundingidx = i;
               hardroundingdir = -1;
               hardroundingoldbd = SCIPgetVarUbDive(scip, var);
               hardroundingnewbd = SCIPfeasFloor(scip, solval);
               SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingnewbd) );
               boundschanged = TRUE;
            }
            else
               newobj = alpha * oldobj + objstep;
         }
         else
         {
            /* if the variable was soft rounded most of the time upwards, round it upwards by changing the bounds;
             * otherwise, apply soft rounding by changing the objective value
             */
            softroundings[i]++;
            if( softroundings[i] >= +10 && hardroundingidx == -1 )
            {
               SCIPdebugMessage(" -> hard rounding <%s>[%g] >= %g\n",
                  SCIPvarGetName(var), solval, SCIPfeasCeil(scip, solval));
               hardroundingidx = i;
               hardroundingdir = +1;
               hardroundingoldbd = SCIPgetVarLbDive(scip, var);
               hardroundingnewbd = SCIPfeasCeil(scip, solval);
               SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingnewbd) );
               boundschanged = TRUE;
            }
            else
               newobj = alpha * oldobj - objstep;
         }

         /* remember the objective change */
         objchgvals[i] = newobj;
      }

      /* apply objective changes if there was no bound change */
      if( !boundschanged )
      {
         /* apply cached changes on integer variables */
         for( i = 0; i < nbinvars + nintvars; ++i )
         {
            SCIP_VAR* var;

            var = vars[i];
            SCIPdebugMessage(" -> i=%d  var <%s>, solval=%g, rootsol=%g, oldobj=%g, newobj=%g\n",
               i, SCIPvarGetName(var), SCIPvarGetLPSol(var), rootsol[i], SCIPgetVarObjDive(scip, var), objchgvals[i]);

            SCIP_CALL( SCIPchgVarObjDive(scip, var, objchgvals[i]) );
         }

         /* fade out the objective values of the continuous variables */
         for( i = nbinvars + nintvars; i < nvars; i++ )
         {
            SCIP_VAR* var;

            var = vars[i];
            oldobj = SCIPgetVarObjDive(scip, var);
            newobj = alpha * oldobj;

            SCIPdebugMessage(" -> i=%d  var <%s>, solval=%g, oldobj=%g, newobj=%g\n",
               i, SCIPvarGetName(var), SCIPvarGetLPSol(var), oldobj, newobj);

            SCIP_CALL( SCIPchgVarObjDive(scip, var, newobj) );
         }
      }

   SOLVEAGAIN:
      /* resolve the diving LP */
      nlpiterations = SCIPgetNLPIterations(scip);

      retcode = SCIPsolveDiveLP(scip,  MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror);
      lpsolstat = SCIPgetLPSolstat(scip);

      /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
       * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
       */
      if( retcode != SCIP_OKAY )
      {
#ifndef NDEBUG
         if( lpsolstat != SCIP_LPSOLSTAT_UNBOUNDEDRAY )
         {
            SCIP_CALL( retcode );
         }
#endif
         SCIPwarningMessage(scip, "Error while solving LP in Rootsoldiving heuristic; LP solve terminated with code <%d>\n", retcode);
         SCIPwarningMessage(scip, "This does not affect the remaining solution procedure --> continue\n");
      }

      if( lperror )
         break;

      /* update iteration count */
      heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations;

      /* if no LP iterations were performed, we stayed at the same solution -> count this cycling */
      lpsolchanged = (SCIPgetNLPIterations(scip) != nlpiterations);
      if( lpsolchanged )
         ncycles = 0;
      else if( !boundschanged ) /* do not count if integral variables have been fixed */
         ncycles++;

      /* get LP solution status and number of fractional variables, that should be integral */
      if( lpsolstat == SCIP_LPSOLSTAT_INFEASIBLE && hardroundingidx != -1 )
      {
         SCIP_VAR* var;

         var = vars[hardroundingidx];

         /* round the hard rounded variable to the opposite direction and resolve the LP */
         if( hardroundingdir == -1 )
         {
            SCIPdebugMessage(" -> opposite hard rounding <%s> >= %g\n", SCIPvarGetName(var), hardroundingnewbd + 1.0);
            SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingoldbd) );
            SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingnewbd + 1.0) );
         }
         else
         {
            SCIPdebugMessage(" -> opposite hard rounding <%s> <= %g\n", SCIPvarGetName(var), hardroundingnewbd - 1.0);
            SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingoldbd) );
            SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingnewbd - 1.0) );
         }
         hardroundingidx = -1;
         goto SOLVEAGAIN;
      }
      if( lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
         nlpcands = SCIPgetNLPBranchCands(scip);
      SCIPdebugMessage("   -> lpsolstat=%d, nfrac=%d\n", lpsolstat, nlpcands);
   }

   SCIPdebugMessage("---> diving finished: lpsolstat = %d, depth %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT"\n",
      lpsolstat, divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations);

   /* check if a solution has been found */
   if( nlpcands == 0 && !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
   {
      SCIP_Bool success;

      /* create solution from diving LP */
      SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
      SCIPdebugMessage("rootsoldiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));

      /* try to add solution to SCIP */
      SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

      /* check, if solution was feasible and good enough */
      if( success )
      {
         SCIPdebugMessage(" -> solution was feasible and good enough\n");
         *result = SCIP_FOUNDSOL;
      }
   }

   /* end diving */
   SCIP_CALL( SCIPendDive(scip) );

   if( *result == SCIP_FOUNDSOL )
      heurdata->nsuccess++;

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &objchgvals);
   SCIPfreeBufferArray(scip, &intvalrounds);
   SCIPfreeBufferArray(scip, &softroundings);
   SCIPfreeBufferArray(scip, &rootsol);

   SCIPdebugMessage("rootsoldiving heuristic finished\n");

   return SCIP_OKAY;
}
Пример #8
0
/** separate 2-cuts */
static
SCIP_RETCODE sep_2cut(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_CONSHDLR*        conshdlr,           /**< constraint handler */
   SCIP_CONSHDLRDATA*    conshdlrdata,       /**< constraint handler data */
   SCIP_CONSDATA*        consdata,           /**< constraint data */
   int                   maxcuts,            /**< maximal number of cuts */
   int*                  ncuts               /**< pointer to store number of cuts */
   )
{
   const SCIP_Bool nested_cut   = conshdlrdata->nestedcut;
   const SCIP_Bool back_cut     = conshdlrdata->backcut;
   const SCIP_Bool creep_flow   = conshdlrdata->creepflow;
   const SCIP_Bool disjunct_cut = conshdlrdata->disjunctcut;
   const SCIP_Bool flowsep      = conshdlrdata->flowsep;

   GRAPH*  g;
   SCIP_Real* xval;
   SCIP_Real* cost;
   PATH*   path;
   int*    w;
   int*    capa;
   int*    term;
   int     terms = 0;
   int     tsave;
   int     i;
   int     k;
   int     layer;
   int     count = 0;
   int     rerun = FALSE;
   int     nedges;
   int     nnodes;
   SCIP_Bool addedcut;

   assert(scip != NULL);
   assert(conshdlr != NULL);
   assert(conshdlrdata != NULL);

   g = consdata->graph;
   assert(g != NULL);

   nedges = g->edges;
   nnodes = g->knots;
   addedcut = FALSE;

   xval = SCIPprobdataGetXval(scip, NULL);
   assert(xval != NULL);

   SCIP_CALL( SCIPallocBufferArray(scip, &capa, nedges) );
   SCIP_CALL( SCIPallocBufferArray(scip, &cost, nedges) );
   SCIP_CALL( SCIPallocBufferArray(scip, &w, nnodes) );
   SCIP_CALL( SCIPallocBufferArray(scip, &term, g->terms) );
   SCIP_CALL( SCIPallocBufferArray(scip, &path, nnodes) );

   for( layer = 0; layer < g->layers; layer++ )
   {
      /* For 2-terminal nets no cuts are necessary if flows are given */
      if( flowsep && (g->locals[layer] == 2) )
         continue;

      for( i = 0; i < nedges; i++ )
         cost[i] = SCIPisFeasLT(scip, xval[layer * nedges + i], 1.0) ? 1.0 : 0.0;

      for( i = 0; i < nnodes; i++ )
      {
	 w[i] = 0;
         g->mark[i] = TRUE;
      }

      graph_path_exec(scip, g, FSP_MODE, g->source[layer], cost, path);

      /* search all terminals not connected to the root by the LP solution */
      for( i = 0, count = 0; i < nnodes; i++ )
      {
         if( (g->term[i] == layer) && (i != g->source[layer]) )
         {
            if( SCIPisPositive(scip, path[i].dist) )
               term[terms++] = i;
            else
               count++;
         }
      }
      SCIPdebugMessage("Cut Pretest: %d eliminations\n", count);

      count = 0;
      tsave = terms;

      /* from source to terminal */
      if( !nested_cut || disjunct_cut )
         set_capacity(g, layer, creep_flow, 0, capa, xval);

      while( terms > 0 )
      {
         if( SCIPisStopped(scip) && terms % 100 == 0 )
            break;

         /* look for reachable terminal */
         i = graph_next_term(terms, term, w);

         terms--;

         assert(g->term[i]       == layer);
         assert(g->source[layer] != i);

         if( nested_cut && !disjunct_cut )
            set_capacity(g, layer, creep_flow, 0, capa, xval);

         do
         {
            graph_mincut_exec(g, g->source[layer], i, capa, w, rerun);

            rerun = TRUE;

            /* cut */
            for( k = 0; k < nnodes; k++ )
               g->mark[k] = (w[k] != 0);

	    SCIP_CALL( cut_add(scip, conshdlr, g, layer, xval, capa, nested_cut || disjunct_cut, ncuts, &addedcut) );
            if( addedcut )
            {
               count++;

               if( *ncuts >= maxcuts )
                  goto TERMINATE;
            }
            else
               break;
         }
         while( nested_cut );               /* Nested Cut is CONSTANT ! */
      }

      /* back cuts enabled? */
      if( back_cut )
      {
         if( !nested_cut || disjunct_cut )
            set_capacity(g, layer, creep_flow, 1, capa, xval);

         terms = tsave;

         while( terms > 0 )
         {
            /* look for reachable terminal */
            i = graph_next_term(terms, term, w);

            terms--;

            assert(g->term[i]       == layer);
            assert(g->source[layer] != i);

            if( nested_cut && !disjunct_cut )
               set_capacity(g, layer, creep_flow, 1, capa, xval);

            rerun = FALSE;

            do
            {
               graph_mincut_exec(g, i, g->source[layer], capa, w, rerun);

               rerun = TRUE;

               for( k = 0; k < nnodes; k++ )
                  g->mark[k] = (w[k] != 0) ? 1 : 0;

	       SCIP_CALL( cut_add(scip, conshdlr, g, layer, xval, capa, nested_cut || disjunct_cut, ncuts, &addedcut) );
               if( addedcut )
               {
                  count++;

                  if( *ncuts >= maxcuts )
                     goto TERMINATE;
               }
               else
                  break;
#if 0
               if (nested_cut || disjunct_cut)
                  for(k = p->beg[p->rcnt - 1]; k < p->nzcnt; k++)
                     capa[p->ind[k] % nedges
                        + (((p->ind[k] % nedges) % 2)
                           ? -1 : 1)] = FLOW_FACTOR;
#endif
            }
            while( nested_cut );                /* Nested Cut is CONSTANT ! */

            rerun = FALSE;
         }
      }
   }

 TERMINATE:
   SCIPfreeBufferArray(scip, &path);
   SCIPfreeBufferArray(scip, &term);
   SCIPfreeBufferArray(scip, &w);
   SCIPfreeBufferArray(scip, &cost);
   SCIPfreeBufferArray(scip, &capa);

   SCIPdebugMessage("2-cut Separator: %d Inequalities added\n", count);

   return SCIP_OKAY;
}
Пример #9
0
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpGomory)
{  /*lint --e{715}*/
   SCIP_SEPADATA* sepadata;
   SCIP_VAR** vars;
   SCIP_COL** cols;
   SCIP_ROW** rows;
   SCIP_Real* binvrow;
   SCIP_Real* cutcoefs;
   SCIP_Real maxscale;
   SCIP_Real minfrac;
   SCIP_Real maxfrac;
   SCIP_Longint maxdnom;
   SCIP_Bool cutoff;
   int* basisind;
   int naddedcuts;
   int nvars;
   int ncols;
   int nrows;
   int ncalls;
   int depth;
   int maxdepth;
   int maxsepacuts;
   int c;
   int i;

   assert(sepa != NULL);
   assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);

   *result = SCIP_DIDNOTRUN;

   sepadata = SCIPsepaGetData(sepa);
   assert(sepadata != NULL);

   depth = SCIPgetDepth(scip);
   ncalls = SCIPsepaGetNCallsAtNode(sepa);

   minfrac = sepadata->away;
   maxfrac = 1.0 - sepadata->away;

   /* only call separator, if we are not close to terminating */
   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   /* only call the gomory cut separator a given number of times at each node */
   if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
      || (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
      return SCIP_OKAY;

   /* only call separator, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call separator, if the LP solution is basic */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* only call separator, if there are fractional variables */
   if( SCIPgetNLPBranchCands(scip) == 0 )
      return SCIP_OKAY;

   /* get variables data */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* get LP data */
   SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
   SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
   if( ncols == 0 || nrows == 0 )
      return SCIP_OKAY;

