Exemplo n.º 1
0
static
SCIP_RETCODE selectBranchingVertex(
   SCIP*                 scip,               /**< original SCIP data structure */
   int*                  vertex              /**< the vertex to branch on */
   )
{
   SCIP_PROBDATA* probdata;
   SCIP_VAR** edgevars;
   GRAPH* g;
   SCIP_Real maxflow;
   SCIP_Real* inflow;
   int a;
   int k;
   int nnodes;
   int branchvert;

   /* get problem data */
   probdata = SCIPgetProbData(scip);
   assert(probdata != NULL);

   /* get graph */
   g = SCIPprobdataGetGraph(probdata);
   assert(g != NULL);

   /* LP has not been solved */
   if( !SCIPhasCurrentNodeLP(scip) || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
   {
      *vertex = UNKNOWN;
      return SCIP_OKAY;
   }

   edgevars = SCIPprobdataGetEdgeVars(scip);
   assert(edgevars != NULL);

   nnodes = g->knots;

   SCIP_CALL( SCIPallocBufferArray(scip, &inflow, nnodes) );

   branchvert = UNKNOWN;
   maxflow = 1.0;
   for( k = 0; k < nnodes; k++ )
   {
      inflow[k] = 0.0;
      for( a = g->inpbeg[k]; a != EAT_LAST; a = g->ieat[a] )
	 inflow[k] += SCIPvarGetLPSol(edgevars[a]);

      if( !Is_term(g->term[k]) && SCIPisLT(scip, inflow[k], 1.0) && SCIPisLT(scip, fabs(inflow[k] - 0.5), maxflow) )
      {
         branchvert = k;
	 maxflow = fabs(inflow[k] - 0.5);
         SCIPdebugMessage("new maxflow %f on vertex %d \n", inflow[k], branchvert );
      }
   }
   SCIPdebugMessage("maxflow %f on vertex %d, term? %d \n", maxflow, branchvert, Is_term(g->term[branchvert])  );
   (*vertex) = branchvert;

   SCIPfreeBufferArray(scip, &inflow);

   return SCIP_OKAY;
}
Exemplo n.º 2
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecRandrounding) /*lint --e{715}*/
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_Bool propagate;

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

   *result = SCIP_DIDNOTRUN;

   /* only call heuristic, if an optimal LP solution is at hand or if relaxation solution is available */
   if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL && ! SCIPisRelaxSolValid(scip) )
      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;

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

   /* don't call heuristic, if we have already processed the current LP solution but no relaxation solution is available */
   if ( SCIPgetNLPs(scip) == heurdata->lastlp && ! SCIPisRelaxSolValid(scip) )
      return SCIP_OKAY;

   propagate = (!heurdata->propagateonlyroot || SCIPgetDepth(scip) == 0);

   /* try to round LP solution */
   SCIP_CALL( performLPRandRounding(scip, heurdata, heurtiming, propagate, result) );

   return SCIP_OKAY;
}
Exemplo n.º 3
0
/** perform randomized LP-rounding */
static
SCIP_RETCODE performLPRandRounding(
   SCIP*                 scip,               /**< SCIP main data structure */
   SCIP_HEURDATA*        heurdata,           /**< heuristic data */
   SCIP_HEURTIMING       heurtiming,         /**< heuristic timing mask */
   SCIP_Bool             propagate,          /**< should the heuristic apply SCIP's propagation? */
   SCIP_RESULT*          result              /**< pointer to store the result of the heuristic call */
   )
{
   SCIP_SOL* sol;
   SCIP_VAR** lpcands;
   SCIP_Longint nlps;
   int nlpcands;

   /* 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;

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

   /* only call heuristic, if LP solution is fractional; except we are called during pricing, in this case we
    * want to detect a (mixed) integer (LP) solution which is primal feasible */
   if ( nlpcands == 0  && heurtiming != SCIP_HEURTIMING_DURINGPRICINGLOOP )
      return SCIP_OKAY;

   /* get the working solution from heuristic's local data */
   sol = heurdata->sol;
   assert( sol != NULL );

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

   /* don't call heuristic, if we have already processed the current LP solution */
   nlps = SCIPgetNLPs(scip);
   if( nlps == heurdata->lastlp )
      return SCIP_OKAY;
   heurdata->lastlp = nlps;

   *result = SCIP_DIDNOTFIND;

   /* perform random rounding */
   SCIPdebugMessage("executing rand LP-rounding heuristic: %d fractionals\n", nlpcands);
   SCIP_CALL( performRandRounding(scip, heurdata, sol, lpcands, nlpcands, propagate, result) );

   return SCIP_OKAY;
}
Exemplo n.º 4
0
/** output method of display column to output file stream 'file' */
static
SCIP_DECL_DISPOUTPUT(SCIPdispOutputNfrac)
{  /*lint --e{715}*/
   assert(disp != NULL);
   assert(strcmp(SCIPdispGetName(disp), DISP_NAME_NFRAC) == 0);
   assert(scip != NULL);

   if( SCIPhasCurrentNodeLP(scip) && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
      SCIPdispInt(SCIPgetMessagehdlr(scip), file, SCIPgetNLPBranchCands(scip), DISP_WIDT_NFRAC);
   else
      SCIPinfoMessage(scip, file, "   - ");

   return SCIP_OKAY;
}
Exemplo n.º 5
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;
}
Exemplo n.º 6
0
/* exec the event handler
 *
 * we interrupt the solution process
 */
static
SCIP_DECL_EVENTEXEC(eventExecZeroobj)
{
   SCIP_HEURDATA* heurdata;

   assert(eventhdlr != NULL);
   assert(eventdata != NULL);
   assert(strcmp(SCIPeventhdlrGetName(eventhdlr), EVENTHDLR_NAME) == 0);
   assert(event != NULL);
   assert(SCIPeventGetType(event) & SCIP_EVENTTYPE_NODESOLVED);

   heurdata = (SCIP_HEURDATA*)eventdata;
   assert(heurdata != NULL);

   /* interrupt solution process of sub-SCIP */
   if( SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_ITERLIMIT || SCIPgetNLPIterations(scip) >= heurdata->maxlpiters )
   {
      SCIP_CALL( SCIPinterruptSolve(scip) );
   }

   return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecSimplerounding) /*lint --e{715}*/
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_SOL* sol;
   SCIP_VAR** lpcands;
   SCIP_Real* lpcandssol;
   SCIP_Longint nlps;
   int nlpcands;
   int c;

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

   *result = SCIP_DIDNOTRUN;

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

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

   /* on our first call or after each pricing round, calculate the number of roundable variables */
   if( heurdata->nroundablevars == -1  || heurtiming == SCIP_HEURTIMING_DURINGPRICINGLOOP )
   {
      SCIP_VAR** vars;
      int nvars;
      int nroundablevars;
      int i;

      vars = SCIPgetVars(scip);
      nvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
      nroundablevars = 0;
      for( i = 0; i < nvars; ++i )
      {
         if( SCIPvarMayRoundDown(vars[i]) || SCIPvarMayRoundUp(vars[i]) )
            nroundablevars++;
      }
      heurdata->nroundablevars = nroundablevars;
   }

   /* don't call heuristic if there are no roundable variables; except we are called during pricing, in this case we
    * want to detect a (mixed) integer (LP) solution which is primal feasible */
   if( heurdata->nroundablevars == 0 && heurtiming != SCIP_HEURTIMING_DURINGPRICINGLOOP )
      return SCIP_OKAY;

   /* don't call heuristic, if we have already processed the current LP solution */
   nlps = SCIPgetNLPs(scip);
   if( nlps == heurdata->lastlp )
      return SCIP_OKAY;
   heurdata->lastlp = nlps;

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

   /* only call heuristic, if LP solution is fractional; except we are called during pricing, in this case we
    * want to detect a (mixed) integer (LP) solution which is primal feasible */
   if( nlpcands == 0  && heurtiming != SCIP_HEURTIMING_DURINGPRICINGLOOP )
      return SCIP_OKAY;

   /* don't call heuristic, if there are more fractional variables than roundable ones */
   if( nlpcands > heurdata->nroundablevars )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   SCIPdebugMessage("executing simple rounding heuristic: %d fractionals\n", nlpcands);

   /* get the working solution from heuristic's local data */
   sol = heurdata->sol;
   assert(sol != NULL);

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

   /* round all roundable fractional columns in the corresponding direction as long as no unroundable column was found */
   for( c = 0; c < nlpcands; ++c )
   {
      SCIP_VAR* var;
      SCIP_Real oldsolval;
      SCIP_Real newsolval;
      SCIP_Bool mayrounddown;
      SCIP_Bool mayroundup;

      oldsolval = lpcandssol[c];
      assert(!SCIPisFeasIntegral(scip, oldsolval));
      var = lpcands[c];
      assert(SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN);
      mayrounddown = SCIPvarMayRoundDown(var);
      mayroundup = SCIPvarMayRoundUp(var);
      SCIPdebugMessage("simple rounding heuristic: var <%s>, val=%g, rounddown=%u, roundup=%u\n",
         SCIPvarGetName(var), oldsolval, mayrounddown, mayroundup);

