Example #1
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;
}
Example #2
0
/** try one-opt on given solution */
static
SCIP_RETCODE tryOneOpt(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_HEUR*            heur,               /**< indicator heuristic */
   SCIP_HEURDATA*        heurdata,           /**< heuristic data */
   int                   nindconss,          /**< number of indicator constraints */
   SCIP_CONS**           indconss,           /**< indicator constraints */
   SCIP_Bool*            solcand,            /**< values for indicator variables in partial solution */
   int*                  nfoundsols          /**< number of solutions found */
   )
{
   SCIP_Bool cutoff;
   SCIP_Bool lperror;
   SCIP_Bool stored;
   SCIP_SOL* sol;
   int cnt = 0;
   int i;
   int c;

   assert( scip != NULL );
   assert( heur != NULL );
   assert( heurdata != NULL );
   assert( nindconss == 0 || indconss != NULL );
   assert( solcand != NULL );
   assert( nfoundsols != NULL );

   SCIPdebugMessage("Performing one-opt ...\n");
   *nfoundsols = 0;

   SCIP_CALL( SCIPstartProbing(scip) );

   for (i = 0; i < nindconss; ++i)
   {
      SCIP_VAR* binvar;

      /* skip nonactive constraints */
      if ( ! SCIPconsIsActive(indconss[i]) )
         continue;

      binvar = SCIPgetBinaryVarIndicator(indconss[i]);
      assert( binvar != NULL );

      /* skip constraints with fixed variables */
      if ( SCIPvarGetUbLocal(binvar) < 0.5 || SCIPvarGetLbLocal(binvar) > 0.5 )
         continue;

      /* return if the we would exceed the depth limit of the tree */
      if( SCIPgetDepthLimit(scip) <= SCIPgetDepth(scip) )
         break;

      /* get rid of all bound changes */
      SCIP_CALL( SCIPnewProbingNode(scip) );
      ++cnt;

      /* fix variables */
      for (c = 0; c < nindconss; ++c)
      {
         SCIP_Bool s;

         /* skip nonactive constraints */
         if ( ! SCIPconsIsActive(indconss[c]) )
            continue;

         binvar = SCIPgetBinaryVarIndicator(indconss[c]);
         assert( binvar != NULL );

         /* fix variables according to solution candidate, except constraint i */
         if ( c == i )
            s = ! solcand[c];
         else
            s = solcand[c];

         if ( ! s )
         {
            if ( SCIPvarGetLbLocal(binvar) < 0.5 && SCIPvarGetUbLocal(binvar) > 0.5 )
            {
               SCIP_CALL( SCIPchgVarLbProbing(scip, binvar, 1.0) );
            }
         }
         else
         {
            if ( SCIPvarGetUbLocal(binvar) > 0.5 && SCIPvarGetLbLocal(binvar) < 0.5 )
            {
               SCIP_CALL( SCIPchgVarUbProbing(scip, binvar, 0.0) );
            }
         }
      }

      /* propagate variables */
      SCIP_CALL( SCIPpropagateProbing(scip, -1, &cutoff, NULL) );
      if ( cutoff )
      {
         SCIP_CALL( SCIPbacktrackProbing(scip, 0) );
         continue;
      }

      /* solve LP to move continuous variables */
      SCIP_CALL( SCIPsolveProbingLP(scip, -1, &lperror, &cutoff) );

      /* the LP often reaches the objective limit - we currently do not use such solutions */
      if ( lperror || cutoff || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      {
#ifdef SCIP_DEBUG
         if ( lperror )
            SCIPdebugMessage("An LP error occured.\n");
#endif
         SCIP_CALL( SCIPbacktrackProbing(scip, 0) );
         continue;
      }

      /* create solution */
      SCIP_CALL( SCIPcreateSol(scip, &sol, heur) );

      /* copy the current LP solution to the working solution */
      SCIP_CALL( SCIPlinkLPSol(scip, sol) );

      /* check solution for feasibility */
      SCIPdebugMessage("One-opt found solution candidate with value %g.\n", SCIPgetSolTransObj(scip, sol));

      /* only check integrality, because we solved an LP */
      SCIP_CALL( SCIPtrySolFree(scip, &sol, FALSE, FALSE, TRUE, FALSE, &stored) );
      if ( stored )
         ++(*nfoundsols);
      SCIP_CALL( SCIPbacktrackProbing(scip, 0) );
   }
   SCIP_CALL( SCIPendProbing(scip) );