#if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */
   if( ncols >= 50*nrows )
      return SCIP_OKAY;

   if( ncols >= 5*nrows )
   {
      int ncutsfound;

      ncutsfound = SCIPgetNCutsFound(scip);
      if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) )
      {
         sepadata->lastncutsfound = ncutsfound;
         *result = SCIP_DELAYED;
         return SCIP_OKAY;
      }
   }
#endif

   /* set the maximal denominator in rational representation of gomory cut and the maximal scale factor to
    * scale resulting cut to integral values to avoid numerical instabilities
    */
   /**@todo find better but still stable gomory cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */
   maxdepth = SCIPgetMaxDepth(scip);
   if( depth == 0 )
   {
      maxdnom = 1000;
      maxscale = 1000.0;
   }
   else if( depth <= maxdepth/4 )
   {
      maxdnom = 1000;
      maxscale = 1000.0;
   }
   else if( depth <= maxdepth/2 )
   {
      maxdnom = 100;
      maxscale = 100.0;
   }
   else
   {
      maxdnom = 10;
      maxscale = 10.0;
   }

   /* allocate temporary memory */
   SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );

   /* get basis indices */
   SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );

   /* get the maximal number of cuts allowed in a separation round */
   if( depth == 0 )
      maxsepacuts = sepadata->maxsepacutsroot;
   else
      maxsepacuts = sepadata->maxsepacuts;

   SCIPdebugMessage("searching gomory cuts: %d cols, %d rows, maxdnom=%"SCIP_LONGINT_FORMAT", maxscale=%g, maxcuts=%d\n",
      ncols, nrows, maxdnom, maxscale, maxsepacuts);

   cutoff = FALSE;
   naddedcuts = 0;

   /* for all basic columns belonging to integer variables, try to generate a gomory cut */
   for( i = 0; i < nrows && naddedcuts < maxsepacuts && !SCIPisStopped(scip) && !cutoff; ++i )
   {
      SCIP_Bool tryrow;

      tryrow = FALSE;
      c = basisind[i];
      if( c >= 0 )
      {
         SCIP_VAR* var;

         assert(c < ncols);
         var = SCIPcolGetVar(cols[c]);
         if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS )
         {
            SCIP_Real primsol;

            primsol = SCIPcolGetPrimsol(cols[c]);
            assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/

            if( SCIPfeasFrac(scip, primsol) >= minfrac )
            {
               SCIPdebugMessage("trying gomory cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol);
               tryrow = TRUE;
            }
         }
      }
      else if( sepadata->separaterows )
      {
         SCIP_ROW* row;

         assert(0 <= -c-1 && -c-1 < nrows);
         row = rows[-c-1];
         if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) )
         {
            SCIP_Real primsol;

            primsol = SCIPgetRowActivity(scip, row);
            if( SCIPfeasFrac(scip, primsol) >= minfrac )
            {
               SCIPdebugMessage("trying gomory cut for row <%s> [%g]\n", SCIProwGetName(row), primsol);
               tryrow = TRUE;
            }
         }
      }

      if( tryrow )
      {
         SCIP_Real cutrhs;
         SCIP_Real cutact;
         SCIP_Bool success;
         SCIP_Bool cutislocal;

         /* get the row of B^-1 for this basic integer variable with fractional solution value */
         SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow) );

         cutact = 0.0;
         cutrhs = SCIPinfinity(scip);

         /* create a MIR cut out of the weighted LP rows using the B^-1 row as weights */
         SCIP_CALL( SCIPcalcMIR(scip, NULL, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, FIXINTEGRALRHS, NULL, NULL,
               (int) MAXAGGRLEN(nvars), sepadata->maxweightrange, minfrac, maxfrac,
               binvrow, 1.0, NULL, NULL, cutcoefs, &cutrhs, &cutact, &success, &cutislocal) );
         assert(ALLOWLOCAL || !cutislocal);

         /* @todo Currently we are using the SCIPcalcMIR() function to compute the coefficients of the Gomory
          *       cut. Alternatively, we could use the direct version (see thesis of Achterberg formula (8.4)) which
          *       leads to cut a of the form \sum a_i x_i \geq 1. Rumor has it that these cuts are better.
          */

         SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs);

         /* if successful, convert dense cut into sparse row, and add the row as a cut */
         if( success && SCIPisFeasGT(scip, cutact, cutrhs) )
         {
            SCIP_ROW* cut;
            char cutname[SCIP_MAXSTRLEN];
            int v;

            /* construct cut name */
            if( c >= 0 )
               (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "gom%d_x%d", SCIPgetNLPs(scip), c);
            else
               (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "gom%d_s%d", SCIPgetNLPs(scip), -c-1);

            /* create empty cut */
            SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs,
                  cutislocal, FALSE, sepadata->dynamiccuts) );

            /* cache the row extension and only flush them if the cut gets added */
            SCIP_CALL( SCIPcacheRowExtensions(scip, cut) );

            /* collect all non-zero coefficients */
            for( v = 0; v < nvars; ++v )
            {
               if( !SCIPisZero(scip, cutcoefs[v]) )
               {
                  SCIP_CALL( SCIPaddVarToRow(scip, cut, vars[v], cutcoefs[v]) );
               }
            }

            if( SCIProwGetNNonz(cut) == 0 )
            {
               assert(SCIPisFeasNegative(scip, cutrhs));
               SCIPdebugMessage(" -> gomory cut detected infeasibility with cut 0 <= %f\n", cutrhs);
               cutoff = TRUE;
            }
            else if( SCIProwGetNNonz(cut) == 1 )
            {
               /* add the bound change as cut to avoid that the LP gets modified. that would mean the LP is not flushed
                * and the method SCIPgetLPBInvRow() fails; SCIP internally will apply that bound change automatically
                */
               SCIP_CALL( SCIPaddCut(scip, NULL, cut, TRUE) );
               naddedcuts++;
            }
            else
            {
               /* Only take efficacious cuts, except for cuts with one non-zero coefficients (= bound
                * changes); the latter cuts will be handeled internally in sepastore.
                */
               if( SCIPisCutEfficacious(scip, NULL, cut) )
               {
                  assert(success == TRUE);

                  SCIPdebugMessage(" -> gomory cut for <%s>: act=%f, rhs=%f, eff=%f\n",
                     c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]),
                     cutact, cutrhs, SCIPgetCutEfficacy(scip, NULL, cut));

                  if( sepadata->makeintegral )
                  {
                     /* try to scale the cut to integral values */
                     SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
                           maxdnom, maxscale, MAKECONTINTEGRAL, &success) );

                     if( sepadata->forcecuts )
                        success = TRUE;

                     /* in case the left hand side in minus infinity and the right hand side is plus infinity the cut is
                      * useless so we are not taking it at all
                      */
                     if( (SCIPisInfinity(scip, -SCIProwGetLhs(cut)) && SCIPisInfinity(scip, SCIProwGetRhs(cut))) )
                        success = FALSE;

                     /* @todo Trying to make the Gomory cut integral might fail. Due to numerical reasons/arguments we
                      *       currently ignore such cuts. If the cut, however, has small support (let's say smaller or equal to
                      *       5), we might want to add that cut (even it does not have integral coefficients). To be able to
                      *       do that we need to add a rank to the data structure of a row. The rank of original rows are
                      *       zero and for aggregated rows it is the maximum over all used rows plus one.
                      */
                  }

                  if( success )
                  {
                     SCIPdebugMessage(" -> found gomory cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
                        cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
                        SCIPgetCutEfficacy(scip, NULL, cut),
                        SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
                        SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut));

                     /* flush all changes before adding the cut */
                     SCIP_CALL( SCIPflushRowExtensions(scip, cut) );

                     /* add global cuts which are not implicit bound changes to the cut pool */
                     if( !cutislocal )
                     {
                        if( sepadata->delayedcuts )
                        {
                           SCIP_CALL( SCIPaddDelayedPoolCut(scip, cut) );
                        }
                        else
                        {
                           SCIP_CALL( SCIPaddPoolCut(scip, cut) );
                        }
                     }
                     else
                     {
                        /* local cuts we add to the sepastore */
                        SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE) );
                     }

                     naddedcuts++;
                  }
               }
            }

            /* release the row */
            SCIP_CALL( SCIPreleaseRow(scip, &cut) );
         }
      }
   }

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &binvrow);
   SCIPfreeBufferArray(scip, &basisind);
   SCIPfreeBufferArray(scip, &cutcoefs);

   SCIPdebugMessage("end searching gomory cuts: found %d cuts\n", naddedcuts);

   sepadata->lastncutsfound = SCIPgetNCutsFound(scip);

   /* evalute the result of the separation */
   if( cutoff )
      *result = SCIP_CUTOFF;
   else if ( naddedcuts > 0 )
      *result = SCIP_SEPARATED;
   else
      *result = SCIP_DIDNOTFIND;

   return SCIP_OKAY;
}
Пример #10
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;
}
Пример #11
0
/** LP solution separation method for disjunctive cuts */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpDisjunctive)
{
   SCIP_SEPADATA* sepadata;
   SCIP_CONSHDLR* conshdlr;
   SCIP_DIGRAPH* conflictgraph;
   SCIP_ROW** rows;
   SCIP_COL** cols;
   SCIP_Real* cutcoefs = NULL;
   SCIP_Real* simplexcoefs1 = NULL;
   SCIP_Real* simplexcoefs2 = NULL;
   SCIP_Real* coef = NULL;
   SCIP_Real* binvrow = NULL;
   SCIP_Real* rowsmaxval = NULL;
   SCIP_Real* violationarray = NULL;
   int* fixings1 = NULL;
   int* fixings2 = NULL;
   int* basisind = NULL;
   int* basisrow = NULL;
   int* varrank = NULL;
   int* edgearray = NULL;
   int nedges;
   int ndisjcuts;
   int nrelevantedges;
   int nsos1vars;
   int nconss;
   int maxcuts;
   int ncalls;
   int depth;
   int ncols;
   int nrows;
   int ind;
   int j;
   int i;

   assert( sepa != NULL );
   assert( strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0 );
   assert( scip != NULL );
   assert( result != NULL );

   *result = SCIP_DIDNOTRUN;

   /* only generate disjunctive cuts if we are not close to terminating */
   if ( SCIPisStopped(scip) )
      return SCIP_OKAY;

   /* only generate disjunctive cuts if an optimal LP solution is at hand */
   if ( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only generate disjunctive cuts if the LP solution is basic */
   if ( ! SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* get LP data */
   SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
   SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );

   /* return if LP has no columns or no rows */
   if ( ncols == 0 || nrows == 0 )
      return SCIP_OKAY;

   assert( cols != NULL );
   assert( rows != NULL );

   /* get sepa data */
   sepadata = SCIPsepaGetData(sepa);
   assert( sepadata != NULL );

   /* get constraint handler */
   conshdlr = sepadata->conshdlr;
   if ( conshdlr == NULL )
      return SCIP_OKAY;

   /* get number of constraints */
   nconss = SCIPconshdlrGetNConss(conshdlr);
   if ( nconss == 0 )
      return SCIP_OKAY;

   /* check for maxdepth < depth, maxinvcutsroot = 0 and maxinvcuts = 0 */
   depth = SCIPgetDepth(scip);
   if ( ( sepadata->maxdepth >= 0 && sepadata->maxdepth < depth )
      || ( depth == 0 && sepadata->maxinvcutsroot == 0 )
      || ( depth > 0 && sepadata->maxinvcuts == 0 ) )
      return SCIP_OKAY;

   /* only call the cut separator a given number of times at each node */
   ncalls = SCIPsepaGetNCallsAtNode(sepa);
   if ( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
      || (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
      return SCIP_OKAY;

   /* get conflict graph and number of conflict graph edges (note that the digraph arcs were added in both directions) */
   conflictgraph = SCIPgetConflictgraphSOS1(conshdlr);
   nedges = (int)SCIPceil(scip, (SCIP_Real)SCIPdigraphGetNArcs(conflictgraph)/2);

   /* if too many conflict graph edges, the separator can be slow: delay it until no other cuts have been found */
   if ( sepadata->maxconfsdelay >= 0 && nedges >= sepadata->maxconfsdelay )
   {
      int ncutsfound;

      ncutsfound = SCIPgetNCutsFound(scip);
      if ( ncutsfound > sepadata->lastncutsfound || ! SCIPsepaWasLPDelayed(sepa) )
      {
         sepadata->lastncutsfound = ncutsfound;
         *result = SCIP_DELAYED;
         return SCIP_OKAY;
      }
   }

   /* check basis status */
   for (j = 0; j < ncols; ++j)
   {
      if ( SCIPcolGetBasisStatus(cols[j]) == SCIP_BASESTAT_ZERO )
         return SCIP_OKAY;
   }

   /* get number of SOS1 variables */
   nsos1vars = SCIPgetNSOS1Vars(conshdlr);

   /* allocate buffer arrays */
   SCIP_CALL( SCIPallocBufferArray(scip, &edgearray, nedges) );
   SCIP_CALL( SCIPallocBufferArray(scip, &fixings1, nedges) );
   SCIP_CALL( SCIPallocBufferArray(scip, &fixings2, nedges) );
   SCIP_CALL( SCIPallocBufferArray(scip, &violationarray, nedges) );

   /* get all violated conflicts {i, j} in the conflict graph and sort them based on the degree of a violation value */
   nrelevantedges = 0;
   for (j = 0; j < nsos1vars; ++j)
   {
      SCIP_VAR* var;

      var = SCIPnodeGetVarSOS1(conflictgraph, j);

      if ( SCIPvarIsActive(var) && ! SCIPisFeasZero(scip, SCIPcolGetPrimsol(SCIPvarGetCol(var))) && SCIPcolGetBasisStatus(SCIPvarGetCol(var)) == SCIP_BASESTAT_BASIC )
      {
         int* succ;
         int nsucc;