      /* choose rounding direction */
      if( mayrounddown && mayroundup )
      {
         /* we can round in both directions: round in objective function direction */
         if( SCIPvarGetObj(var) >= 0.0 )
            newsolval = SCIPfeasFloor(scip, oldsolval);
         else
            newsolval = SCIPfeasCeil(scip, oldsolval);
      }
      else if( mayrounddown )
         newsolval = SCIPfeasFloor(scip, oldsolval);
      else if( mayroundup )
         newsolval = SCIPfeasCeil(scip, oldsolval);
      else
         break;

      /* store new solution value */
      SCIP_CALL( SCIPsetSolVal(scip, sol, var, newsolval) );
   }

   /* check, if rounding was successful */
   if( c == nlpcands )
   {
      SCIP_Bool stored;

      /* 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, FALSE, &stored) );

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

   return SCIP_OKAY;
}
Exemplo n.º 8
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;
}
Exemplo n.º 9
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;
}
Exemplo n.º 10
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecZirounding)
{  /*lint --e{715}*/
   SCIP_HEURDATA*     heurdata;
   SCIP_SOL*          sol;
   SCIP_VAR**         lpcands;
   SCIP_VAR**         zilpcands;

   SCIP_VAR**         slackvars;
   SCIP_Real*         upslacks;
   SCIP_Real*         downslacks;
   SCIP_Real*         activities;
   SCIP_Real*         slackvarcoeffs;
   SCIP_Bool*         rowneedsslackvar;

   SCIP_ROW**         rows;
   SCIP_Real*         lpcandssol;
   SCIP_Real*         solarray;

   SCIP_Longint       nlps;
   int                currentlpcands;
   int                nlpcands;
   int                nimplfracs;
   int                i;
   int                c;
   int                nslacks;
   int                nroundings;

   SCIP_RETCODE       retcode;

   SCIP_Bool          improvementfound;
   SCIP_Bool          numericalerror;

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

   *result = SCIP_DIDNOTRUN;

   /* 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;

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

   /* Do not call heuristic if deactivation check is enabled and percentage of found solutions in relation
    * to number of calls falls below heurdata->stoppercentage */
   if( heurdata->stopziround && SCIPheurGetNCalls(heur) >= heurdata->minstopncalls
      && SCIPheurGetNSolsFound(heur)/(SCIP_Real)SCIPheurGetNCalls(heur) < heurdata->stoppercentage )
      return SCIP_OKAY;

   /* assure that heuristic has not already been called after the last LP had been solved */
   nlps = SCIPgetNLPs(scip);
   if( nlps == heurdata->lastlp )
      return SCIP_OKAY;

   heurdata->lastlp = nlps;

   /* get fractional variables */
   SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, &nimplfracs) );
   nlpcands = nlpcands + nimplfracs;
   /* make sure that there is at least one fractional variable that should be integral */
   if( nlpcands == 0 )
      return SCIP_OKAY;

   assert(nlpcands > 0);
   assert(lpcands != NULL);
   assert(lpcandssol != NULL);

   /* get LP rows data */
   rows    = SCIPgetLPRows(scip);
   nslacks = SCIPgetNLPRows(scip);

   /* cannot do anything if LP is empty */
   if( nslacks == 0 )
      return SCIP_OKAY;

   assert(rows != NULL);
   assert(nslacks > 0);

   /* get the working solution from heuristic's local data */
   sol = heurdata->sol;
   assert(sol != NULL);

   *result = SCIP_DIDNOTFIND;

   solarray = NULL;
   zilpcands = NULL;

   retcode = SCIP_OKAY;
   /* copy the current LP solution to the working solution and allocate memory for local data */
   SCIP_CALL( SCIPlinkLPSol(scip, sol) );
   SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &solarray, nlpcands), TERMINATE);
   SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &zilpcands, nlpcands), TERMINATE);

   /* copy necessary data to local arrays */
   BMScopyMemoryArray(solarray, lpcandssol, nlpcands);
   BMScopyMemoryArray(zilpcands, lpcands, nlpcands);

   /* allocate buffer data arrays */
   SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &slackvars, nslacks), TERMINATE);
   SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &upslacks, nslacks), TERMINATE);
   SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &downslacks, nslacks), TERMINATE);
   SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &slackvarcoeffs, nslacks), TERMINATE);
   SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &rowneedsslackvar, nslacks), TERMINATE);
   SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &activities, nslacks), TERMINATE);

   BMSclearMemoryArray(slackvars, nslacks);
   BMSclearMemoryArray(slackvarcoeffs, nslacks);
   BMSclearMemoryArray(rowneedsslackvar, nslacks);

   numericalerror = FALSE;
   nroundings = 0;

   /* loop over fractional variables and involved LP rows to find all rows which require a slack variable */
   for( c = 0; c < nlpcands; ++c )
   {
      SCIP_VAR* cand;
      SCIP_ROW** candrows;
      int r;
      int ncandrows;

      cand = zilpcands[c];
      assert(cand != NULL);
      assert(SCIPcolGetLPPos(SCIPvarGetCol(cand)) >= 0);

      candrows = SCIPcolGetRows(SCIPvarGetCol(cand));
      ncandrows = SCIPcolGetNLPNonz(SCIPvarGetCol(cand));

      assert(candrows == NULL || ncandrows > 0);

      for( r = 0; r < ncandrows; ++r )
      {
         int rowpos;

         assert(candrows != NULL); /* to please flexelint */
         assert(candrows[r] != NULL);
         rowpos = SCIProwGetLPPos(candrows[r]);

         if( rowpos >= 0 && SCIPisFeasEQ(scip, SCIProwGetLhs(candrows[r]), SCIProwGetRhs(candrows[r])) )
         {
            rowneedsslackvar[rowpos] = TRUE;
            SCIPdebugMessage("  Row %s needs slack variable for variable %s\n", SCIProwGetName(candrows[r]), SCIPvarGetName(cand));
         }
      }
   }

   /* calculate row slacks for every every row that belongs to the current LP and ensure, that the current solution
    * has no violated constraint -- if any constraint is violated, i.e. a slack is significantly smaller than zero,
    * this will cause the termination of the heuristic because Zirounding does not provide feasibility recovering
    */
   for( i = 0; i < nslacks; ++i )
   {
      SCIP_ROW*          row;
      SCIP_Real          lhs;
      SCIP_Real          rhs;

      row = rows[i];

      assert(row != NULL);

      lhs = SCIProwGetLhs(row);
      rhs = SCIProwGetRhs(row);

      /* get row activity */
      activities[i] = SCIPgetRowActivity(scip, row);
      assert(SCIPisFeasLE(scip, lhs, activities[i]) && SCIPisFeasLE(scip, activities[i], rhs));

      /* in special case if LHS or RHS is (-)infinity slacks have to be initialized as infinity */
      if( SCIPisInfinity(scip, -lhs) )
         downslacks[i] = SCIPinfinity(scip);
      else
         downslacks[i] = activities[i] - lhs;

      if( SCIPisInfinity(scip, rhs) )
         upslacks[i] = SCIPinfinity(scip);
      else
         upslacks[i] = rhs - activities[i];

      SCIPdebugMessage("lhs:%5.2f <= act:%5.2g <= rhs:%5.2g --> down: %5.2g, up:%5.2g\n", lhs, activities[i], rhs, downslacks[i], upslacks[i]);