   SCIPdebugMessage("Finished one-opt (tried variables: %d, found sols: %d).\n", cnt, *nfoundsols);

   return SCIP_OKAY;
}
Example #3
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;
}
Example #4
0
/** try given solution */
static
SCIP_RETCODE trySolCandidate(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_HEUR*            heur,               /**< indicator heuristic */
   SCIP_HEURDATA*        heurdata,           /**< heuristic data */
   int                   nindconss,          /**< number of indicator constraints */
   SCIP_CONS**           indconss,           /**< indicator constraints */
   SCIP_Bool*            solcand,            /**< values for indicator variables in partial solution */
   int*                  nfoundsols          /**< number of solutions found */
   )
{
   SCIP_Bool cutoff;
   SCIP_Bool lperror;
   SCIP_Bool stored;
   SCIP_SOL* sol;
   int c;

   assert( scip != NULL );
   assert( heur != NULL );
   assert( heurdata != NULL );
   assert( nindconss == 0 || indconss != NULL );
   assert( solcand != NULL );
   assert( nfoundsols != NULL );

   SCIPdebugMessage("Trying to generate feasible solution with indicators from solution candidate ...\n");
   *nfoundsols = 0;

   SCIP_CALL( SCIPstartProbing(scip) );

   /* we can stop here if we have already reached the maximal depth */
   if( SCIPgetDepthLimit(scip) <= SCIPgetDepth(scip) )
   {
      SCIP_CALL( SCIPendProbing(scip) );
      return SCIP_OKAY;
   }

   SCIP_CALL( SCIPnewProbingNode(scip) );

   /* fix variables */
   for (c = 0; c < nindconss; ++c)
   {
      SCIP_VAR* binvar;

      /* skip nonactive constraints */
      if ( ! SCIPconsIsActive(indconss[c]) )
         continue;

      binvar = SCIPgetBinaryVarIndicator(indconss[c]);
      assert( binvar != NULL );

      /* Fix binary variables not in cover to 1 and corresponding slack variables to 0. The other binary variables are fixed to 0. */
      if ( ! solcand[c] )
      {
         /* to be sure, check for non-fixed variables */
         if ( SCIPvarGetLbLocal(binvar) < 0.5 && SCIPvarGetUbLocal(binvar) > 0.5 )
         {
            SCIP_CALL( SCIPchgVarLbProbing(scip, binvar, 1.0) );
         }
      }
      else
      {
         if ( SCIPvarGetUbLocal(binvar) > 0.5 && SCIPvarGetLbLocal(binvar) < 0.5 )
         {
            SCIP_CALL( SCIPchgVarUbProbing(scip, binvar, 0.0) );
         }
      }
   }

   /* propagate variables */
   SCIP_CALL( SCIPpropagateProbing(scip, -1, &cutoff, NULL) );
   if ( cutoff )
   {
      SCIPdebugMessage("Solution candidate reaches cutoff (in propagation).\n");
      SCIP_CALL( SCIPendProbing(scip) );
      return SCIP_OKAY;
   }

   /* solve LP to move continuous variables */
   SCIP_CALL( SCIPsolveProbingLP(scip, -1, &lperror, &cutoff) );

   /* the LP often reaches the objective limit - we currently do not use such solutions */
   if ( lperror || cutoff || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
   {
#ifdef SCIP_DEBUG
      if ( lperror )
         SCIPdebugMessage("An LP error occured.\n");
      else
         SCIPdebugMessage("Solution candidate reaches cutoff (in LP solving).\n");
#endif
      SCIP_CALL( SCIPendProbing(scip) );
      return SCIP_OKAY;
   }

   /* create solution */
   SCIP_CALL( SCIPcreateSol(scip, &sol, heur) );

   /* copy the current LP solution to the working solution */
   SCIP_CALL( SCIPlinkLPSol(scip, sol) );

   /* check solution for feasibility */
#ifdef SCIP_DEBUG
   SCIPdebugMessage("Found solution candidate with value %g.\n", SCIPgetSolTransObj(scip, sol));
#ifdef SCIP_MORE_DEBUG
   SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) );
#endif
   SCIP_CALL( SCIPtrySolFree(scip, &sol, TRUE, TRUE, TRUE, TRUE, &stored) );
   if ( stored )
   {
      ++(*nfoundsols);
      SCIPdebugMessage("Solution is feasible and stored.\n");
   }
   else
      SCIPdebugMessage("Solution was not stored.\n");
#else
   /* only check integrality, because we solved an LP */
   SCIP_CALL( SCIPtrySolFree(scip, &sol, FALSE, FALSE, TRUE, FALSE, &stored) );
   if ( stored )
      ++(*nfoundsols);
#endif
   SCIP_CALL( SCIPendProbing(scip) );

   /* possibly perform one-opt */
   if ( stored && heurdata->oneopt )
   {
      int nfound = 0;
      assert( *nfoundsols > 0 );
      SCIP_CALL( tryOneOpt(scip, heur, heurdata, nindconss, indconss, solcand, &nfound) );
   }

   return SCIP_OKAY;
}