         /* get successors and number of successors */
         nsucc = SCIPdigraphGetNSuccessors(conflictgraph, j);
         succ = SCIPdigraphGetSuccessors(conflictgraph, j);

         for (i = 0; i < nsucc; ++i)
         {
            SCIP_VAR* varsucc;
            int succind;

            succind = succ[i];
            varsucc = SCIPnodeGetVarSOS1(conflictgraph, succind);
            if ( SCIPvarIsActive(varsucc) && succind < j && ! SCIPisFeasZero(scip, SCIPgetSolVal(scip, NULL, varsucc) ) &&
                 SCIPcolGetBasisStatus(SCIPvarGetCol(varsucc)) == SCIP_BASESTAT_BASIC )
            {
               fixings1[nrelevantedges] = j;
               fixings2[nrelevantedges] = succind;
               edgearray[nrelevantedges] = nrelevantedges;
               violationarray[nrelevantedges++] = SCIPgetSolVal(scip, NULL, var) * SCIPgetSolVal(scip, NULL, varsucc);
            }
         }
      }
   }

   /* sort violation score values */
   if ( nrelevantedges > 0)
      SCIPsortDownRealInt(violationarray, edgearray, nrelevantedges);
   else
   {
      SCIPfreeBufferArrayNull(scip, &violationarray);
      SCIPfreeBufferArrayNull(scip, &fixings2);
      SCIPfreeBufferArrayNull(scip, &fixings1);
      SCIPfreeBufferArrayNull(scip, &edgearray);

      return SCIP_OKAY;
   }
   SCIPfreeBufferArrayNull(scip, &violationarray);

   /* compute maximal number of cuts */
   if ( SCIPgetDepth(scip) == 0 )
      maxcuts = MIN(sepadata->maxinvcutsroot, nrelevantedges);
   else
      maxcuts = MIN(sepadata->maxinvcuts, nrelevantedges);
   assert( maxcuts > 0 );

   /* allocate buffer arrays */
   SCIP_CALL( SCIPallocBufferArray(scip, &varrank, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &rowsmaxval, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &basisrow, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &coef, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &simplexcoefs1, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &simplexcoefs2, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, ncols) );
   SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );

   /* get basis indices */
   SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );

   /* create vector "basisrow" with basisrow[column of non-slack basis variable] = corresponding row of B^-1;
    * compute maximum absolute value of nonbasic row coefficients */
   for (j = 0; j < nrows; ++j)
   {
      SCIP_COL** rowcols;
      SCIP_Real* rowvals;
      SCIP_ROW* row;
      SCIP_Real val;
      SCIP_Real max = 0.0;
      int nnonz;

      /* fill basisrow vector */
      ind = basisind[j];
      if ( ind >= 0 )
         basisrow[ind] = j;

      /* compute maximum absolute value of nonbasic row coefficients */
      row = rows[j];
      assert( row != NULL );
      rowvals = SCIProwGetVals(row);
      nnonz = SCIProwGetNNonz(row);
      rowcols = SCIProwGetCols(row);

      for (i = 0; i < nnonz; ++i)
      {
         if ( SCIPcolGetBasisStatus(rowcols[i]) == SCIP_BASESTAT_LOWER  || SCIPcolGetBasisStatus(rowcols[i]) == SCIP_BASESTAT_UPPER )
         {
            val = REALABS(rowvals[i]);
            if ( SCIPisFeasGT(scip, val, max) )
               max = REALABS(val);
         }
      }

      /* handle slack variable coefficient and save maximum value */
      rowsmaxval[j] = MAX(max, 1.0);
   }

   /* initialize variable ranks with -1 */
   for (j = 0; j < ncols; ++j)
      varrank[j] = -1;

   /* free buffer array */
   SCIPfreeBufferArrayNull(scip, &basisind);

   /* for the most promising disjunctions: try to generate disjunctive cuts */
   ndisjcuts = 0;
   for (i = 0; i < maxcuts; ++i)
   {
      SCIP_Bool madeintegral;
      SCIP_Real cutlhs1;
      SCIP_Real cutlhs2;
      SCIP_Real bound1;
      SCIP_Real bound2;
      SCIP_ROW* row = NULL;
      SCIP_VAR* var;
      SCIP_COL* col;

      int nonbasicnumber;
      int cutrank = 0;
      int edgenumber;
      int rownnonz;

      edgenumber = edgearray[i];

      /* determine first simplex row */
      var = SCIPnodeGetVarSOS1(conflictgraph, fixings1[edgenumber]);
      col = SCIPvarGetCol(var);
      ind = SCIPcolGetLPPos(col);
      assert( ind >= 0 );
      assert( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_BASIC );

      /* get the 'ind'th row of B^-1 and B^-1 \cdot A */
      SCIP_CALL( SCIPgetLPBInvRow(scip, basisrow[ind], binvrow, NULL, NULL) );
      SCIP_CALL( SCIPgetLPBInvARow(scip, basisrow[ind], binvrow, coef, NULL, NULL) );

      /* get the simplex-coefficients of the non-basic variables */
      SCIP_CALL( getSimplexCoefficients(scip, rows, nrows, cols, ncols, coef, binvrow, simplexcoefs1, &nonbasicnumber) );

      /* get rank of variable if not known already */
      if ( varrank[ind] < 0 )
         varrank[ind] = getVarRank(scip, binvrow, rowsmaxval, sepadata->maxweightrange, rows, nrows);
      cutrank = MAX(cutrank, varrank[ind]);

      /* get right hand side and bound of simplex talbeau row */
      cutlhs1 = SCIPcolGetPrimsol(col);
      if ( SCIPisFeasPositive(scip, cutlhs1) )
         bound1 = SCIPcolGetUb(col);
      else
         bound1 = SCIPcolGetLb(col);


      /* determine second simplex row */
      var = SCIPnodeGetVarSOS1(conflictgraph, fixings2[edgenumber]);
      col = SCIPvarGetCol(var);
      ind = SCIPcolGetLPPos(col);
      assert( ind >= 0 );
      assert( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_BASIC );

      /* get the 'ind'th row of B^-1 and B^-1 \cdot A */
      SCIP_CALL( SCIPgetLPBInvRow(scip, basisrow[ind], binvrow, NULL, NULL) );
      SCIP_CALL( SCIPgetLPBInvARow(scip, basisrow[ind], binvrow, coef, NULL, NULL) );

      /* get the simplex-coefficients of the non-basic variables */
      SCIP_CALL( getSimplexCoefficients(scip, rows, nrows, cols, ncols, coef, binvrow, simplexcoefs2, &nonbasicnumber) );

      /* get rank of variable if not known already */
      if ( varrank[ind] < 0 )
         varrank[ind] = getVarRank(scip, binvrow, rowsmaxval, sepadata->maxweightrange, rows, nrows);
      cutrank = MAX(cutrank, varrank[ind]);

      /* get right hand side and bound of simplex talbeau row */
      cutlhs2 = SCIPcolGetPrimsol(col);
      if ( SCIPisFeasPositive(scip, cutlhs2) )
         bound2 = SCIPcolGetUb(col);
      else
         bound2 = SCIPcolGetLb(col);

      /* add coefficients to cut */
      SCIP_CALL( generateDisjCutSOS1(scip, sepa, rows, nrows, cols, ncols, ndisjcuts, TRUE, sepadata->strengthen, cutlhs1, cutlhs2, bound1, bound2, simplexcoefs1, simplexcoefs2, cutcoefs, &row, &madeintegral) );
      if ( row == NULL )
         continue;

      /* raise cutrank for present cut */
      ++cutrank;

      /* check if there are numerical evidences */
      if ( ( madeintegral && ( sepadata->maxrankintegral == -1 || cutrank <= sepadata->maxrankintegral ) )
         || ( ! madeintegral && ( sepadata->maxrank == -1 || cutrank <= sepadata->maxrank ) ) )
      {
         /* possibly add cut to LP if it is useful; in case the lhs of the cut is minus infinity (due to scaling) the cut is useless */
         rownnonz = SCIProwGetNNonz(row);
         if ( rownnonz > 0 && ! SCIPisInfinity(scip, -SCIProwGetLhs(row)) && ! SCIProwIsInLP(row) && SCIPisCutEfficacious(scip, NULL, row) )
         {
            SCIP_Bool infeasible;

            /* set cut rank */
            SCIProwChgRank(row, cutrank);

            /* add cut */
            SCIP_CALL( SCIPaddCut(scip, NULL, row, FALSE, &infeasible) );
            SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
            if ( infeasible )
            {
               *result = SCIP_CUTOFF;
               break;
            }
            ++ndisjcuts;
         }
      }

      /* release row */
      SCIP_CALL( SCIPreleaseRow(scip, &row) );
   }

   /* save total number of cuts found so far */
   sepadata->lastncutsfound = SCIPgetNCutsFound(scip);

   /* evaluate the result of the separation */
   if ( *result != SCIP_CUTOFF )
   {
      if ( ndisjcuts > 0 )
         *result = SCIP_SEPARATED;
      else
         *result = SCIP_DIDNOTFIND;
   }

   SCIPdebugMessage("Number of found disjunctive cuts: %d.\n", ndisjcuts);

   /* free buffer arrays */
   SCIPfreeBufferArrayNull(scip, &cutcoefs);
   SCIPfreeBufferArrayNull(scip, &simplexcoefs2);
   SCIPfreeBufferArrayNull(scip, &simplexcoefs1);
   SCIPfreeBufferArrayNull(scip, &coef);
   SCIPfreeBufferArrayNull(scip, &binvrow);
   SCIPfreeBufferArrayNull(scip, &basisrow);
   SCIPfreeBufferArrayNull(scip, &fixings2);
   SCIPfreeBufferArrayNull(scip, &fixings1);
   SCIPfreeBufferArrayNull(scip, &edgearray);
   SCIPfreeBufferArrayNull(scip, &rowsmaxval);
   SCIPfreeBufferArrayNull(scip, &varrank);

   return SCIP_OKAY;
}
Пример #12
0
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpStrongcg)
{  /*lint --e{715}*/
   SCIP_SEPADATA* sepadata;
   SCIP_VAR** vars;
   SCIP_COL** cols;
   SCIP_ROW** rows;
   SCIP_Real* varsolvals;
   SCIP_Real* binvrow;
   SCIP_Real* cutcoefs;
   SCIP_Real cutrhs;
   SCIP_Real cutact;
   SCIP_Real maxscale;
   SCIP_Longint maxdnom;
   int* basisind;
   int* inds;
   int ninds;
   int nvars;
   int ncols;
   int nrows;
   int ncalls;
   int depth;
   int maxdepth;
   int maxsepacuts;
   int ncuts;
   int c;
   int i;
   int cutrank;
   SCIP_Bool success;
   SCIP_Bool cutislocal;
   char normtype;

   assert(sepa != NULL);
   assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);

   *result = SCIP_DIDNOTRUN;

   sepadata = SCIPsepaGetData(sepa);
   assert(sepadata != NULL);

   depth = SCIPgetDepth(scip);
   ncalls = SCIPsepaGetNCallsAtNode(sepa);

   /* only call separator, if we are not close to terminating */
   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   /* only call the strong CG cut separator a given number of times at each node */
   if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
      || (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
      return SCIP_OKAY;

   /* only call separator, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call separator, if the LP solution is basic */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* only call separator, if there are fractional variables */
   if( SCIPgetNLPBranchCands(scip) == 0 )
      return SCIP_OKAY;

   /* get variables data */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* get LP data */
   SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
   SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
   if( ncols == 0 || nrows == 0 )
      return SCIP_OKAY;

#if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */
   if( ncols >= 50*nrows )
      return SCIP_OKAY;
   if( ncols >= 5*nrows )
   {
      int ncutsfound;

      ncutsfound = SCIPgetNCutsFound(scip);
      if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) )
      {
         sepadata->lastncutsfound = ncutsfound;
         *result = SCIP_DELAYED;
         return SCIP_OKAY;
      }
   }
#endif

   /* get the type of norm to use for efficacy calculations */
   SCIP_CALL( SCIPgetCharParam(scip, "separating/efficacynorm", &normtype) );

   /* set the maximal denominator in rational representation of strong CG cut and the maximal scale factor to
    * scale resulting cut to integral values to avoid numerical instabilities
    */
   /**@todo find better but still stable strong CG cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */
   maxdepth = SCIPgetMaxDepth(scip);
   if( depth == 0 )
   {
      maxdnom = 1000;
      maxscale = 1000.0;
   }
   else if( depth <= maxdepth/4 )
   {
      maxdnom = 1000;
      maxscale = 1000.0;
   }
   else if( depth <= maxdepth/2 )
   {
      maxdnom = 100;
      maxscale = 100.0;
   }
   else
   {
      maxdnom = 10;
      maxscale = 10.0;
   }

   *result = SCIP_DIDNOTFIND;

   /* allocate temporary memory */
   SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &inds, nrows) );
   varsolvals = NULL; /* allocate this later, if needed */

   /* get basis indices */
   SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );

   /* get the maximal number of cuts allowed in a separation round */
   if( depth == 0 )
      maxsepacuts = sepadata->maxsepacutsroot;
   else
      maxsepacuts = sepadata->maxsepacuts;

   SCIPdebugMessage("searching strong CG cuts: %d cols, %d rows, maxdnom=%" SCIP_LONGINT_FORMAT ", maxscale=%g, maxcuts=%d\n",
      ncols, nrows, maxdnom, maxscale, maxsepacuts);