      /* row is an equation. Try to find a slack variable in the row, i.e.,
       * a continuous variable which occurs only in this row. If no such variable exists,
       * there is no hope for an IP-feasible solution in this round
       */
      if( SCIPisFeasEQ(scip, lhs, rhs) && rowneedsslackvar[i] )
      {
         /* @todo: This is only necessary for rows containing fractional variables. */
         rowFindSlackVar(scip, row, &(slackvars[i]), &(slackvarcoeffs[i]));

         if( slackvars[i] == NULL )
         {
            SCIPdebugMessage("No slack variable found for equation %s, terminating ZI Round heuristic\n", SCIProwGetName(row));
            goto TERMINATE;
         }
         else
         {
            SCIP_Real ubslackvar;
            SCIP_Real lbslackvar;
            SCIP_Real solvalslackvar;
            SCIP_Real coeffslackvar;
            SCIP_Real ubgap;
            SCIP_Real lbgap;

            assert(SCIPvarGetType(slackvars[i]) == SCIP_VARTYPE_CONTINUOUS);
            solvalslackvar = SCIPgetSolVal(scip, sol, slackvars[i]);
            ubslackvar = SCIPvarGetUbGlobal(slackvars[i]);
            lbslackvar = SCIPvarGetLbGlobal(slackvars[i]);

            coeffslackvar = slackvarcoeffs[i];
            assert(!SCIPisFeasZero(scip, coeffslackvar));

            ubgap = ubslackvar - solvalslackvar;
            lbgap = solvalslackvar - lbslackvar;

            if( SCIPisFeasZero(scip, ubgap) )
              ubgap = 0.0;
            if( SCIPisFeasZero(scip, lbgap) )
              lbgap = 0.0;

            if( SCIPisFeasPositive(scip, coeffslackvar) )
            {
              if( !SCIPisInfinity(scip, lbslackvar) )
                upslacks[i] += coeffslackvar * lbgap;
              else
                upslacks[i] = SCIPinfinity(scip);
              if( !SCIPisInfinity(scip, ubslackvar) )
                downslacks[i] += coeffslackvar * ubgap;
              else
                downslacks[i] = SCIPinfinity(scip);
            }
            else
            {
               if( !SCIPisInfinity(scip, ubslackvar) )
                  upslacks[i] -= coeffslackvar * ubgap;
               else
                  upslacks[i] = SCIPinfinity(scip);
               if( !SCIPisInfinity(scip, lbslackvar) )
                  downslacks[i] -= coeffslackvar * lbgap;
               else
                  downslacks[i] = SCIPinfinity(scip);
            }
            SCIPdebugMessage("  Slack variable for row %s at pos %d: %g <= %s = %g <= %g; Coeff %g, upslack = %g, downslack = %g  \n",
               SCIProwGetName(row), SCIProwGetLPPos(row), lbslackvar, SCIPvarGetName(slackvars[i]), solvalslackvar, ubslackvar, coeffslackvar,
               upslacks[i], downslacks[i]);
         }
      }
      /* due to numerical inaccuracies, the rows might be feasible, even if the slacks are
       * significantly smaller than zero -> terminate
       */
      if( SCIPisFeasLT(scip, upslacks[i], 0.0) || SCIPisFeasLT(scip, downslacks[i], 0.0) )
         goto TERMINATE;
   }

   assert(nslacks == 0 || (upslacks != NULL && downslacks != NULL && activities != NULL));

   /* initialize number of remaining variables and flag to enter the main loop */
   currentlpcands = nlpcands;
   improvementfound = TRUE;

   /* iterate over variables as long as there are fractional variables left */
   while( currentlpcands > 0 && improvementfound && (heurdata->maxroundingloops == -1 || nroundings < heurdata->maxroundingloops) )
   {  /*lint --e{850}*/
      improvementfound = FALSE;
      nroundings++;
      SCIPdebugMessage("zirounding enters while loop for %d time with %d candidates left. \n", nroundings, currentlpcands);

      /* check for every remaining fractional variable if a shifting decreases ZI-value of the variable */
      for( c = 0; c < currentlpcands; ++c )
      {
         SCIP_VAR* var;
         SCIP_Real oldsolval;
         SCIP_Real upperbound;
         SCIP_Real lowerbound;
         SCIP_Real up;
         SCIP_Real down;
         SCIP_Real ziup;
         SCIP_Real zidown;
         SCIP_Real zicurrent;
         SCIP_Real shiftval;

         DIRECTION direction;

         /* get values from local data */
         oldsolval = solarray[c];
         var = zilpcands[c];

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

         /* calculate bounds for variable and make sure that there are no numerical inconsistencies */
         upperbound = SCIPinfinity(scip);
         lowerbound = SCIPinfinity(scip);
         calculateBounds(scip, var, oldsolval, &upperbound, &lowerbound, upslacks, downslacks, nslacks, &numericalerror);

         if( numericalerror )
            goto TERMINATE;

         /* calculate the possible values after shifting */
         up   = oldsolval + upperbound;
         down = oldsolval - lowerbound;

         /* if the variable is integer or implicit binary, do not shift further than the nearest integer */
         if( SCIPvarGetType(var) != SCIP_VARTYPE_BINARY)
         {
            SCIP_Real ceilx;
            SCIP_Real floorx;

            ceilx = SCIPfeasCeil(scip, oldsolval);
            floorx = SCIPfeasFloor(scip, oldsolval);
            up   = MIN(up, ceilx);
            down = MAX(down, floorx);
         }

         /* calculate necessary values */
         ziup      = getZiValue(scip, up);
         zidown    = getZiValue(scip, down);
         zicurrent = getZiValue(scip, oldsolval);

         /* calculate the shifting direction that reduces ZI-value the most,
          * if both directions improve ZI-value equally, take the direction which improves the objective
          */
         if( SCIPisFeasLT(scip, zidown, zicurrent) || SCIPisFeasLT(scip, ziup, zicurrent) )
         {
            if( SCIPisFeasEQ(scip,ziup, zidown) )
               direction  = SCIPisFeasGE(scip, SCIPvarGetObj(var), 0.0) ? DIRECTION_DOWN : DIRECTION_UP;
            else if( SCIPisFeasLT(scip, zidown, ziup) )
               direction = DIRECTION_DOWN;
            else
               direction = DIRECTION_UP;

            /* once a possible shifting direction and value have been found, variable value is updated */
            shiftval = (direction == DIRECTION_UP ? up - oldsolval : down - oldsolval);

            /* this improves numerical stability in some cases */
            if( direction == DIRECTION_UP )
               shiftval = MIN(shiftval, upperbound);
            else
               shiftval = MIN(shiftval, lowerbound);
            /* update the solution */
            solarray[c] = direction == DIRECTION_UP ? up : down;
            SCIP_CALL( SCIPsetSolVal(scip, sol, var, solarray[c]) );

            /* update the rows activities and slacks */
            SCIP_CALL( updateSlacks(scip, sol, var, shiftval, upslacks,
                  downslacks, activities, slackvars, slackvarcoeffs, nslacks) );

            SCIPdebugMessage("zirounding update step : %d var index, oldsolval=%g, shiftval=%g\n",
               SCIPvarGetIndex(var), oldsolval, shiftval);
            /* since at least one improvement has been found, heuristic will enter main loop for another time because the improvement
             * might affect many LP rows and their current slacks and thus make further rounding steps possible */
            improvementfound = TRUE;
         }

         /* if solution value of variable has become feasibly integral due to rounding step,
          * variable is put at the end of remaining candidates array so as not to be considered in future loops
          */
         if( SCIPisFeasIntegral(scip, solarray[c]) )
         {
            zilpcands[c] = zilpcands[currentlpcands - 1];
            solarray[c] = solarray[currentlpcands - 1];
            currentlpcands--;

            /* counter is decreased if end of candidates array has not been reached yet */
            if( c < currentlpcands )
               c--;
         }
         else if( nroundings == heurdata->maxroundingloops - 1 )
            goto TERMINATE;
      }
   }

   /* in case that no candidate is left for rounding after the final main loop
    * the found solution has to be checked for feasibility in the original problem
    */
   if( currentlpcands == 0 )
   {
      SCIP_Bool stored;
      SCIP_CALL(SCIPtrySol(scip, sol, FALSE, FALSE, TRUE, FALSE, &stored));
      if( stored )
      {
#ifdef SCIP_DEBUG
         SCIPdebugMessage("found feasible rounded solution:\n");
         SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) );
#endif
         SCIPstatisticMessage("  ZI Round solution value: %g \n", SCIPgetSolOrigObj(scip, sol));

         *result = SCIP_FOUNDSOL;
      }
   }

   /* free memory for all locally allocated data */
 TERMINATE:
   SCIPfreeBufferArrayNull(scip, &activities);
   SCIPfreeBufferArrayNull(scip, &rowneedsslackvar);
   SCIPfreeBufferArrayNull(scip, &slackvarcoeffs);
   SCIPfreeBufferArrayNull(scip, &downslacks);
   SCIPfreeBufferArrayNull(scip, &upslacks);
   SCIPfreeBufferArrayNull(scip, &slackvars);
   SCIPfreeBufferArrayNull(scip, &zilpcands);
   SCIPfreeBufferArrayNull(scip, &solarray);

   return retcode;
}
Exemplo n.º 11
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecOneopt)
{  /*lint --e{715}*/

   SCIP_HEURDATA* heurdata;
   SCIP_SOL* bestsol;                        /* incumbent solution */
   SCIP_SOL* worksol;                        /* heuristic's working solution */
   SCIP_VAR** vars;                          /* SCIP variables                */
   SCIP_VAR** shiftcands;                    /* shiftable variables           */
   SCIP_ROW** lprows;                        /* SCIP LP rows                  */
   SCIP_Real* activities;                    /* row activities for working solution */
   SCIP_Real* shiftvals;

   SCIP_Real lb;
   SCIP_Real ub;
   SCIP_Bool localrows;
   SCIP_Bool valid;
   int nchgbound;
   int nbinvars;
   int nintvars;
   int nvars;
   int nlprows;
   int i;
   int nshiftcands;
   int shiftcandssize;
   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;