   /* for all basic columns belonging to integer variables, try to generate a strong CG cut */
   ncuts = 0;
   for( i = 0; i < nrows && ncuts < maxsepacuts && !SCIPisStopped(scip) && *result != SCIP_CUTOFF; ++i )
   {
      SCIP_Bool tryrow;

      tryrow = FALSE;
      c = basisind[i];
      if( c >= 0 )
      {
         SCIP_VAR* var;

         assert(c < ncols);
         var = SCIPcolGetVar(cols[c]);
         if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS )
         {
            SCIP_Real primsol;

            primsol = SCIPcolGetPrimsol(cols[c]);
            assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/

            if( SCIPfeasFrac(scip, primsol) >= MINFRAC )
            {
               SCIPdebugMessage("trying strong CG cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol);
               tryrow = TRUE;
            }
         }
      }
#ifdef SEPARATEROWS
      else
      {
         SCIP_ROW* row;

         assert(0 <= -c-1 && -c-1 < nrows);
         row = rows[-c-1];
         if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) )
         {
            SCIP_Real primsol;

            primsol = SCIPgetRowActivity(scip, row);
            if( SCIPfeasFrac(scip, primsol) >= MINFRAC )
            {
               SCIPdebugMessage("trying strong CG cut for row <%s> [%g]\n", SCIProwGetName(row), primsol);
               tryrow = TRUE;
            }
         }
      }
#endif

      if( tryrow )
      {
         /* get the row of B^-1 for this basic integer variable with fractional solution value */
         SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow, inds, &ninds) );

#ifdef SCIP_DEBUG
         /* initialize variables, that might not have been initialized in SCIPcalcMIR if success == FALSE */
         cutact = 0.0;
         cutrhs = SCIPinfinity(scip);
#endif
         /* create a strong CG cut out of the weighted LP rows using the B^-1 row as weights */
         SCIP_CALL( SCIPcalcStrongCG(scip, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, (int) MAXAGGRLEN(nvars), sepadata->maxweightrange, MINFRAC, MAXFRAC,
               binvrow, inds, ninds, 1.0, cutcoefs, &cutrhs, &cutact, &success, &cutislocal, &cutrank) );
         assert(ALLOWLOCAL || !cutislocal);
         SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs);

         /* if successful, convert dense cut into sparse row, and add the row as a cut */
         if( success && SCIPisFeasGT(scip, cutact, cutrhs) )
         {
            SCIP_VAR** cutvars;
            SCIP_Real* cutvals;
            SCIP_Real cutnorm;
            int cutlen;

            /* if this is the first successful cut, get the LP solution for all COLUMN variables */
            if( varsolvals == NULL )
            {
               int v;

               SCIP_CALL( SCIPallocBufferArray(scip, &varsolvals, nvars) );
               for( v = 0; v < nvars; ++v )
               {
                  if( SCIPvarGetStatus(vars[v]) == SCIP_VARSTATUS_COLUMN )
                     varsolvals[v] = SCIPvarGetLPSol(vars[v]);
               }
            }
            assert(varsolvals != NULL);

            /* get temporary memory for storing the cut as sparse row */
            SCIP_CALL( SCIPallocBufferArray(scip, &cutvars, nvars) );
            SCIP_CALL( SCIPallocBufferArray(scip, &cutvals, nvars) );

            /* store the cut as sparse row, calculate activity and norm of cut */
            SCIP_CALL( storeCutInArrays(scip, nvars, vars, cutcoefs, varsolvals, normtype,
                  cutvars, cutvals, &cutlen, &cutact, &cutnorm) );

            SCIPdebugMessage(" -> strong CG cut for <%s>: act=%f, rhs=%f, norm=%f, eff=%f, rank=%d\n",
               c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]),
               cutact, cutrhs, cutnorm, (cutact - cutrhs)/cutnorm, cutrank);

            if( SCIPisPositive(scip, cutnorm) && SCIPisEfficacious(scip, (cutact - cutrhs)/cutnorm) )
            {
               SCIP_ROW* cut;
               char cutname[SCIP_MAXSTRLEN];

               /* create the cut */
               if( c >= 0 )
                  (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_x%d", SCIPgetNLPs(scip), c);
               else
                  (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_s%d", SCIPgetNLPs(scip), -c-1);
               SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs, cutislocal, FALSE, sepadata->dynamiccuts) );
               SCIP_CALL( SCIPaddVarsToRow(scip, cut, cutlen, cutvars, cutvals) );
               /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
               SCIProwChgRank(cut, cutrank);

               assert(success);
#ifdef MAKECUTINTEGRAL
               /* try to scale the cut to integral values */
               SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
                     maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
#else
#ifdef MAKEINTCUTINTEGRAL
               /* try to scale the cut to integral values if there are no continuous variables
                *  -> leads to an integral slack variable that can later be used for other cuts
                */
               {
                  int k = 0;
                  while ( k < cutlen && SCIPvarIsIntegral(cutvars[k]) )
                     ++k;
                  if( k == cutlen )
                  {
                     SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
                           maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
                  }
               }
#endif
#endif

#ifndef FORCECUTINTEGRAL
               success = TRUE;
#endif

               if( success )
               {
                  if( !SCIPisCutEfficacious(scip, NULL, cut) )
                  {
                     SCIPdebugMessage(" -> strong CG cut <%s> no longer efficacious: act=%f, rhs=%f, norm=%f, eff=%f\n",
                        cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
                        SCIPgetCutEfficacy(scip, NULL, cut));
                     /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
                     success = FALSE;
                  }
                  else
                  {
                     SCIP_Bool infeasible;

                     SCIPdebugMessage(" -> found strong CG cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
                        cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
                        SCIPgetCutEfficacy(scip, NULL, cut),
                        SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
                        SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut));
                     /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
                     SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE, &infeasible) );
                     if ( infeasible )
                        *result = SCIP_CUTOFF;
                     else
                     {
                        if( !cutislocal )
                        {
                           SCIP_CALL( SCIPaddPoolCut(scip, cut) );
                        }
                        *result = SCIP_SEPARATED;
                     }
                     ncuts++;
                  }
               }
               else
               {
                  SCIPdebugMessage(" -> strong CG cut <%s> couldn't be scaled to integral coefficients: act=%f, rhs=%f, norm=%f, eff=%f\n",
                     cutname, cutact, cutrhs, cutnorm, SCIPgetCutEfficacy(scip, NULL, cut));
               }

               /* release the row */
               SCIP_CALL( SCIPreleaseRow(scip, &cut) );
            }

            /* free temporary memory */
            SCIPfreeBufferArray(scip, &cutvals);
            SCIPfreeBufferArray(scip, &cutvars);
         }
      }
   }

   /* free temporary memory */
   SCIPfreeBufferArrayNull(scip, &varsolvals);
   SCIPfreeBufferArray(scip, &inds);
   SCIPfreeBufferArray(scip, &binvrow);
   SCIPfreeBufferArray(scip, &basisind);
   SCIPfreeBufferArray(scip, &cutcoefs);

   SCIPdebugMessage("end searching strong CG cuts: found %d cuts\n", ncuts);

   sepadata->lastncutsfound = SCIPgetNCutsFound(scip);

   return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecFixandinfer)
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_VAR** cands;
   int ncands;
   int startncands;
   int divedepth;
   SCIP_Bool cutoff;
   SCIP_Real large;

   *result = SCIP_DIDNOTRUN;

   /* we cannot run on problems with continuous variables */
   if( SCIPgetNContVars(scip) > 0 )
      return SCIP_OKAY;

   /* get unfixed variables */
   SCIP_CALL( SCIPgetPseudoBranchCands(scip, &cands, &ncands, NULL) );
   if( ncands == 0 )
      return SCIP_OKAY;

   SCIPdebugMessage("starting fix-and-infer heuristic with %d unfixed integral variables\n", ncands);

   *result = SCIP_DIDNOTFIND;

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

   /* start probing */
   SCIP_CALL( SCIPstartProbing(scip) );

   /* fix variables and propagate inferences as long as the problem is still feasible and there are
    * unfixed integral variables
    */
   cutoff = FALSE;
   divedepth = 0;
   startncands = ncands;

   /* determine large value to set variables to */
   large = SCIPinfinity(scip);
   if( !SCIPisInfinity(scip, 0.1 / SCIPfeastol(scip)) )
      large = 0.1 / SCIPfeastol(scip);

   while( !cutoff && ncands > 0
      && (divedepth < heurdata->minfixings || (startncands - ncands) * 2 * MAXDIVEDEPTH >= startncands * divedepth)
      && !SCIPisStopped(scip) )
   {
      divedepth++;

      /* create next probing node */
      SCIP_CALL( SCIPnewProbingNode(scip) );

      /* fix next variable */
      SCIP_CALL( fixVariable(scip, cands, ncands, large) );

      /* propagate the fixing */
      SCIP_CALL( SCIPpropagateProbing(scip, heurdata->proprounds, &cutoff, NULL) );

      /* get remaining unfixed variables */
      if( !cutoff )
      {
         SCIP_CALL( SCIPgetPseudoBranchCands(scip, &cands, &ncands, NULL) );
      }
   }

   /* check, if we are still feasible */
   if( cutoff )
   {
      SCIPdebugMessage("propagation detected a cutoff\n");
   }
   else if( ncands == 0 )
   {
      SCIP_Bool success;

      success = FALSE;

      /* try to add solution to SCIP */
      SCIP_CALL( SCIPtryCurrentSol(scip, heur, FALSE, FALSE, TRUE, &success) );

      if( success )
      {
         SCIPdebugMessage("found primal feasible solution\n");
         *result = SCIP_FOUNDSOL;
      }
      else
      {
         SCIPdebugMessage("primal solution was rejected\n");
      }
   }
   else
   {
      SCIPdebugMessage("probing was aborted (probing depth: %d, fixed: %d/%d)", divedepth, startncands - ncands, startncands);
   }

   /* end probing */
   SCIP_CALL( SCIPendProbing(scip) );

   return SCIP_OKAY;
}
Пример #14
0
/** 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;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpRapidlearning)
{/*lint --e{715}*/
   SCIP* subscip;                            /* the subproblem created by rapid learning       */
   SCIP_SEPADATA* sepadata;                  /* separator's private data                       */

   SCIP_VAR** vars;                          /* original problem's variables                   */
   SCIP_VAR** subvars;                       /* subproblem's variables                         */
   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */    
   SCIP_HASHMAP* varmapbw;                   /* mapping of sub-SCIP variables to SCIP variables */

   SCIP_CONSHDLR** conshdlrs;                /* array of constraint handler's that might that might obtain conflicts */
   int* oldnconss;                           /* number of constraints without rapid learning conflicts               */

   SCIP_Longint nodelimit;                   /* node limit for the subproblem                  */
   SCIP_Real timelimit;                      /* time limit for the subproblem                  */
   SCIP_Real memorylimit;                    /* memory limit for the subproblem                */

   int nconshdlrs;                           /* size of conshdlr and oldnconss array                      */
   int nfixedvars;                           /* number of variables that could be fixed by rapid learning */
   int nvars;                                /* number of variables                                       */           
   int restartnum;                           /* maximal number of conflicts that should be created        */
   int i;                                    /* counter                                                   */

   SCIP_Bool success;                        /* was problem creation / copying constraint successful? */
   SCIP_RETCODE retcode;                     /* used for catching sub-SCIP errors in debug mode */

   int nconflicts;                          /* statistic: number of conflicts applied         */
   int nbdchgs;                             /* statistic: number of bound changes applied     */
   int n1startinfers;                       /* statistic: number of one side infer values     */
   int n2startinfers;                       /* statistic: number of both side infer values    */

   SCIP_Bool soladded;                      /* statistic: was a new incumbent found?          */
   SCIP_Bool dualboundchg;                  /* statistic: was a new dual bound found?         */
   SCIP_Bool disabledualreductions;         /* TRUE, if dual reductions in sub-SCIP are not valid for original SCIP,
                                             * e.g., because a constraint could not be copied or a primal solution
                                             * could not be copied back 
                                             */

   int ndiscvars;

   soladded = FALSE;

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

   *result = SCIP_DIDNOTRUN;
   
   ndiscvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip)+SCIPgetNImplVars(scip);

   /* only run when still not fixed binary variables exists */
   if( ndiscvars == 0 )
      return SCIP_OKAY;

   /* get separator's data */
   sepadata = SCIPsepaGetData(sepa);
   assert(sepadata != NULL);

   /* only run for integer programs */
   if( !sepadata->contvars && ndiscvars != SCIPgetNVars(scip) )
      return SCIP_OKAY;

   /* only run if there are few enough continuous variables */
   if( sepadata->contvars && SCIPgetNContVars(scip) > sepadata->contvarsquot * SCIPgetNVars(scip) )
      return SCIP_OKAY;

   /* do not run if pricers are present */
   if( SCIPgetNActivePricers(scip) > 0 )
      return SCIP_OKAY;

   /* if the separator should be exclusive to the root node, this prevents multiple calls due to restarts */
   if(  SCIPsepaGetFreq(sepa) == 0 && SCIPsepaGetNCalls(sepa) > 0)
      return SCIP_OKAY;

   /* call separator at most once per node */
   if( SCIPsepaGetNCallsAtNode(sepa) > 0 )
      return SCIP_OKAY;

   /* do not call rapid learning, if the problem is too big */
   if( SCIPgetNVars(scip) > sepadata->maxnvars || SCIPgetNConss(scip) > sepadata->maxnconss )
      return SCIP_OKAY; 

   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;
   
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );

   /* initializing the subproblem */  
   SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) ); 
   SCIP_CALL( SCIPcreate(&subscip) );
   SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
   success = FALSE;

   /* copy the subproblem */
   SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rapid", FALSE, FALSE, &success) );
   
   if( sepadata->copycuts )
   {
      /** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
      SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, FALSE) );
   }

   for( i = 0; i < nvars; i++ )
      subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);
   
   SCIPhashmapFree(&varmapfw);
   
   /* this avoids dual presolving */
   if( !success )
   {
      for( i = 0; i < nvars; i++ )
      {     
         SCIP_CALL( SCIPaddVarLocks(subscip, subvars[i], 1, 1 ) );
      }
   }

   SCIPdebugMessage("Copying SCIP was%s successful.\n", success ? "" : " not");
   
   /* mimic an FD solver: DFS, no LP solving, 1-FUIP instead of all-FUIP */
   SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );
   SCIP_CALL( SCIPsetIntParam(subscip, "conflict/fuiplevels", 1) );
   SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/dfs/stdpriority", INT_MAX/4) ); 
   SCIP_CALL( SCIPsetBoolParam(subscip, "constraints/disableenfops", TRUE) );
   SCIP_CALL( SCIPsetIntParam(subscip, "propagating/pseudoobj/freq", -1) );

   /* use inference branching */
   SCIP_CALL( SCIPsetBoolParam(subscip, "branching/inference/useweightedsum", FALSE) );

   /* only create short conflicts */
   SCIP_CALL( SCIPsetRealParam(subscip, "conflict/maxvarsfac", 0.05) );
  
   /* set limits for the subproblem */
   nodelimit = SCIPgetNLPIterations(scip);
   nodelimit = MAX(sepadata->minnodes, nodelimit);
   nodelimit = MIN(sepadata->maxnodes, nodelimit);

   restartnum = 1000;
   
   /* 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) );
   if( !SCIPisInfinity(scip, memorylimit) )   
      memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
   if( timelimit <= 0.0 || memorylimit <= 0.0 )
      goto TERMINATE;

   SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit/5) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
   SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
   SCIP_CALL( SCIPsetIntParam(subscip, "limits/restarts", 0) );
   SCIP_CALL( SCIPsetIntParam(subscip, "conflict/restartnum", restartnum) );

   /* 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) );

   /* 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

   /* add an objective cutoff */
   SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetUpperbound(scip)) );

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

   /* store reversing mapping of variables */
   SCIP_CALL( SCIPtransformProb(subscip) );
   for( i = 0; i < nvars; ++i)
   {  
      SCIP_CALL( SCIPhashmapInsert(varmapbw, SCIPvarGetTransVar(subvars[i]), vars[i]) );
   }

   /** allocate memory for constraints storage. Each constraint that will be created from now on will be a conflict.
    *  Therefore, we need to remember oldnconss to get the conflicts from the FD search. 
    */
   nconshdlrs = 4;
   SCIP_CALL( SCIPallocBufferArray(scip, &conshdlrs, nconshdlrs) );
   SCIP_CALL( SCIPallocBufferArray(scip, &oldnconss, nconshdlrs) );

   /* store number of constraints before rapid learning search */
   conshdlrs[0] = SCIPfindConshdlr(subscip, "bounddisjunction");
   conshdlrs[1] = SCIPfindConshdlr(subscip, "setppc");
   conshdlrs[2] = SCIPfindConshdlr(subscip, "linear");
   conshdlrs[3] = SCIPfindConshdlr(subscip, "logicor");

   /* redundant constraints might be eliminated in presolving */
   SCIP_CALL( SCIPpresolve(subscip));

   for( i = 0; i < nconshdlrs; ++i)
   {
      if( conshdlrs[i] != NULL )
         oldnconss[i] = SCIPconshdlrGetNConss(conshdlrs[i]);
   }

   nfixedvars = SCIPgetNFixedVars(scip);
   
   /* solve the subproblem */
   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("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
   }
 
   /* abort solving, if limit of applied conflicts is reached */
   if( SCIPgetNConflictConssApplied(subscip) >= restartnum )
   {
      SCIPdebugMessage("finish after %lld successful conflict calls.\n", SCIPgetNConflictConssApplied(subscip)); 
   }
   /* if the first 20% of the solution process were successful, proceed */
   else if( (sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPisFeasLT(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
      || (sepadata->applybdchgs && SCIPgetNFixedVars(subscip) > nfixedvars)
      || (sepadata->applyconflicts && SCIPgetNConflictConssApplied(subscip) > 0) ) 
   {
      SCIPdebugMessage("proceed solving after the first 20%% of the solution process, since:\n");

      if( SCIPgetNSols(subscip) > 0 && SCIPisFeasLE(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
      {
         SCIPdebugMessage("   - there was a better solution (%f < %f)\n",SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip));
      }
      if( SCIPgetNFixedVars(subscip) > nfixedvars )
      {
         SCIPdebugMessage("   - there were %d variables fixed\n", SCIPgetNFixedVars(scip)-nfixedvars );
      }
      if( SCIPgetNConflictConssFound(subscip) > 0 )
      {
         SCIPdebugMessage("   - there were %lld conflict constraints created\n", SCIPgetNConflictConssApplied(subscip));
      }

      /* set node limit to 100% */
      SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit) );

      /* solve the subproblem */
      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("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
      }
   }
   else
   {
      SCIPdebugMessage("do not proceed solving after the first 20%% of the solution process.\n");
   }

#ifdef SCIP_DEBUG
   SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif

   disabledualreductions = FALSE;

   /* check, whether a solution was found */
   if( sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPfindHeur(scip, "trysol") != NULL )
   {
      SCIP_HEUR* heurtrysol;
      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 was declared to be feasible 
       */
      nsubsols = SCIPgetNSols(subscip);
      subsols = SCIPgetSols(subscip);
      soladded = FALSE;
      heurtrysol = SCIPfindHeur(scip, "trysol");

      /* sequentially add solutions to trysol heuristic */
      for( i = 0; i < nsubsols && !soladded; ++i )
      {
         SCIPdebugMessage("Try to create new solution by copying subscip solution.\n");
         SCIP_CALL( createNewSol(scip, subscip, subvars, heurtrysol, subsols[i], &soladded) );
      }
      if( !soladded || !SCIPisEQ(scip, SCIPgetSolOrigObj(subscip, subsols[i-1]), SCIPgetSolOrigObj(subscip, subsols[0])) )
         disabledualreductions = TRUE;
   }

   /* if the sub problem was solved completely, we update the dual bound */
   dualboundchg = FALSE;
   if( sepadata->applysolved && !disabledualreductions 
      && (SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL || SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE) )
   {
      /* we need to multiply the dualbound with the scaling factor and add the offset, 
       * because this information has been disregarded in the sub-SCIP */
      SCIPdebugMessage("Update old dualbound %g to new dualbound %g.\n", SCIPgetDualbound(scip), SCIPgetTransObjscale(scip) * SCIPgetDualbound(subscip) + SCIPgetTransObjoffset(scip));

      SCIP_CALL( SCIPupdateLocalDualbound(scip, SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip)) );
      dualboundchg = TRUE;
   }

   /* check, whether conflicts were created */
   nconflicts = 0;
   if( sepadata->applyconflicts && !disabledualreductions && SCIPgetNConflictConssApplied(subscip) > 0 )
   {
      SCIP_HASHMAP* consmap;
      int hashtablesize;

      assert(SCIPgetNConflictConssApplied(subscip) < (SCIP_Longint) INT_MAX);
      hashtablesize = (int) SCIPgetNConflictConssApplied(subscip);
      assert(hashtablesize < INT_MAX/5);
      hashtablesize *= 5;

      /* create the variable mapping hash map */
      SCIP_CALL( SCIPhashmapCreate(&consmap, SCIPblkmem(scip), SCIPcalcHashtableSize(hashtablesize)) );

      /* loop over all constraint handlers that might contain conflict constraints */
      for( i = 0; i < nconshdlrs; ++i)
      {
         /* copy constraints that have been created in FD run */
         if( conshdlrs[i] != NULL && SCIPconshdlrGetNConss(conshdlrs[i]) > oldnconss[i] )
         {
            SCIP_CONS** conss;
            int c;
            int nconss;
            
            nconss = SCIPconshdlrGetNConss(conshdlrs[i]);
            conss = SCIPconshdlrGetConss(conshdlrs[i]);

            /* loop over all constraints that have been added in sub-SCIP run, these are the conflicts */            
            for( c = oldnconss[i]; c < nconss; ++c)
            {
               SCIP_CONS* cons;
               SCIP_CONS* conscopy;
               
               cons = conss[c];
               assert(cons != NULL);        

               success = FALSE;

               SCIP_CALL( SCIPgetConsCopy(subscip, scip, cons, &conscopy, conshdlrs[i], varmapbw, consmap, NULL,
                     SCIPconsIsInitial(cons), SCIPconsIsSeparated(cons), SCIPconsIsEnforced(cons), SCIPconsIsChecked(cons),
                     SCIPconsIsPropagated(cons), TRUE, FALSE, SCIPconsIsDynamic(cons), 
                     SCIPconsIsRemovable(cons), FALSE, TRUE, &success) );

               if( success )
               {
                  nconflicts++;
                  SCIP_CALL( SCIPaddCons(scip, conscopy) );
                  SCIP_CALL( SCIPreleaseCons(scip, &conscopy) );
               }
               else
               {
                  SCIPdebugMessage("failed to copy conflict constraint %s back to original SCIP\n", SCIPconsGetName(cons));
               }
            }
         }
      }   
      SCIPhashmapFree(&consmap);
   }

   /* check, whether tighter global bounds were detected */
   nbdchgs = 0;
   if( sepadata->applybdchgs && !disabledualreductions )
      for( i = 0; i < nvars; ++i )
      {
         SCIP_Bool infeasible;
         SCIP_Bool tightened;
         
         assert(SCIPisLE(scip, SCIPvarGetLbGlobal(vars[i]), SCIPvarGetLbGlobal(subvars[i]))); 
         assert(SCIPisLE(scip, SCIPvarGetLbGlobal(subvars[i]), SCIPvarGetUbGlobal(subvars[i])));
         assert(SCIPisLE(scip, SCIPvarGetUbGlobal(subvars[i]), SCIPvarGetUbGlobal(vars[i])));  
         
         /* update the bounds of the original SCIP, if a better bound was proven in the sub-SCIP */
         SCIP_CALL( SCIPtightenVarUb(scip, vars[i], SCIPvarGetUbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
         if( tightened ) 
            nbdchgs++;
         
         SCIP_CALL( SCIPtightenVarLb(scip, vars[i], SCIPvarGetLbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
         if( tightened )
            nbdchgs++;   
      }

   n1startinfers = 0;
   n2startinfers = 0;

   /* install start values for inference branching */
   if( sepadata->applyinfervals && (!sepadata->reducedinfer || soladded || nbdchgs+nconflicts > 0) )
   {
      for( i = 0; i < nvars; ++i )
      {
         SCIP_Real downinfer;
         SCIP_Real upinfer;
         SCIP_Real downvsids;
         SCIP_Real upvsids;
         SCIP_Real downconflen;
         SCIP_Real upconflen;
        
         /* copy downwards branching statistics */
         downvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);            
         downconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
         downinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);            
         
         /* copy upwards branching statistics */
         upvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);                     
         upconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
         upinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);            
        
         /* memorize statistics */
         if( downinfer+downconflen+downvsids > 0.0 || upinfer+upconflen+upvsids != 0 )
            n1startinfers++;
         
         if( downinfer+downconflen+downvsids > 0.0 && upinfer+upconflen+upvsids != 0 )
            n2startinfers++;
         
         SCIP_CALL( SCIPinitVarBranchStats(scip, vars[i], 0.0, 0.0, downvsids, upvsids, downconflen, upconflen, downinfer, upinfer, 0.0, 0.0) );
      }   
   }
   
   SCIPdebugPrintf("XXX Rapidlearning added %d conflicts, changed %d bounds, %s primal solution, %s dual bound improvement.\n", nconflicts, nbdchgs, soladded ? "found" : "no", 
      dualboundchg ? "found" : "no");

   SCIPdebugPrintf("YYY Infervalues initialized on one side: %5.2f %% of variables, %5.2f %% on both sides\n", 
      100.0 * n1startinfers/(SCIP_Real)nvars, 100.0 * n2startinfers/(SCIP_Real)nvars);

   /* change result pointer */
   if( nconflicts > 0 || dualboundchg )
      *result = SCIP_CONSADDED;
   else if( nbdchgs > 0 )
      *result = SCIP_REDUCEDDOM;
  
   /* free local data */
   SCIPfreeBufferArray(scip, &oldnconss);
   SCIPfreeBufferArray(scip, &conshdlrs);

   SCIPhashmapFree(&varmapbw);

 TERMINATE:
   /* free subproblem */
   SCIPfreeBufferArray(scip, &subvars);
   SCIP_CALL( SCIPfree(&subscip) );
  
   return SCIP_OKAY;
}
Пример #16
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecGcgrens)
{  /*lint --e{715}*/

   SCIP* masterprob;
   SCIP_HEURDATA* heurdata;                  /* heuristic's data                    */
   SCIP_Longint nstallnodes;                 /* number of stalling nodes for the subproblem */

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

   /* get master problem */
   masterprob = GCGrelaxGetMasterprob(scip);
   assert( masterprob != NULL);

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

   *result = SCIP_DELAYED;

   /* do not execute the heuristic on invalid relaxation solutions
    * (which is the case if the node has been cut off)
    */
   if( !SCIPisRelaxSolValid(scip) )
   {
      SCIPdebugMessage("skipping GCG RENS: invalid relaxation solution\n");
      return SCIP_OKAY;
   }