   /* we only want to process each solution once */
   bestsol = SCIPgetBestSol(scip);
   if( bestsol == NULL || heurdata->lastsolindex == SCIPsolGetIndex(bestsol) )
      return SCIP_OKAY;

   /* reset the timing mask to its default value (at the root node it could be different) */
   if( SCIPgetNNodes(scip) > 1 )
      SCIPheurSetTimingmask(heur, HEUR_TIMING);

   /* get problem variables */
   SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
   nintvars += nbinvars;

   /* do not run if there are no discrete variables */
   if( nintvars == 0 )
   {
      *result = SCIP_DIDNOTRUN;
      return SCIP_OKAY;
   }

   if( heurtiming == SCIP_HEURTIMING_BEFOREPRESOL )
   {
      SCIP*                 subscip;            /* the subproblem created by zeroobj              */
      SCIP_HASHMAP*         varmapfw;           /* mapping of SCIP variables to sub-SCIP variables */
      SCIP_VAR**            subvars;            /* subproblem's variables                          */
      SCIP_Real* subsolvals;                    /* solution values of the subproblem               */

      SCIP_Real timelimit;                      /* time limit for zeroobj subproblem              */
      SCIP_Real memorylimit;                    /* memory limit for zeroobj subproblem            */

      SCIP_SOL* startsol;
      SCIP_SOL** subsols;
      int nsubsols;

      if( !heurdata->beforepresol )
         return SCIP_OKAY;

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

      /* 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 )
         return SCIP_OKAY;

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

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

      /* copy complete SCIP instance */
      valid = FALSE;
      SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "oneopt", TRUE, FALSE, TRUE, &valid) );
      SCIP_CALL( SCIPtransformProb(subscip) );

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

      /* copy the solution */
      SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
      SCIP_CALL( SCIPgetSolVals(scip, bestsol, nvars, vars, subsolvals) );

      /* create start solution for the subproblem */
      SCIP_CALL( SCIPcreateOrigSol(subscip, &startsol, NULL) );
      SCIP_CALL( SCIPsetSolVals(subscip, startsol, nvars, subvars, subsolvals) );

      /* try to add new solution to sub-SCIP and free it immediately */
      valid = FALSE;
      SCIP_CALL( SCIPtrySolFree(subscip, &startsol, FALSE, FALSE, FALSE, FALSE, &valid) );
      SCIPfreeBufferArray(scip, &subsolvals);
      SCIPhashmapFree(&varmapfw);

      /* disable statistic timing inside sub SCIP */
      SCIP_CALL( SCIPsetBoolParam(subscip, "timing/statistictiming", FALSE) );

      /* deactivate basically everything except oneopt in the sub-SCIP */
      SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
      SCIP_CALL( SCIPsetHeuristics(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
      SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
      SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );
      SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
      SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
      SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
      SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );

      /* if necessary, some of the parameters have to be unfixed first */
      if( SCIPisParamFixed(subscip, "lp/solvefreq") )
      {
         SCIPwarningMessage(scip, "unfixing parameter lp/solvefreq in subscip of oneopt heuristic\n");
         SCIP_CALL( SCIPunfixParam(subscip, "lp/solvefreq") );
      }
      SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );

      if( SCIPisParamFixed(subscip, "heuristics/oneopt/freq") )
      {
         SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/freq in subscip of oneopt heuristic\n");
         SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/freq") );
      }
      SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/oneopt/freq", 1) );

      if( SCIPisParamFixed(subscip, "heuristics/oneopt/forcelpconstruction") )
      {
         SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/forcelpconstruction in subscip of oneopt heuristic\n");
         SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/forcelpconstruction") );
      }
      SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/forcelpconstruction", TRUE) );

      /* avoid recursive call, which would lead to an endless loop */
      if( SCIPisParamFixed(subscip, "heuristics/oneopt/beforepresol") )
      {
         SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/beforepresol in subscip of oneopt heuristic\n");
         SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/beforepresol") );
      }
      SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/beforepresol", FALSE) );

      if( valid )
      {
         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 zeroobj heuristic; sub-SCIP terminated with code <%d>\n",retcode);
         }

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

      /* 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);
      valid = FALSE;
      for( i = 0; i < nsubsols && !valid; ++i )
      {
         SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &valid) );
         if( valid )
            *result = SCIP_FOUNDSOL;
      }

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

      return SCIP_OKAY;
   }

   /* we can only work on solutions valid in the transformed space */
   if( SCIPsolIsOriginal(bestsol) )
      return SCIP_OKAY;

   if( heurtiming == SCIP_HEURTIMING_BEFORENODE && (SCIPhasCurrentNodeLP(scip) || heurdata->forcelpconstruction) )
   {
      SCIP_Bool cutoff;
      cutoff = FALSE;
      SCIP_CALL( SCIPconstructLP(scip, &cutoff) );
      SCIP_CALL( SCIPflushLP(scip) );

      /* get problem variables again, SCIPconstructLP() might have added new variables */
      SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
      nintvars += nbinvars;
   }

   /* we need an LP */
   if( SCIPgetNLPRows(scip) == 0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   nchgbound = 0;

   /* initialize data */
   nshiftcands = 0;
   shiftcandssize = 8;
   heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
   SCIP_CALL( SCIPcreateSolCopy(scip, &worksol, bestsol) );
   SCIPsolSetHeur(worksol,heur);

   SCIPdebugMessage("Starting bound adjustment in 1-opt heuristic\n");

   /* maybe change solution values due to global bound changes first */
   for( i = nvars - 1; i >= 0; --i )
   {
      SCIP_VAR* var;
      SCIP_Real solval;

      var = vars[i];
      lb = SCIPvarGetLbGlobal(var);
      ub = SCIPvarGetUbGlobal(var);

      solval = SCIPgetSolVal(scip, bestsol,var);
      /* old solution value is smaller than the actual lower bound */
      if( SCIPisFeasLT(scip, solval, lb) )
      {
         /* set the solution value to the global lower bound */
         SCIP_CALL( SCIPsetSolVal(scip, worksol, var, lb) );
         ++nchgbound;
         SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to lb %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, lb);
      }
      /* old solution value is greater than the actual upper bound */
      else if( SCIPisFeasGT(scip, solval, SCIPvarGetUbGlobal(var)) )
      {
         /* set the solution value to the global upper bound */
         SCIP_CALL( SCIPsetSolVal(scip, worksol, var, ub) );
         ++nchgbound;
         SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to ub %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, ub);
      }
   }

   SCIPdebugMessage("number of bound changes (due to global bounds) = %d\n", nchgbound);
   SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );

   localrows = FALSE;
   valid = TRUE;

   /* initialize activities */
   for( i = 0; i < nlprows; ++i )
   {
      SCIP_ROW* row;

      row = lprows[i];
      assert(SCIProwGetLPPos(row) == i);

      if( !SCIProwIsLocal(row) )
      {
         activities[i] = SCIPgetRowSolActivity(scip, row, worksol);
         SCIPdebugMessage("Row <%s> has activity %g\n", SCIProwGetName(row), activities[i]);
         if( SCIPisFeasLT(scip, activities[i], SCIProwGetLhs(row)) || SCIPisFeasGT(scip, activities[i], SCIProwGetRhs(row)) )
         {
            valid = FALSE;
            SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
            SCIPdebugMessage("row <%s> activity %g violates bounds, lhs = %g, rhs = %g\n", SCIProwGetName(row), activities[i], SCIProwGetLhs(row), SCIProwGetRhs(row));
            break;
         }
      }
      else
         localrows = TRUE;
   }

   if( !valid )
   {
      /** @todo try to correct lp rows */
      SCIPdebugMessage("Some global bound changes were not valid in lp rows.\n");
      goto TERMINATE;
   }

   SCIP_CALL( SCIPallocBufferArray(scip, &shiftcands, shiftcandssize) );
   SCIP_CALL( SCIPallocBufferArray(scip, &shiftvals, shiftcandssize) );


   SCIPdebugMessage("Starting 1-opt heuristic\n");

   /* enumerate all integer variables and find out which of them are shiftable */
   for( i = 0; i < nintvars; i++ )
   {
      if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
      {
         SCIP_Real shiftval;
         SCIP_Real solval;

         /* find out whether the variable can be shifted */
         solval = SCIPgetSolVal(scip, worksol, vars[i]);
         shiftval = calcShiftVal(scip, vars[i], solval, activities);

         /* insert the variable into the list of shifting candidates */
         if( !SCIPisFeasZero(scip, shiftval) )
         {
            SCIPdebugMessage(" -> Variable <%s> can be shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);

            if( nshiftcands == shiftcandssize)
            {
               shiftcandssize *= 8;
               SCIP_CALL( SCIPreallocBufferArray(scip, &shiftcands, shiftcandssize) );
               SCIP_CALL( SCIPreallocBufferArray(scip, &shiftvals, shiftcandssize) );
            }
            shiftcands[nshiftcands] = vars[i];
            shiftvals[nshiftcands] = shiftval;
            nshiftcands++;
         }
      }
   }

   /* if at least one variable can be shifted, shift variables sorted by their objective */
   if( nshiftcands > 0 )
   {
      SCIP_Real shiftval;
      SCIP_Real solval;
      SCIP_VAR* var;

      /* the case that exactly one variable can be shifted is slightly easier */
      if( nshiftcands == 1 )
      {
         var = shiftcands[0];
         assert(var != NULL);
         solval = SCIPgetSolVal(scip, worksol, var);
         shiftval = shiftvals[0];
         assert(!SCIPisFeasZero(scip,shiftval));
         SCIPdebugMessage(" Only one shiftcand found, var <%s>, which is now shifted by<%1.1f> \n",
            SCIPvarGetName(var), shiftval);
         SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
      }
      else
      {
         SCIP_Real* objcoeffs;

         SCIP_CALL( SCIPallocBufferArray(scip, &objcoeffs, nshiftcands) );

         SCIPdebugMessage(" %d shiftcands found \n", nshiftcands);

         /* sort the variables by their objective, optionally weighted with the shiftval */
         if( heurdata->weightedobj )
         {
            for( i = 0; i < nshiftcands; ++i )
               objcoeffs[i] = SCIPvarGetObj(shiftcands[i])*shiftvals[i];
         }
         else
         {
            for( i = 0; i < nshiftcands; ++i )
               objcoeffs[i] = SCIPvarGetObj(shiftcands[i]);
         }

         /* sort arrays with respect to the first one */
         SCIPsortRealPtr(objcoeffs, (void**)shiftcands, nshiftcands);

         /* try to shift each variable -> Activities have to be updated */
         for( i = 0; i < nshiftcands; ++i )
         {
            var = shiftcands[i];
            assert(var != NULL);
            solval = SCIPgetSolVal(scip, worksol, var);
            shiftval = calcShiftVal(scip, var, solval, activities);
            SCIPdebugMessage(" -> Variable <%s> is now shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);
            assert(i > 0 || !SCIPisFeasZero(scip, shiftval));
            assert(SCIPisFeasGE(scip, solval+shiftval, SCIPvarGetLbGlobal(var)) && SCIPisFeasLE(scip, solval+shiftval, SCIPvarGetUbGlobal(var)));
            SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
            SCIP_CALL( updateRowActivities(scip, activities, var, shiftval) );
         }

         SCIPfreeBufferArray(scip, &objcoeffs);
      }

      /* if the problem is a pure IP, try to install the solution, if it is a MIP, solve LP again to set the continuous
       * variables to the best possible value
       */
      if( nvars == nintvars || !SCIPhasCurrentNodeLP(scip) || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
      {
         SCIP_Bool success;

         /* since we ignore local rows, we cannot guarantee their feasibility and have to set the checklprows flag to
          * TRUE if local rows are present
          */
         SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, localrows, &success) );

         if( success )
         {
            SCIPdebugMessage("found feasible shifted solution:\n");
            SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
            heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
            *result = SCIP_FOUNDSOL;
         }
      }
      else
      {
         SCIP_Bool lperror;
#ifdef NDEBUG
         SCIP_RETCODE retstat;
#endif

         SCIPdebugMessage("shifted solution should be feasible -> solve LP to fix continuous variables to best values\n");

         /* start diving to calculate the LP relaxation */
         SCIP_CALL( SCIPstartDive(scip) );

         /* set the bounds of the variables: fixed for integers, global bounds for continuous */
         for( i = 0; i < nvars; ++i )
         {
            if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
            {
               SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], SCIPvarGetLbGlobal(vars[i])) );
               SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], SCIPvarGetUbGlobal(vars[i])) );
            }
         }
         /* apply this after global bounds to not cause an error with intermediate empty domains */
         for( i = 0; i < nintvars; ++i )
         {
            if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
            {
               solval = SCIPgetSolVal(scip, worksol, vars[i]);
               SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], solval) );
               SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], solval) );
            }
         }

         /* solve LP */
         SCIPdebugMessage(" -> old LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));

         /**@todo in case of an MINLP, if SCIPisNLPConstructed() is TRUE, say, rather solve the NLP instead of the 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
         retstat = SCIPsolveDiveLP(scip, -1, &lperror, NULL);
         if( retstat != SCIP_OKAY )
         { 
            SCIPwarningMessage(scip, "Error while solving LP in Oneopt heuristic; LP solve terminated with code <%d>\n",retstat);
         }
#else
         SCIP_CALL( SCIPsolveDiveLP(scip, -1, &lperror, NULL) );
#endif

         SCIPdebugMessage(" -> new LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));
         SCIPdebugMessage(" -> error=%u, status=%d\n", lperror, SCIPgetLPSolstat(scip));

         /* check if this is a feasible solution */
         if( !lperror && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
         {
            SCIP_Bool success;

            /* copy the current LP solution to the working solution */
            SCIP_CALL( SCIPlinkLPSol(scip, worksol) );
            SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, FALSE, &success) );

            /* check solution for feasibility */
            if( success )
            {
               SCIPdebugMessage("found feasible shifted solution:\n");
               SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
               heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
               *result = SCIP_FOUNDSOL;
            }
         }

         /* terminate the diving */
         SCIP_CALL( SCIPendDive(scip) );
      }
   }
   SCIPdebugMessage("Finished 1-opt heuristic\n");

   SCIPfreeBufferArray(scip, &shiftvals);
   SCIPfreeBufferArray(scip, &shiftcands);

 TERMINATE:
   SCIPfreeBufferArray(scip, &activities);
   SCIP_CALL( SCIPfreeSol(scip, &worksol) );

   return SCIP_OKAY;
}
Exemplo n.º 12
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;
}
Exemplo n.º 13
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecRounding) /*lint --e{715}*/
{  /*lint --e{715}*/
   SCIP_HEURDATA* heurdata;
   SCIP_SOL* sol;
   SCIP_VAR** lpcands;
   SCIP_Real* lpcandssol;
   SCIP_ROW** lprows;
   SCIP_Real* activities;
   SCIP_ROW** violrows;
   int* violrowpos;
   SCIP_Real obj;
   SCIP_Real bestroundval;
   SCIP_Real minobj;
   int nlpcands;
   int nlprows;
   int nfrac;
   int nviolrows;
   int c;
   int r;
   SCIP_Longint nlps;
   SCIP_Longint ncalls;
   SCIP_Longint nsolsfound;
   SCIP_Longint nnodes;

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

   *result = SCIP_DIDNOTRUN;

   /* 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;

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

   /* don't call heuristic, if we have already processed the current LP solution */
   nlps = SCIPgetNLPs(scip);
   if( nlps == heurdata->lastlp )
      return SCIP_OKAY;
   heurdata->lastlp = nlps;

   /* don't call heuristic, if it was not successful enough in the past */
   ncalls = SCIPheurGetNCalls(heur);
   nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur);
   nnodes = SCIPgetNNodes(scip);
   if( nnodes % ((ncalls/heurdata->successfactor)/(nsolsfound+1)+1) != 0 )
      return SCIP_OKAY;

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

   /* only call heuristic, if LP solution is fractional */
   if( nfrac == 0 )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;

   /* get LP rows */
   SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );

   SCIPdebugMessage("executing rounding heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac);

   /* get memory for activities, violated rows, and row violation positions */
   SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) );
   SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) );

   /* get the activities for all globally valid rows;
    * the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated
    */
   nviolrows = 0;
   for( r = 0; r < nlprows; ++r )
   {
      SCIP_ROW* row;

      row = lprows[r];
      assert(SCIProwGetLPPos(row) == r);

      if( !SCIProwIsLocal(row) )
      {
         activities[r] = SCIPgetRowActivity(scip, row);
         if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row))
            || SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) )
         {
            violrows[nviolrows] = row;
            violrowpos[r] = nviolrows;
            nviolrows++;
         }
         else
            violrowpos[r] = -1;
      }
   }

   /* get the working solution from heuristic's local data */
   sol = heurdata->sol;
   assert(sol != NULL);

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

   /* calculate the minimal objective value possible after rounding fractional variables */
   minobj = SCIPgetSolTransObj(scip, sol);
   assert(minobj < SCIPgetCutoffbound(scip));
   for( c = 0; c < nlpcands; ++c )
   {
      obj = SCIPvarGetObj(lpcands[c]);
      bestroundval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]);
      minobj += obj * (bestroundval - lpcandssol[c]);
   }

   /* try to round remaining variables in order to become/stay feasible */
   while( nfrac > 0 )
   {
      SCIP_VAR* roundvar;
      SCIP_Real oldsolval;
      SCIP_Real newsolval;

      SCIPdebugMessage("rounding heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
         nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));

      /* minobj < SCIPgetCutoffbound(scip) should be true, otherwise the rounding variable selection
       * should have returned NULL. Due to possible cancellation we use SCIPisLE. */
      assert( SCIPisLE(scip, minobj, SCIPgetCutoffbound(scip)) );