   /* only call heuristic, if an optimal LP solution is at hand */
   if( SCIPgetStage(masterprob) > SCIP_STAGE_SOLVING || SCIPgetLPSolstat(masterprob) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

   /* only continue with some fractional variables */
   if( SCIPgetNExternBranchCands(scip) == 0 )
      return SCIP_OKAY;

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

   /* reward RENS if it succeeded often */
   nstallnodes = (SCIP_Longint)(nstallnodes * 3.0 * (SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur) + 1.0));
   nstallnodes -= 100 * SCIPheurGetNCalls(heur);  /* count the setup costs for the sub-SCIP as 100 nodes */
   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 )
   {
      SCIPdebugMessage("skipping RENS: nstallnodes=%"SCIP_LONGINT_FORMAT", minnodes=%"SCIP_LONGINT_FORMAT"\n", nstallnodes, heurdata->minnodes);
      return SCIP_OKAY;
   }

   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   SCIP_CALL( SCIPapplyGcgrens(scip, heur, result, heurdata->minfixingrate, heurdata->minimprove,
         heurdata->maxnodes, nstallnodes, heurdata->binarybounds, heurdata->uselprows) );

   return SCIP_OKAY;
}
Пример #17
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecIntdiving) /*lint --e{715}*/
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_LPSOLSTAT lpsolstat;
   SCIP_VAR** pseudocands;
   SCIP_VAR** fixcands;
   SCIP_Real* fixcandscores;
   SCIP_Real searchubbound;
   SCIP_Real searchavgbound;
   SCIP_Real searchbound;
   SCIP_Real objval;
   SCIP_Bool lperror;
   SCIP_Bool cutoff;
   SCIP_Bool backtracked;
   SCIP_Longint ncalls;
   SCIP_Longint nsolsfound;
   SCIP_Longint nlpiterations;
   SCIP_Longint maxnlpiterations;
   int nfixcands;
   int nbinfixcands;
   int depth;
   int maxdepth;
   int maxdivedepth;
   int divedepth;
   int nextcand;
   int c;

   assert(heur != NULL);
   assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);
   assert(SCIPhasCurrentNodeLP(scip));

   *result = SCIP_DELAYED;

   /* do not call heuristic of node was already detected to be infeasible */
   if( nodeinfeasible )
      return SCIP_OKAY;

   /* only call heuristic, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   /* only call heuristic, if the LP objective value is smaller than the cutoff bound */
   if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
      return SCIP_OKAY;

   /* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* don't dive two times at the same node */
   if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

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

   /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
   depth = SCIPgetDepth(scip);
   maxdepth = SCIPgetMaxDepth(scip);
   maxdepth = MAX(maxdepth, 100);
   if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
      return SCIP_OKAY;

   /* calculate the maximal number of LP iterations until heuristic is aborted */
   nlpiterations = SCIPgetNNodeLPIterations(scip);
   ncalls = SCIPheurGetNCalls(heur);
   nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
   maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
   maxnlpiterations += heurdata->maxlpiterofs;

   /* don't try to dive, if we took too many LP iterations during diving */
   if( heurdata->nlpiterations >= maxnlpiterations )
      return SCIP_OKAY;

   /* allow at least a certain number of LP iterations in this dive */
   maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);

   /* get unfixed integer variables */
   SCIP_CALL( SCIPgetPseudoBranchCands(scip, &pseudocands, &nfixcands, NULL) );

   /* don't try to dive, if there are no fractional variables */
   if( nfixcands == 0 )
      return SCIP_OKAY;

   /* calculate the objective search bound */
   if( SCIPgetNSolsFound(scip) == 0 )
   {
      if( heurdata->maxdiveubquotnosol > 0.0 )
         searchubbound = SCIPgetLowerbound(scip)
            + heurdata->maxdiveubquotnosol * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
      else
         searchubbound = SCIPinfinity(scip);
      if( heurdata->maxdiveavgquotnosol > 0.0 )
         searchavgbound = SCIPgetLowerbound(scip)
            + heurdata->maxdiveavgquotnosol * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
      else
         searchavgbound = SCIPinfinity(scip);
   }
   else
   {
      if( heurdata->maxdiveubquot > 0.0 )
         searchubbound = SCIPgetLowerbound(scip)
            + heurdata->maxdiveubquot * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
      else
         searchubbound = SCIPinfinity(scip);
      if( heurdata->maxdiveavgquot > 0.0 )
         searchavgbound = SCIPgetLowerbound(scip)
            + heurdata->maxdiveavgquot * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
      else
         searchavgbound = SCIPinfinity(scip);
   }
   searchbound = MIN(searchubbound, searchavgbound);
   if( SCIPisObjIntegral(scip) )
      searchbound = SCIPceil(scip, searchbound);

   /* calculate the maximal diving depth: 10 * min{number of integer variables, max depth} */
   maxdivedepth = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
   maxdivedepth = MIN(maxdivedepth, maxdepth);
   maxdivedepth *= 10;

   *result = SCIP_DIDNOTFIND;

   /* start diving */
   SCIP_CALL( SCIPstartProbing(scip) );

   /* enables collection of variable statistics during probing */
   SCIPenableVarHistory(scip);

   SCIPdebugMessage("(node %" SCIP_LONGINT_FORMAT ") executing intdiving heuristic: depth=%d, %d non-fixed, dualbound=%g, searchbound=%g\n",
      SCIPgetNNodes(scip), SCIPgetDepth(scip), nfixcands, SCIPgetDualbound(scip), SCIPretransformObj(scip, searchbound));

   /* copy the pseudo candidates into own array, because we want to reorder them */
   SCIP_CALL( SCIPduplicateBufferArray(scip, &fixcands, pseudocands, nfixcands) );

   /* sort non-fixed variables by non-increasing inference score, but prefer binaries over integers in any case */
   SCIP_CALL( SCIPallocBufferArray(scip, &fixcandscores, nfixcands) );
   nbinfixcands = 0;
   for( c = 0; c < nfixcands; ++c )
   {
      SCIP_VAR* var;
      SCIP_Real score;
      int colveclen;
      int left;
      int right;
      int i;

      assert(c >= nbinfixcands);
      var = fixcands[c];
      assert(SCIPvarIsIntegral(var));
      colveclen = (SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN ? SCIPcolGetNNonz(SCIPvarGetCol(var)) : 0);
      if( SCIPvarIsBinary(var) )
      {
         score = 500.0 * SCIPvarGetNCliques(var, TRUE) + 100.0 * SCIPvarGetNImpls(var, TRUE)
            + SCIPgetVarAvgInferenceScore(scip, var) + (SCIP_Real)colveclen/100.0;

         /* shift the non-binary variables one slot to the right */
         for( i = c; i > nbinfixcands; --i )
         {
            fixcands[i] = fixcands[i-1];
            fixcandscores[i] = fixcandscores[i-1];
         }
         /* put the new candidate into the first nbinfixcands slot */
         left = 0;
         right = nbinfixcands;
         nbinfixcands++;
      }
      else
      {
         score = 5.0 * (SCIPvarGetNCliques(var, FALSE) + SCIPvarGetNCliques(var, TRUE))
            + SCIPvarGetNImpls(var, FALSE) + SCIPvarGetNImpls(var, TRUE) + SCIPgetVarAvgInferenceScore(scip, var)
            + (SCIP_Real)colveclen/10000.0;

         /* put the new candidate in the slots after the binary candidates */
         left = nbinfixcands;
         right = c;
      }
      for( i = right; i > left && score > fixcandscores[i-1]; --i )
      {
         fixcands[i] = fixcands[i-1];
         fixcandscores[i] = fixcandscores[i-1];
      }
      fixcands[i] = var;
      fixcandscores[i] = score;
      SCIPdebugMessage("  <%s>: ncliques=%d/%d, nimpls=%d/%d, inferencescore=%g, colveclen=%d  ->  score=%g\n",
         SCIPvarGetName(var), SCIPvarGetNCliques(var, FALSE), SCIPvarGetNCliques(var, TRUE),
         SCIPvarGetNImpls(var, FALSE), SCIPvarGetNImpls(var, TRUE), SCIPgetVarAvgInferenceScore(scip, var),
         colveclen, score);
   }
   SCIPfreeBufferArray(scip, &fixcandscores);

   /* get LP objective value */
   lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
   objval = SCIPgetLPObjval(scip);

   /* dive as long we are in the given objective, depth and iteration limits, but if possible, we dive at least with
    * the depth 10
    */
   lperror = FALSE;
   cutoff = FALSE;
   divedepth = 0;
   nextcand = 0;
   while( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL
      && (divedepth < 10
         || (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations && objval < searchbound))
      && !SCIPisStopped(scip) )
   {
      SCIP_VAR* var;
      SCIP_Real bestsolval;
      SCIP_Real bestfixval;
      int bestcand;
      SCIP_Longint nnewlpiterations;
      SCIP_Longint nnewdomreds;

      /* open a new probing node if this will not exceed the maximal tree depth, otherwise stop here */
      if( SCIPgetDepth(scip) < SCIPgetDepthLimit(scip) )
      {
         SCIP_CALL( SCIPnewProbingNode(scip) );
         divedepth++;
      }
      else
         break;

      nnewlpiterations = 0;
      nnewdomreds = 0;

      /* fix binary variable that is closest to 1 in the LP solution to 1;
       * if all binary variables are fixed, fix integer variable with least fractionality in LP solution
       */
      bestcand = -1;
      bestsolval = -1.0;
      bestfixval = 1.0;

      /* look in the binary variables for fixing candidates */
      for( c = nextcand; c < nbinfixcands; ++c )
      {
         SCIP_Real solval;

         var = fixcands[c];

         /* ignore already fixed variables */
         if( var == NULL )
            continue;
         if( SCIPvarGetLbLocal(var) > 0.5 || SCIPvarGetUbLocal(var) < 0.5 )
         {
            fixcands[c] = NULL;
            continue;
         }

         /* get the LP solution value */
         solval = SCIPvarGetLPSol(var);

         if( solval > bestsolval )
         {
            bestcand = c;
            bestfixval = 1.0;
            bestsolval = solval;
            if( SCIPisGE(scip, bestsolval, 1.0) )
            {
               /* we found an unfixed binary variable with LP solution value of 1.0 - there cannot be a better candidate */
               break;
            }
            else if( SCIPisLE(scip, bestsolval, 0.0) )
            {
               /* the variable is currently at 0.0 - this is the only situation where we want to fix it to 0.0 */
               bestfixval = 0.0;
            }
         }
      }

      /* if all binary variables are fixed, look in the integer variables for a fixing candidate */
      if( bestcand == -1 )
      {
         SCIP_Real bestfrac;

         bestfrac = SCIP_INVALID;
         for( c = MAX(nextcand, nbinfixcands); c < nfixcands; ++c )
         {
            SCIP_Real solval;
            SCIP_Real frac;

            var = fixcands[c];

            /* ignore already fixed variables */
            if( var == NULL )
               continue;
            if( SCIPvarGetUbLocal(var) - SCIPvarGetLbLocal(var) < 0.5 )
            {
               fixcands[c] = NULL;
               continue;
            }

            /* get the LP solution value */
            solval = SCIPvarGetLPSol(var);
            frac = SCIPfrac(scip, solval);

            /* ignore integer variables that are currently integral */
            if( SCIPisFeasFracIntegral(scip, frac) )
               continue;

            if( frac < bestfrac )
            {
               bestcand = c;
               bestsolval = solval;
               bestfrac = frac;
               bestfixval = SCIPfloor(scip, bestsolval + 0.5);
               if( SCIPisZero(scip, bestfrac) )
               {
                  /* we found an unfixed integer variable with integral LP solution value */
                  break;
               }
            }
         }
      }
      assert(-1 <= bestcand && bestcand < nfixcands);

      /* if there is no unfixed candidate left, we are done */
      if( bestcand == -1 )
         break;

      var = fixcands[bestcand];
      assert(var != NULL);
      assert(SCIPvarIsIntegral(var));
      assert(SCIPvarGetUbLocal(var) - SCIPvarGetLbLocal(var) > 0.5);
      assert(SCIPisGE(scip, bestfixval, SCIPvarGetLbLocal(var)));
      assert(SCIPisLE(scip, bestfixval, SCIPvarGetUbLocal(var)));

      backtracked = FALSE;
      do
      {
         /* if the variable is already fixed or if the solution value is outside the domain, numerical troubles may have
          * occured or variable was fixed by propagation while backtracking => Abort diving!
          */
         if( SCIPvarGetLbLocal(var) >= SCIPvarGetUbLocal(var) - 0.5 )
         {
            SCIPdebugMessage("Selected variable <%s> already fixed to [%g,%g], diving aborted \n",
               SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var));
            cutoff = TRUE;
            break;
         }
         if( SCIPisFeasLT(scip, bestfixval, SCIPvarGetLbLocal(var)) || SCIPisFeasGT(scip, bestfixval, SCIPvarGetUbLocal(var)) )
         {
            SCIPdebugMessage("selected variable's <%s> solution value is outside the domain [%g,%g] (solval: %.9f), diving aborted\n",
               SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), bestfixval);
            assert(backtracked);
            break;
         }

         /* apply fixing of best candidate */
         SCIPdebugMessage("  dive %d/%d, LP iter %" SCIP_LONGINT_FORMAT "/%" SCIP_LONGINT_FORMAT ", %d unfixed: var <%s>, sol=%g, oldbounds=[%g,%g], fixed to %g\n",
            divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations, SCIPgetNPseudoBranchCands(scip),
            SCIPvarGetName(var), bestsolval, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), bestfixval);
         SCIP_CALL( SCIPfixVarProbing(scip, var, bestfixval) );