      /* choose next variable to process:
       *  - if a violated row exists, round a variable decreasing the violation, that has least impact on other rows
       *  - otherwise, round a variable, that has strongest devastating impact on rows in opposite direction
       */
      if( nviolrows > 0 )
      {
         SCIP_ROW* row;
         int rowpos;

         row = violrows[nviolrows-1];
         rowpos = SCIProwGetLPPos(row);
         assert(0 <= rowpos && rowpos < nlprows);
         assert(violrowpos[rowpos] == nviolrows-1);

         SCIPdebugMessage("rounding heuristic: try to fix violated row <%s>: %g <= %g <= %g\n",
            SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row));
         if( SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) )
         {
            /* lhs is violated: select a variable rounding, that increases the activity */
            SCIP_CALL( selectIncreaseRounding(scip, sol, minobj, row, &roundvar, &oldsolval, &newsolval) );
         }
         else
         {
            assert(SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row)));
            /* rhs is violated: select a variable rounding, that decreases the activity */
            SCIP_CALL( selectDecreaseRounding(scip, sol, minobj, row, &roundvar, &oldsolval, &newsolval) );
         }
      }
      else
      {
         SCIPdebugMessage("rounding heuristic: search rounding variable and try to stay feasible\n");
         SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &roundvar, &oldsolval, &newsolval) );
      }

      /* check, whether rounding was possible */
      if( roundvar == NULL )
      {
         SCIPdebugMessage("rounding heuristic:  -> didn't find a rounding variable\n");
         break;
      }

      SCIPdebugMessage("rounding heuristic:  -> round var <%s>, oldval=%g, newval=%g, obj=%g\n",
         SCIPvarGetName(roundvar), oldsolval, newsolval, SCIPvarGetObj(roundvar));

      /* update row activities of globally valid rows */
      SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows, 
            roundvar, oldsolval, newsolval) );

      /* store new solution value and decrease fractionality counter */
      SCIP_CALL( SCIPsetSolVal(scip, sol, roundvar, newsolval) );
      nfrac--;

      /* update minimal objective value possible after rounding remaining variables */
      obj = SCIPvarGetObj(roundvar);
      if( obj > 0.0 && newsolval > oldsolval )
         minobj += obj;
      else if( obj < 0.0 && newsolval < oldsolval )
         minobj -= obj;

      SCIPdebugMessage("rounding heuristic:  -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
         nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
   }

   /* check, if the new solution is feasible */
   if( nfrac == 0 && nviolrows == 0 )
   {
      SCIP_Bool stored;

      /* check solution for feasibility, and add it to solution store if possible
       * neither integrality nor feasibility of LP rows has to be checked, because this is already
       * done in the rounding heuristic itself; however, be better check feasibility of LP rows,
       * because of numerical problems with activity updating
       */
      SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, 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;
      }
   }

   /* free memory buffers */
   SCIPfreeBufferArray(scip, &violrowpos);
   SCIPfreeBufferArray(scip, &violrows);
   SCIPfreeBufferArray(scip, &activities);

   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;
}
Exemplo n.º 15
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;
}
Exemplo n.º 16
0
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecShifting) /*lint --e{715}*/
{   /*lint --e{715}*/
    SCIP_HEURDATA* heurdata;
    SCIP_SOL* sol;
    SCIP_VAR** lpcands;
    SCIP_Real* lpcandssol;
    SCIP_ROW** lprows;
    SCIP_Real* activities;
    SCIP_ROW** violrows;
    SCIP_Real* nincreases;
    SCIP_Real* ndecreases;
    int* violrowpos;
    int* nfracsinrow;
    SCIP_Real increaseweight;
    SCIP_Real obj;
    SCIP_Real bestshiftval;
    SCIP_Real minobj;
    int nlpcands;
    int nlprows;
    int nvars;
    int nfrac;
    int nviolrows;
    int nprevviolrows;
    int minnviolrows;
    int nnonimprovingshifts;
    int c;
    int r;
    SCIP_Longint nlps;
    SCIP_Longint ncalls;
    SCIP_Longint nsolsfound;
    SCIP_Longint nnodes;

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

    *result = SCIP_DIDNOTRUN;

    /* 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;

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

    /* don't call heuristic, if we have already processed the current LP solution */
    nlps = SCIPgetNLPs(scip);
    if( nlps == heurdata->lastlp )
        return SCIP_OKAY;
    heurdata->lastlp = nlps;

    /* don't call heuristic, if it was not successful enough in the past */
    ncalls = SCIPheurGetNCalls(heur);
    nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur);
    nnodes = SCIPgetNNodes(scip);
    if( nnodes % ((ncalls/100)/(nsolsfound+1)+1) != 0 )
        return SCIP_OKAY;

    /* get fractional variables, that should be integral */
    /* todo check if heuristic should include implicit integer variables for its calculations */
    SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) );
    nfrac = nlpcands;

    /* only call heuristic, if LP solution is fractional */
    if( nfrac == 0 )
        return SCIP_OKAY;

    *result = SCIP_DIDNOTFIND;

    /* get LP rows */
    SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );

    SCIPdebugMessage("executing shifting heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac);

    /* get memory for activities, violated rows, and row violation positions */
    nvars = SCIPgetNVars(scip);
    SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
    SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) );
    SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) );
    SCIP_CALL( SCIPallocBufferArray(scip, &nfracsinrow, nlprows) );
    SCIP_CALL( SCIPallocBufferArray(scip, &nincreases, nvars) );
    SCIP_CALL( SCIPallocBufferArray(scip, &ndecreases, nvars) );
    BMSclearMemoryArray(nfracsinrow, nlprows);
    BMSclearMemoryArray(nincreases, nvars);
    BMSclearMemoryArray(ndecreases, nvars);

    /* get the activities for all globally valid rows;
     * the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated
     */
    nviolrows = 0;
    for( r = 0; r < nlprows; ++r )
    {
        SCIP_ROW* row;

        row = lprows[r];
        assert(SCIProwGetLPPos(row) == r);

        if( !SCIProwIsLocal(row) )
        {
            activities[r] = SCIPgetRowActivity(scip, row);
            if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row))
                    || SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) )
            {
                violrows[nviolrows] = row;
                violrowpos[r] = nviolrows;
                nviolrows++;
            }
            else
                violrowpos[r] = -1;
        }
    }

    /* calc the current number of fractional variables in rows */
    for( c = 0; c < nlpcands; ++c )
        addFracCounter(nfracsinrow, nlprows, lpcands[c], +1);

    /* get the working solution from heuristic's local data */
    sol = heurdata->sol;
    assert(sol != NULL);

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

    /* calculate the minimal objective value possible after rounding fractional variables */
    minobj = SCIPgetSolTransObj(scip, sol);
    assert(minobj < SCIPgetCutoffbound(scip));
    for( c = 0; c < nlpcands; ++c )
    {
        obj = SCIPvarGetObj(lpcands[c]);
        bestshiftval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]);
        minobj += obj * (bestshiftval - lpcandssol[c]);
    }

    /* try to shift remaining variables in order to become/stay feasible */
    nnonimprovingshifts = 0;
    minnviolrows = INT_MAX;
    increaseweight = 1.0;
    while( (nfrac > 0 || nviolrows > 0) && nnonimprovingshifts < MAXSHIFTINGS )
    {
        SCIP_VAR* shiftvar;
        SCIP_Real oldsolval;
        SCIP_Real newsolval;
        SCIP_Bool oldsolvalisfrac;
        int probindex;

        SCIPdebugMessage("shifting heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g), cutoff=%g\n",
                         nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj),
                         SCIPretransformObj(scip, SCIPgetCutoffbound(scip)));

        nprevviolrows = nviolrows;

        /* choose next variable to process:
         *  - if a violated row exists, shift a variable decreasing the violation, that has least impact on other rows
         *  - otherwise, shift a variable, that has strongest devastating impact on rows in opposite direction
         */
        shiftvar = NULL;
        oldsolval = 0.0;
        newsolval = 0.0;
        if( nviolrows > 0 && (nfrac == 0 || nnonimprovingshifts < MAXSHIFTINGS-1) )
        {
            SCIP_ROW* row;
            int rowidx;
            int rowpos;
            int direction;

            rowidx = -1;
            rowpos = -1;
            row = NULL;
            if( nfrac > 0 )
            {
                for( rowidx = nviolrows-1; rowidx >= 0; --rowidx )
                {
                    row = violrows[rowidx];
                    rowpos = SCIProwGetLPPos(row);
                    assert(violrowpos[rowpos] == rowidx);
                    if( nfracsinrow[rowpos] > 0 )
                        break;
                }
            }
            if( rowidx == -1 )
            {
                rowidx = SCIPgetRandomInt(0, nviolrows-1, &heurdata->randseed);
                row = violrows[rowidx];
                rowpos = SCIProwGetLPPos(row);
                assert(0 <= rowpos && rowpos < nlprows);
                assert(violrowpos[rowpos] == rowidx);
                assert(nfracsinrow[rowpos] == 0);
            }
            assert(violrowpos[rowpos] == rowidx);