         /* apply domain propagation */
         SCIP_CALL( SCIPpropagateProbing(scip, 0, &cutoff, &nnewdomreds) );
         if( !cutoff )
         {
            /* if the best candidate was just fixed to its LP value and no domain reduction was found, the LP solution
             * stays valid, and the LP does not need to be resolved
             */
            if( nnewdomreds > 0 || !SCIPisEQ(scip, bestsolval, bestfixval) )
            {
            /* resolve the diving LP */
               /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
                * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
                */
#ifdef NDEBUG
               SCIP_RETCODE retstat;
               nlpiterations = SCIPgetNLPIterations(scip);
               retstat = SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff);
               if( retstat != SCIP_OKAY )
               {
                  SCIPwarningMessage(scip, "Error while solving LP in Intdiving heuristic; LP solve terminated with code <%d>\n",retstat);
               }
#else
               nlpiterations = SCIPgetNLPIterations(scip);
               SCIP_CALL( SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff) );
#endif

               if( lperror )
                  break;

               /* update iteration count */
               nnewlpiterations = SCIPgetNLPIterations(scip) - nlpiterations;
               heurdata->nlpiterations += nnewlpiterations;

               /* get LP solution status */
               lpsolstat = SCIPgetLPSolstat(scip);
               assert(cutoff || (lpsolstat != SCIP_LPSOLSTAT_OBJLIMIT && lpsolstat != SCIP_LPSOLSTAT_INFEASIBLE &&
                     (lpsolstat != SCIP_LPSOLSTAT_OPTIMAL || SCIPisLT(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)))));
            }
         }

         /* perform backtracking if a cutoff was detected */
         if( cutoff && !backtracked && heurdata->backtrack )
         {
            SCIPdebugMessage("  *** cutoff detected at level %d - backtracking\n", SCIPgetProbingDepth(scip));
            SCIP_CALL( SCIPbacktrackProbing(scip, SCIPgetProbingDepth(scip)-1) );

            /* after backtracking there has to be at least one open node without exceeding the maximal tree depth */
            assert(SCIPgetDepthLimit(scip) > SCIPgetDepth(scip));

            SCIP_CALL( SCIPnewProbingNode(scip) );

            bestfixval = SCIPvarIsBinary(var)
               ? 1.0 - bestfixval
               : (SCIPisGT(scip, bestsolval, bestfixval) && SCIPisFeasLE(scip, bestfixval + 1, SCIPvarGetUbLocal(var)) ? bestfixval + 1 : bestfixval - 1);

            backtracked = TRUE;
         }
         else
            backtracked = FALSE;
      }
      while( backtracked );

      if( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
      {
         SCIP_Bool success;

         /* get new objective value */
         objval = SCIPgetLPObjval(scip);

         if( nnewlpiterations > 0 || !SCIPisEQ(scip, bestsolval, bestfixval) )
         {
            /* we must start again with the first candidate, since the LP solution changed */
            nextcand = 0;

            /* create solution from diving LP and try to round it */
            SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
            SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );
            if( success )
            {
               SCIPdebugMessage("intdiving found roundable primal solution: obj=%g\n",
                  SCIPgetSolOrigObj(scip, heurdata->sol));

               /* try to add solution to SCIP */
               SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );

               /* check, if solution was feasible and good enough */
               if( success )
               {
                  SCIPdebugMessage(" -> solution was feasible and good enough\n");
                  *result = SCIP_FOUNDSOL;
               }
            }
         }
         else
            nextcand = bestcand+1; /* continue with the next candidate in the following loop */
      }
      SCIPdebugMessage("   -> lpsolstat=%d, objval=%g/%g\n", lpsolstat, objval, searchbound);
   }

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &fixcands);

   /* end diving */
   SCIP_CALL( SCIPendProbing(scip) );

   if( *result == SCIP_FOUNDSOL )
      heurdata->nsuccess++;

   SCIPdebugMessage("intdiving heuristic finished\n");

   return SCIP_OKAY;
}
Пример #18
0
/** call writing method */
static
SCIP_RETCODE writeBounds(
   SCIP*                 scip,               /**< SCIP data structure */
   FILE*                 file,               /**< file to write to or NULL */
   SCIP_Bool             writesubmipdualbound/**< write dualbounds of submip roots for all open nodes */
   )
{
   SCIP_NODE** opennodes;
   int nopennodes;
   int n;
   int v;

   assert(scip != NULL);

   nopennodes = -1;

#ifdef LONGSTATS
   SCIPinfoMessage(scip, file, "Status after %"SCIP_LONGINT_FORMAT" processed nodes (%d open)\n", SCIPgetNNodes(scip), SCIPgetNNodesLeft(scip));

   SCIPinfoMessage(scip, file, "Primalbound: %g\n", SCIPgetPrimalbound(scip));
   SCIPinfoMessage(scip, file, "Dualbound: %g\n", SCIPgetDualbound(scip));
#else
   SCIPinfoMessage(scip, file, "PB %g\n", SCIPgetPrimalbound(scip));
#endif

   /* get all open nodes and therefor print all dualbounds */
   for( v = 2; v >= 0; --v )
   {
      SCIP_NODE* node;

      switch( v )
      {
      case 2:
         SCIP_CALL( SCIPgetChildren(scip, &opennodes, &nopennodes) );
         break;
      case 1:
         SCIP_CALL( SCIPgetSiblings(scip, &opennodes, &nopennodes) );
         break;
      case 0:
         SCIP_CALL( SCIPgetLeaves(scip, &opennodes, &nopennodes) );
         break;
      default:
	 assert(0);
	 break;
      }
      assert(nopennodes >= 0);

      /* print all node information */
      for( n = nopennodes - 1; n >= 0 && !SCIPisStopped(scip); --n )
      {
         node = opennodes[n];

         if( writesubmipdualbound )
         {
            SCIP* subscip;
            SCIP_Bool valid;
            SCIP_HASHMAP* varmap;                     /* mapping of SCIP variables to sub-SCIP variables */
            SCIP_VAR** vars;                          /* original problem's variables                    */
            int nvars;
            SCIP_Real submipdb;
	    SCIP_Bool cutoff;

            SCIP_CALL( SCIPcreate(&subscip) );

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

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

            submipdb = SCIP_INVALID;
            valid = FALSE;
	    cutoff = FALSE;
            SCIP_CALL( SCIPcopy(scip, subscip, varmap, NULL, "__boundwriting", TRUE, FALSE, TRUE, &valid) );

            if( valid )
            {
               SCIP_VAR** branchvars;
               SCIP_Real* branchbounds;
               SCIP_BOUNDTYPE* boundtypes;
               int nbranchvars;
               int size;

               size = SCIPnodeGetDepth(node);

               /* allocate memory for all branching decisions */
               SCIP_CALL( SCIPallocBufferArray(scip, &branchvars, size) );
               SCIP_CALL( SCIPallocBufferArray(scip, &branchbounds, size) );
               SCIP_CALL( SCIPallocBufferArray(scip, &boundtypes, size) );

               /* we assume that we only have one branching decision at each node */
               SCIPnodeGetAncestorBranchings( node, branchvars, branchbounds, boundtypes, &nbranchvars, size );

               /* check if did not have enough memory */
               if( nbranchvars > size )
               {
                  size = nbranchvars;
                  SCIP_CALL( SCIPallocBufferArray(scip, &branchvars, size) );
                  SCIP_CALL( SCIPallocBufferArray(scip, &branchbounds, size) );
                  SCIP_CALL( SCIPallocBufferArray(scip, &boundtypes, size) );

                  /* now getting all information */
                  SCIPnodeGetAncestorBranchings( node, branchvars, branchbounds, boundtypes, &nbranchvars, size );
               }

               /* apply all changes to the submip */
               SCIP_CALL( applyDomainChanges(subscip, branchvars, branchbounds, boundtypes, nbranchvars, varmap) );

               /* free memory for all branching decisions */
               SCIPfreeBufferArray(scip, &boundtypes);
               SCIPfreeBufferArray(scip, &branchbounds);
               SCIPfreeBufferArray(scip, &branchvars);

	       /* 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) );
	       /* solve only root node */
	       SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );

	       /* set cutoffbound as objective limit for subscip */
	       SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetCutoffbound(scip)) );

	       SCIP_CALL( SCIPsolve(subscip) );

	       cutoff = (SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE);
	       submipdb = SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip);
	    }

#ifdef LONGSTATS
            SCIPinfoMessage(scip, file, "Node %"SCIP_LONGINT_FORMAT" (depth %d): dualbound: %g, nodesubmiprootdualbound: %g %s\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node), submipdb, cutoff ? "(cutoff)" : "");
#else
	    SCIPinfoMessage(scip, file, "%"SCIP_LONGINT_FORMAT" %d %g %g %s\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node), submipdb, cutoff ? "(cutoff)" : "");
#endif

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

            SCIP_CALL( SCIPfree(&subscip) );
         }
         else
         {
#ifdef LONGSTATS
            SCIPinfoMessage(scip, file, "Node %"SCIP_LONGINT_FORMAT" (depth %d): dualbound: %g\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node));
#else
            SCIPinfoMessage(scip, file, "%"SCIP_LONGINT_FORMAT" %d %g\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node));
#endif
         }
      }
   }

#ifdef LONGSTATS
   SCIPinfoMessage(scip, file, "\n");
#endif

   return SCIP_OKAY;
}
Пример #19
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecMutation)
{  /*lint --e{715}*/
   SCIP_Longint maxnnodes;
   SCIP_Longint nsubnodes;                   /* node limit for the subproblem                       */

   SCIP_HEURDATA* heurdata;                  /* heuristic's data                                    */
   SCIP* subscip;                            /* the subproblem created by mutation                  */
   SCIP_VAR** vars;                          /* original problem's variables                        */
   SCIP_VAR** subvars;                       /* subproblem's variables                              */
   SCIP_HASHMAP* varmapfw;                   /* mapping of SCIP variables to sub-SCIP variables */

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

   int nvars;                                /* number of original problem's variables              */
   int i;

   SCIP_Bool success;

   SCIP_RETCODE retcode;

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

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

   *result = SCIP_DELAYED;

   /* only call heuristic, if feasible solution is available */
   if( SCIPgetNSols(scip) <= 0 )
      return SCIP_OKAY;

   /* only call heuristic, if the best solution comes from transformed problem */
   assert( SCIPgetBestSol(scip) != NULL );
   if( SCIPsolIsOriginal(SCIPgetBestSol(scip)) )
      return SCIP_OKAY;

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

   *result = SCIP_DIDNOTRUN;

   /* only call heuristic, if discrete variables are present */
   if( SCIPgetNBinVars(scip) == 0 && SCIPgetNIntVars(scip) == 0 )
      return SCIP_OKAY;

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

   /* reward mutation if it succeeded often, count the setup costs for the sub-MIP as 100 nodes */
   maxnnodesr *= 1.0 + 2.0 * (SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur) + 1.0);
   maxnnodes = (SCIP_Longint) maxnnodesr - 100 * SCIPheurGetNCalls(heur);
   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 subproblem solving */
   if( nsubnodes < heurdata->minnodes )
       return SCIP_OKAY;

   if( SCIPisStopped(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   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)) );

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

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

      /* get name of the original problem and add the string "_mutationsub" */
      (void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_mutationsub", 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;
      valid = FALSE;

      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rens", TRUE, FALSE, TRUE, &valid) );

      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, heurdata->minfixingrate, &heurdata->randseed, heurdata->uselprows) );

   /* 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", nsubnodes) );
   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 handlers; 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 decutions shall be
    * made for the original SCIP
    */
   if( SCIPfindConshdlr(subscip, "quadratic") != NULL && !SCIPisParamFixed(subscip, "constraints/quadratic/enfolplimit") )
   {
      SCIP_CALL( SCIPsetIntParam(subscip, "constraints/quadratic/enfolplimit", 10) );
   }

   /* 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) );

   /* solve the subproblem */
   SCIPdebugMessage("Solve Mutation 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 Mutation 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;

      /* 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;
}
Пример #20
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecOctane)
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_SOL* sol;
   SCIP_SOL** first_sols;     /* stores the first ffirst sols in order to check for common violation of a row */

   SCIP_VAR** vars;           /* the variables of the problem */
   SCIP_VAR** fracvars;       /* variables, that are fractional in current LP solution */
   SCIP_VAR** subspacevars;   /* the variables on which the search is performed. Either coinciding with vars or with the
                               * space of all fractional variables of the current LP solution */

   SCIP_Real p;               /* n/2 - <delta,x> ( for some facet delta ) */
   SCIP_Real q;               /* <delta,a> */

   SCIP_Real* rayorigin;      /* origin of the ray, vector x in paper */
   SCIP_Real* raydirection;   /* direction of the ray, vector a in paper */
   SCIP_Real* negquotient;    /* negated quotient of rayorigin and raydirection, vector v in paper */
   SCIP_Real* lambda;         /* stores the distance of the facets (s.b.) to the origin of the ray */

   SCIP_Bool usefracspace;    /* determines whether the search concentrates on fractional variables and fixes integer ones */
   SCIP_Bool cons_viol;       /* used for checking whether a linear constraint is violated by one of the possible solutions */
   SCIP_Bool success;
   SCIP_Bool* sign;           /* signature of the direction of the ray */
   SCIP_Bool** facets;        /* list of extended facets */

   int nvars;            /* number of variables  */
   int nbinvars;         /* number of 0-1-variables */
   int nfracvars;        /* number of fractional variables in current LP solution */
   int nsubspacevars;    /* dimension of the subspace on which the search is performed */
   int nfacets;          /* number of facets hidden by the ray that where already found */
   int i;                /* counter */
   int j;                /* counter */
   int f_max;            /* {0,1}-points to be checked */
   int f_first;          /* {0,1}-points to be generated at first in order to check whether a restart is necessary */
   int r;                /* counter */
   int firstrule;

   int* perm;            /* stores the way in which the coordinates were permuted */
   int* fracspace;       /* maps the variables of the subspace to the original variables */

   assert(heur != NULL);
   assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);
   assert(SCIPhasCurrentNodeLP(scip));

   *result = SCIP_DELAYED;

   /* only call heuristic, if an optimal LP solution is at hand */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTRUN;

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

   /* OCTANE is for use in 0-1 programs only */
   if( nvars != nbinvars )
      return SCIP_OKAY;

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

   /* don't call heuristic, if it was not successful enough in the past */
   /*lint --e{647}*/
   if( SCIPgetNNodes(scip) % (SCIPheurGetNCalls(heur) / (100 * SCIPheurGetNBestSolsFound(heur) + 10*heurdata->nsuccess + 1) + 1) != 0 )
      return SCIP_OKAY;

   SCIP_CALL( SCIPgetLPBranchCands(scip, &fracvars, NULL, NULL, &nfracvars, NULL) );

   /* don't use integral starting points */
   if( nfracvars == 0 )
      return SCIP_OKAY;

   /* get working pointers from heurdata */
   sol = heurdata->sol;
   assert( sol != NULL );
   f_max = heurdata->f_max;
   f_first = heurdata->f_first;
   usefracspace = heurdata->usefracspace;

   SCIP_CALL( SCIPallocBufferArray(scip, &fracspace, nvars) );

   /* determine the space one which OCTANE should work either as the whole space or as the space of fractional variables */
   if( usefracspace )
   {
      nsubspacevars = nfracvars;
      SCIP_CALL( SCIPallocBufferArray(scip, &subspacevars, nsubspacevars) );
      BMScopyMemoryArray(subspacevars, fracvars, nsubspacevars);
      for( i = nvars - 1; i >= 0; --i )
         fracspace[i] = -1;
      for( i = nsubspacevars - 1; i >= 0; --i )
         fracspace[SCIPvarGetProbindex(subspacevars[i])] = i;
   }
   else
   {
      int currentindex;

      nsubspacevars = nvars;
      SCIP_CALL( SCIPallocBufferArray(scip, &subspacevars, nsubspacevars) );

      /* only copy the variables which are in the current LP */
      currentindex = 0;
      for( i = 0; i < nvars; ++i )
      {
         if( SCIPcolGetLPPos(SCIPvarGetCol(vars[i])) >= 0 )
         {
            subspacevars[currentindex] = vars[i];
            fracspace[i] = currentindex;
            ++currentindex;

         }
         else
         {
            fracspace[i] = -1;
            --nsubspacevars;
         }
      }
   }

   /* nothing to do for empty search space */
   if( nsubspacevars == 0 )
      return SCIP_OKAY;

   assert(0 < nsubspacevars && nsubspacevars <= nvars);

   for( i = 0; i < nsubspacevars; i++)
      assert(fracspace[SCIPvarGetProbindex(subspacevars[i])] == i);

   /* at most 2^(n-1) facets can be hit */
   if( nsubspacevars < 30 )
   {
      /*lint --e{701}*/
      assert(f_max > 0);
      f_max = MIN(f_max, 1 << (nsubspacevars - 1) );
   }

   f_first = MIN(f_first, f_max);

   /* memory allocation */
   SCIP_CALL( SCIPallocBufferArray(scip, &rayorigin, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &raydirection, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &negquotient, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &sign, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &perm, nsubspacevars) );
   SCIP_CALL( SCIPallocBufferArray(scip, &lambda, f_max + 1) );
   SCIP_CALL( SCIPallocBufferArray(scip, &facets, f_max + 1) );
   for( i = f_max; i >= 0; --i )
   {
      /*lint --e{866}*/
      SCIP_CALL( SCIPallocBufferArray(scip, &facets[i], nsubspacevars) );
   }
   SCIP_CALL( SCIPallocBufferArray(scip, &first_sols, f_first) );

   *result = SCIP_DIDNOTFIND;

   /* starting OCTANE */
   SCIPdebugMessage("run Octane heuristic on %s variables, which are %d vars, generate at most %d facets, using rule number %d\n",
      usefracspace ? "fractional" : "all", nsubspacevars, f_max, (heurdata->lastrule+1)%5);

   /* generate starting point in original coordinates */
   SCIP_CALL( generateStartingPoint(scip, rayorigin, subspacevars, nsubspacevars) );
   for( i = nsubspacevars - 1; i >= 0; --i )
      rayorigin[i] -= 0.5;

   firstrule = heurdata->lastrule;
   ++firstrule;
   for( r = firstrule; r <= firstrule + 10 && !SCIPisStopped(scip); r++ )
   {
      SCIP_ROW** rows;
      int nrows;

      /* generate shooting ray in original coordinates by certain rules */
      switch(r % 5)
      {
      case 1:
         if( heurdata->useavgnbray )
         {
            SCIP_CALL( generateAverageNBRay(scip, raydirection, fracspace, subspacevars, nsubspacevars) );
         }
         break;
      case 2:
         if( heurdata->useobjray )
         {
            SCIP_CALL( generateObjectiveRay(scip, raydirection, subspacevars, nsubspacevars) );
         }
         break;
      case 3:
         if( heurdata->usediffray )
         {
            SCIP_CALL( generateDifferenceRay(scip, raydirection, subspacevars, nsubspacevars) );
         }
         break;
      case 4:
         if( heurdata->useavgwgtray && SCIPisLPSolBasic(scip) )
         {
            SCIP_CALL( generateAverageRay(scip, raydirection, subspacevars, nsubspacevars, TRUE) );
         }
         break;
      case 0:
         if( heurdata->useavgray && SCIPisLPSolBasic(scip) )
         {
            SCIP_CALL( generateAverageRay(scip, raydirection, subspacevars, nsubspacevars, FALSE) );
         }
         break;
      default:
         SCIPerrorMessage("invalid ray rule identifier\n");
         SCIPABORT();
      }

      /* there must be a feasible direction for the shooting ray */
      if( isZero(scip, raydirection, nsubspacevars) )
         continue;

      /* transform coordinates such that raydirection >= 0 */
      flipCoords(rayorigin, raydirection, sign, nsubspacevars);

      for( i = f_max - 1; i >= 0; --i)
         lambda[i] = SCIPinfinity(scip);

      /* calculate negquotient, initialize perm, facets[0], p, and q */
      p = 0.5 * nsubspacevars;
      q = 0.0;
      for( i = nsubspacevars - 1; i >= 0; --i )
      {
         /* calculate negquotient, the ratio of rayorigin and raydirection, paying special attention to the case raydirection[i] == 0 */
         if( SCIPisFeasZero(scip, raydirection[i]) )
         {
            if( rayorigin[i] < 0 )
               negquotient[i] = SCIPinfinity(scip);
            else
               negquotient[i] = -SCIPinfinity(scip);
         }
         else
            negquotient[i] = - (rayorigin[i] / raydirection[i]);

         perm[i] = i;

         /* initialization of facets[0] to the all-one facet with p and q its characteristic values */
         facets[0][i] = TRUE;
         p -= rayorigin[i];
         q += raydirection[i];
      }

      assert(SCIPisPositive(scip, q));

      /* resort the coordinates in nonincreasing order of negquotient */
      SCIPsortDownRealRealRealBoolPtr( negquotient, raydirection, rayorigin, sign, (void**) subspacevars, nsubspacevars);

#ifndef NDEBUG
      for( i = 0; i < nsubspacevars; i++ )
         assert( raydirection[i] >= 0 );
      for( i = 1; i < nsubspacevars; i++ )
         assert( negquotient[i - 1] >= negquotient[i] );
#endif
      /* finished initialization */

      /* find the first facet of the octahedron hit by a ray shot from rayorigin into direction raydirection */
      for( i = 0; i < nsubspacevars && negquotient[i] * q > p; ++i )
      {
         facets[0][i] = FALSE;
         p += 2 * rayorigin[i];
         q -= 2 * raydirection[i];
         assert(SCIPisPositive(scip, p));
         assert(SCIPisPositive(scip, q));
      }

      /* avoid dividing by values close to 0.0 */
      if( !SCIPisFeasPositive(scip, q) )
         continue;

      /* assert necessary for flexelint */
      assert(q > 0);
      lambda[0] = p / q;

      nfacets = 1;

      /* find the first facets hit by the ray */
      for( i = 0; i < nfacets && i < f_first; ++i)
         generateNeighborFacets(scip, facets, lambda, rayorigin, raydirection, negquotient, nsubspacevars, f_max, i, &nfacets);

      /* construct the first ffirst possible solutions */
      for( i = 0; i < nfacets && i < f_first; ++i )
      {
         SCIP_CALL( SCIPcreateSol(scip, &first_sols[i], heur) );
         SCIP_CALL( getSolFromFacet(scip, facets[i], first_sols[i], sign, subspacevars, nsubspacevars) );
         assert( first_sols[i] != NULL );
      }

      /* try, whether there is a row violated by all of the first ffirst solutions */
      cons_viol = FALSE;
      SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
      for( i = nrows - 1; i >= 0; --i )
      {
         if( !SCIProwIsLocal(rows[i]) )
         {
            SCIP_COL** cols;
            SCIP_Real constant;
            SCIP_Real lhs;
            SCIP_Real rhs;
            SCIP_Real rowval;
            SCIP_Real* coeffs;
            int nnonzerovars;
            int k;

            /* get the row's data */
            constant = SCIProwGetConstant(rows[i]);
            lhs = SCIProwGetLhs(rows[i]);
            rhs = SCIProwGetRhs(rows[i]);
            coeffs = SCIProwGetVals(rows[i]);
            nnonzerovars = SCIProwGetNNonz(rows[i]);
            cols = SCIProwGetCols(rows[i]);
            rowval = constant;

            for( j = nnonzerovars - 1; j >= 0; --j )
               rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[0], SCIPcolGetVar(cols[j]));

            /* if the row's lhs is violated by the first sol, test, whether it is violated by the next ones, too */
            if( lhs > rowval )
            {
               cons_viol = TRUE;
               for( k = MIN(f_first, nfacets) - 1; k > 0; --k )
               {
                  rowval = constant;
                  for( j = nnonzerovars - 1; j >= 0; --j )
                     rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[k], SCIPcolGetVar(cols[j]));
                  if( lhs <= rowval )
                  {
                     cons_viol = FALSE;
                     break;
                  }
               }
            }
            /* dito for the right hand side */
            else if( rhs < rowval )
            {
               cons_viol = TRUE;
               for( k = MIN(f_first, nfacets) - 1; k > 0; --k )
               {
                  rowval = constant;
                  for( j = nnonzerovars - 1; j >= 0; --j )
                     rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[k], SCIPcolGetVar(cols[j]));
                  if( rhs >= rowval )
                  {
                     cons_viol = FALSE;
                     break;
                  }
               }
            }
            /* break as soon as one row is violated by all of the ffirst solutions */
            if( cons_viol )
               break;
         }
      }


      if( !cons_viol )
      {
         /* if there was no row violated by all solutions, try whether one or more of them are feasible */
         for( i = MIN(f_first, nfacets) - 1; i >= 0; --i )
         {
            assert(first_sols[i] != NULL);
            SCIP_CALL( SCIPtrySol(scip, first_sols[i], FALSE, TRUE, FALSE, TRUE, &success) );
            if( success )
               *result = SCIP_FOUNDSOL;
         }
         /* search for further facets and construct and try solutions out of facets fixed as closest ones */
         for( i = f_first; i < f_max; ++i)
         {
            if( i >= nfacets )
               break;
            generateNeighborFacets(scip, facets, lambda, rayorigin, raydirection, negquotient, nsubspacevars, f_max, i, &nfacets);
            SCIP_CALL( getSolFromFacet(scip, facets[i], sol, sign, subspacevars, nsubspacevars) );
            SCIP_CALL( SCIPtrySol(scip, sol, FALSE, TRUE, FALSE, TRUE, &success) );
            if( success )
               *result = SCIP_FOUNDSOL;
         }
      }

      /* finished OCTANE */
      for( i = MIN(f_first, nfacets) - 1; i >= 0; --i )
      {
         SCIP_CALL( SCIPfreeSol(scip, &first_sols[i]) );
      }
   }
   heurdata->lastrule = r;

   if( *result == SCIP_FOUNDSOL )
      ++(heurdata->nsuccess);

   /* free temporary memory */
   SCIPfreeBufferArray(scip, &first_sols);
   for( i = f_max; i >= 0; --i )
      SCIPfreeBufferArray(scip, &facets[i]);
   SCIPfreeBufferArray(scip, &facets);
   SCIPfreeBufferArray(scip, &lambda);
   SCIPfreeBufferArray(scip, &perm);
   SCIPfreeBufferArray(scip, &sign);
   SCIPfreeBufferArray(scip, &negquotient);
   SCIPfreeBufferArray(scip, &raydirection);
   SCIPfreeBufferArray(scip, &rayorigin);
   SCIPfreeBufferArray(scip, &subspacevars);
   SCIPfreeBufferArray(scip, &fracspace);

   return SCIP_OKAY;
}