            SCIPdebugMessage("shifting heuristic: try to fix violated row <%s>: %g <= %g <= %g\n",
                             SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row));
            SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );

            /* get direction in which activity must be shifted */
            assert(SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row))
                   || SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row)));
            direction = SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) ? +1 : -1;

            /* search a variable that can shift the activity in the necessary direction */
            SCIP_CALL( selectShifting(scip, sol, row, activities[rowpos], direction,
                                      nincreases, ndecreases, increaseweight, &shiftvar, &oldsolval, &newsolval) );
        }

        if( shiftvar == NULL && nfrac > 0 )
        {
            SCIPdebugMessage("shifting heuristic: search rounding variable and try to stay feasible\n");
            SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &shiftvar, &oldsolval, &newsolval) );
        }

        /* check, whether shifting was possible */
        if( shiftvar == NULL || SCIPisEQ(scip, oldsolval, newsolval) )
        {
            SCIPdebugMessage("shifting heuristic:  -> didn't find a shifting variable\n");
            break;
        }

        SCIPdebugMessage("shifting heuristic:  -> shift var <%s>[%g,%g], type=%d, oldval=%g, newval=%g, obj=%g\n",
                         SCIPvarGetName(shiftvar), SCIPvarGetLbGlobal(shiftvar), SCIPvarGetUbGlobal(shiftvar), SCIPvarGetType(shiftvar),
                         oldsolval, newsolval, SCIPvarGetObj(shiftvar));

        /* update row activities of globally valid rows */
        SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows,
                                    shiftvar, oldsolval, newsolval) );
        if( nviolrows >= nprevviolrows )
            nnonimprovingshifts++;
        else if( nviolrows < minnviolrows )
        {
            minnviolrows = nviolrows;
            nnonimprovingshifts = 0;
        }

        /* store new solution value and decrease fractionality counter */
        SCIP_CALL( SCIPsetSolVal(scip, sol, shiftvar, newsolval) );

        /* update fractionality counter and minimal objective value possible after shifting remaining variables */
        oldsolvalisfrac = !SCIPisFeasIntegral(scip, oldsolval)
                          && (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER);
        obj = SCIPvarGetObj(shiftvar);
        if( (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER)
                && oldsolvalisfrac )
        {
            assert(SCIPisFeasIntegral(scip, newsolval));
            nfrac--;
            nnonimprovingshifts = 0;
            minnviolrows = INT_MAX;
            addFracCounter(nfracsinrow, nlprows, shiftvar, -1);

            /* the rounding was already calculated into the minobj -> update only if rounding in "wrong" direction */
            if( obj > 0.0 && newsolval > oldsolval )
                minobj += obj;
            else if( obj < 0.0 && newsolval < oldsolval )
                minobj -= obj;
        }
        else
        {
            /* update minimal possible objective value */
            minobj += obj * (newsolval - oldsolval);
        }

        /* update increase/decrease arrays */
        if( !oldsolvalisfrac )
        {
            probindex = SCIPvarGetProbindex(shiftvar);
            assert(0 <= probindex && probindex < nvars);
            increaseweight *= WEIGHTFACTOR;
            if( newsolval < oldsolval )
                ndecreases[probindex] += increaseweight;
            else
                nincreases[probindex] += increaseweight;
            if( increaseweight >= 1e+09 )
            {
                int i;

                for( i = 0; i < nvars; ++i )
                {
                    nincreases[i] /= increaseweight;
                    ndecreases[i] /= increaseweight;
                }
                increaseweight = 1.0;
            }
        }

        SCIPdebugMessage("shifting heuristic:  -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
                         nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
    }

    /* check, if the new solution is feasible */
    if( nfrac == 0 && nviolrows == 0 )
    {
        SCIP_Bool stored;

        /* check solution for feasibility, and add it to solution store if possible
         * neither integrality nor feasibility of LP rows has to be checked, because this is already
         * done in the shifting heuristic itself; however, we better check feasibility of LP rows,
         * because of numerical problems with activity updating
         */
        SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );

        if( stored )
        {
            SCIPdebugMessage("found feasible shifted solution:\n");
            SCIPdebug( SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) ) );
            *result = SCIP_FOUNDSOL;
        }
    }

    /* free memory buffers */
    SCIPfreeBufferArray(scip, &ndecreases);
    SCIPfreeBufferArray(scip, &nincreases);
    SCIPfreeBufferArray(scip, &nfracsinrow);
    SCIPfreeBufferArray(scip, &violrowpos);
    SCIPfreeBufferArray(scip, &violrows);
    SCIPfreeBufferArray(scip, &activities);

    return SCIP_OKAY;
}
Exemplo n.º 17
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;
}
Exemplo n.º 18
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;
}
Exemplo n.º 19
0
/**
 * Selects a variable from a set of candidates by strong branching
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 * @note The variables in the lpcands array must have a fractional value in the current LP solution
 */
SCIP_RETCODE SCIPselectVarPseudoStrongBranching(
   SCIP*                 scip,               /**< original SCIP data structure                        */
   SCIP_VAR**            pseudocands,        /**< branching candidates                                */
   SCIP_Bool*            skipdown,           /**< should down branchings be skipped? */
   SCIP_Bool*            skipup,             /**< should up branchings be skipped? */
   int                   npseudocands,       /**< number of branching candidates                      */
   int                   npriopseudocands,   /**< number of priority branching candidates             */
   SCIP_Bool             allowaddcons,       /**< is the branching rule allowed to add constraints?   */
   int*                  bestpseudocand,     /**< best candidate for branching                        */
   SCIP_Real*            bestdown,           /**< objective value of the down branch for bestcand     */
   SCIP_Real*            bestup,             /**< objective value of the up branch for bestcand       */
   SCIP_Real*            bestscore,          /**< score for bestcand                                  */
   SCIP_Bool*            bestdownvalid,      /**< is bestdown a valid dual bound for the down branch? */
   SCIP_Bool*            bestupvalid,        /**< is bestup a valid dual bound for the up branch?     */
   SCIP_Real*            provedbound,        /**< proved dual bound for current subtree               */
   SCIP_RESULT*          result              /**< result pointer                                      */
   )
{
   SCIP_Real lpobjval;
   SCIP_Bool allcolsinlp;
   SCIP_Bool exactsolve;
#ifndef NDEBUG
   SCIP_Real cutoffbound;
   cutoffbound = SCIPgetCutoffbound(scip);
#endif


   assert(scip != NULL);
   assert(pseudocands != NULL);
   assert(bestpseudocand != NULL);
   assert(skipdown != NULL);
   assert(skipup != NULL);
   assert(bestdown != NULL);
   assert(bestup != NULL);
   assert(bestscore != NULL);
   assert(bestdownvalid != NULL);
   assert(bestupvalid != NULL);
   assert(provedbound != NULL);
   assert(result != NULL);
   assert(SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL);

   /* get current LP objective bound of the local sub problem and global cutoff bound */
   lpobjval = SCIPgetLPObjval(scip);

   /* check, if we want to solve the problem exactly, meaning that strong branching information is not useful
    * for cutting off sub problems and improving lower bounds of children
    */
   exactsolve = SCIPisExactSolve(scip);

   /* check, if all existing columns are in LP, and thus the strong branching results give lower bounds */
   allcolsinlp = SCIPallColsInLP(scip);

   /* if only one candidate exists, choose this one without applying strong branching */
   *bestpseudocand = 0;
   *bestdown = lpobjval;
   *bestup = lpobjval;
   *bestdownvalid = TRUE;
   *bestupvalid = TRUE;
   *bestscore = -SCIPinfinity(scip);
   *provedbound = lpobjval;
   if( npseudocands > 1 )
   {
      SCIP_BRANCHRULE* branchrule;
      SCIP_BRANCHRULEDATA* branchruledata;

      SCIP_Real solval;
      SCIP_Real down;
      SCIP_Real up;
      SCIP_Real downgain;
      SCIP_Real upgain;
      SCIP_Real score;
      SCIP_Bool integral;
      SCIP_Bool lperror;
      SCIP_Bool downvalid;
      SCIP_Bool upvalid;
      SCIP_Bool downinf;
      SCIP_Bool upinf;
      SCIP_Bool downconflict;
      SCIP_Bool upconflict;
      int nsbcalls;
      int i;
      int c;

      branchrule = SCIPfindBranchrule(scip, BRANCHRULE_NAME);
      assert(branchrule != NULL);

      /* get branching rule data */
      branchruledata = SCIPbranchruleGetData(branchrule);
      assert(branchruledata != NULL);


      /* initialize strong branching */
      SCIP_CALL( SCIPstartStrongbranch(scip, FALSE) );

      /* search the full strong candidate:
       * cycle through the candidates, starting with the position evaluated in the last run
       */
      nsbcalls = 0;
      for( i = 0, c = branchruledata->lastcand; i < npseudocands; ++i, ++c )
      {
         c = c % npseudocands;
         assert(pseudocands[c] != NULL);

         /* we can only apply strong branching on COLUMN variables that are in the current LP */
         if( !SCIPvarIsInLP(pseudocands[c]) )
            continue;

         solval = SCIPvarGetLPSol(pseudocands[c]);
         integral = SCIPisFeasIntegral(scip, solval);

         SCIPdebugMessage("applying strong branching on %s variable <%s>[%g,%g] with solution %g\n",
            integral ? "integral" : "fractional", SCIPvarGetName(pseudocands[c]), SCIPvarGetLbLocal(pseudocands[c]),
            SCIPvarGetUbLocal(pseudocands[c]), solval);

         up = -SCIPinfinity(scip);
         down = -SCIPinfinity(scip);

         if( integral )
         {
            SCIP_CALL( SCIPgetVarStrongbranchInt(scip, pseudocands[c], INT_MAX,
                  skipdown[c] ? NULL : &down, skipup[c] ? NULL : &up, &downvalid, &upvalid, &downinf, &upinf, &downconflict, &upconflict, &lperror) );
         }
         else
         {
            SCIP_CALL( SCIPgetVarStrongbranchFrac(scip, pseudocands[c], INT_MAX,
                  skipdown[c] ? NULL : &down, skipup[c] ? NULL : &up, &downvalid, &upvalid, &downinf, &upinf, &downconflict, &upconflict, &lperror) );
         }
         nsbcalls++;

         /* display node information line in root node */
         if( SCIPgetDepth(scip) == 0 && nsbcalls % 100 == 0 )
         {
            SCIP_CALL( SCIPprintDisplayLine(scip, NULL, SCIP_VERBLEVEL_HIGH, TRUE) );
         }

         /* check for an error in strong branching */
         if( lperror )
         {
            SCIPverbMessage(scip, SCIP_VERBLEVEL_HIGH, NULL,
               "(node %"SCIP_LONGINT_FORMAT") error in strong branching call for variable <%s> with solution %g\n",
               SCIPgetNNodes(scip), SCIPvarGetName(pseudocands[c]), solval);
            break;
         }

         /* evaluate strong branching */
         down = MAX(down, lpobjval);
         up = MAX(up, lpobjval);
         downgain = down - lpobjval;
         upgain = up - lpobjval;
         assert(!allcolsinlp || exactsolve || !downvalid || downinf == SCIPisGE(scip, down, cutoffbound));
         assert(!allcolsinlp || exactsolve || !upvalid || upinf == SCIPisGE(scip, up, cutoffbound));
         assert(downinf || !downconflict);
         assert(upinf || !upconflict);

         /* check if there are infeasible roundings */
         if( downinf || upinf )
         {
            assert(allcolsinlp);
            assert(!exactsolve);

            /* if for both infeasibilities, a conflict constraint was created, we don't need to fix the variable by hand,
             * but better wait for the next propagation round to fix them as an inference, and potentially produce a
             * cutoff that can be analyzed
             */
            if( allowaddcons && downinf == downconflict && upinf == upconflict )
            {
               *result = SCIP_CONSADDED;
               break; /* terminate initialization loop, because constraint was added */
            }
            else if( downinf && upinf )
            {
               if( integral )
               {
                  SCIP_Bool infeasible;
                  SCIP_Bool fixed;

                  /* both bound changes are infeasible: variable can be fixed to its current value */
                  SCIP_CALL( SCIPfixVar(scip, pseudocands[c], solval, &infeasible, &fixed) );
                  assert(!infeasible);
                  assert(fixed);
                  *result = SCIP_REDUCEDDOM;
                  SCIPdebugMessage(" -> integral variable <%s> is infeasible in both directions\n",
                     SCIPvarGetName(pseudocands[c]));
                  break; /* terminate initialization loop, because LP was changed */
               }
               else
               {
                  /* both roundings are infeasible: the node is infeasible */
                  *result = SCIP_CUTOFF;
                  SCIPdebugMessage(" -> fractional variable <%s> is infeasible in both directions\n",
                     SCIPvarGetName(pseudocands[c]));
                  break; /* terminate initialization loop, because node is infeasible */
               }
            }
            else if( downinf )
            {
               SCIP_Real newlb;

               /* downwards rounding is infeasible -> change lower bound of variable to upward rounding */
               newlb = SCIPfeasCeil(scip, solval);
               if( SCIPvarGetLbLocal(pseudocands[c]) < newlb - 0.5 )
               {
                  SCIP_CALL( SCIPchgVarLb(scip, pseudocands[c], newlb) );
                  *result = SCIP_REDUCEDDOM;
                  SCIPdebugMessage(" -> variable <%s> is infeasible in downward branch\n", SCIPvarGetName(pseudocands[c]));
                  break; /* terminate initialization loop, because LP was changed */
               }
            }
            else
            {
               SCIP_Real newub;

               /* upwards rounding is infeasible -> change upper bound of variable to downward rounding */
               assert(upinf);
               newub = SCIPfeasFloor(scip, solval);
               if( SCIPvarGetUbLocal(pseudocands[c]) > newub + 0.5 )
               {
                  SCIP_CALL( SCIPchgVarUb(scip, pseudocands[c], newub) );
                  *result = SCIP_REDUCEDDOM;
                  SCIPdebugMessage(" -> variable <%s> is infeasible in upward branch\n", SCIPvarGetName(pseudocands[c]));
                  break; /* terminate initialization loop, because LP was changed */
               }
            }
         }
         else if( allcolsinlp && !exactsolve && downvalid && upvalid )
         {
            SCIP_Real minbound;

            /* the minimal lower bound of both children is a proved lower bound of the current subtree */
            minbound = MIN(down, up);
            *provedbound = MAX(*provedbound, minbound);
         }

         /* check for a better score, if we are within the maximum priority candidates */
         if( c < npriopseudocands )
         {
            if( integral )
            {

               if( skipdown[c] )
               {
                  downgain = 0.0;
                  score = SCIPgetBranchScore(scip, pseudocands[c], downgain, upgain);
               }
               else if( skipup[c] )
               {
                  upgain = 0.0;
                  score = SCIPgetBranchScore(scip, pseudocands[c], downgain, upgain);
               }
               else
               {
                  SCIP_Real gains[3];

                  gains[0] = downgain;
                  gains[1] = 0.0;
                  gains[2] = upgain;
                  score = SCIPgetBranchScoreMultiple(scip, pseudocands[c], 3, gains);
               }
            }
            else
               score = SCIPgetBranchScore(scip, pseudocands[c], downgain, upgain);

            if( score > *bestscore )
            {
               *bestpseudocand = c;
               *bestdown = down;
               *bestup = up;
               *bestdownvalid = downvalid;
               *bestupvalid = upvalid;
               *bestscore = score;
            }
         }
         else
            score = 0.0;

         /* update pseudo cost values */
         if( !downinf )
         {
            SCIP_CALL( SCIPupdateVarPseudocost(scip, pseudocands[c],
                  solval-SCIPfeasCeil(scip, solval-1.0), downgain, 1.0) );
         }
         if( !upinf )
         {
            SCIP_CALL( SCIPupdateVarPseudocost(scip, pseudocands[c],
                  solval-SCIPfeasFloor(scip, solval+1.0), upgain, 1.0) );
         }

         SCIPdebugMessage(" -> var <%s> (solval=%g, downgain=%g, upgain=%g, score=%g) -- best: <%s> (%g)\n",
            SCIPvarGetName(pseudocands[c]), solval, downgain, upgain, score,
            SCIPvarGetName(pseudocands[*bestpseudocand]), *bestscore);
      }

      /* remember last evaluated candidate */
      branchruledata->lastcand = c;

      /* end strong branching */
      SCIP_CALL( SCIPendStrongbranch(scip) );
   }

   return SCIP_OKAY;
}
Exemplo n.º 20
0
/** reduced cost propagation method for an LP solution */
static
SCIP_DECL_PROPEXEC(propExecRedcost)
{  /*lint --e{715}*/
   SCIP_PROPDATA* propdata;
   SCIP_COL** cols;
   SCIP_Real requiredredcost;
   SCIP_Real cutoffbound;
   SCIP_Real lpobjval;
   SCIP_Bool propbinvars;
   SCIP_Bool cutoff;
   int nchgbds;
   int ncols;
   int c;

   *result = SCIP_DIDNOTRUN;

   /* in case we have a zero objective function, we skip the reduced cost propagator */
   if( SCIPgetNObjVars(scip) == 0 )
      return SCIP_OKAY;

   /* propagator can only be applied during solving stage */
   if( SCIPgetStage(scip) < SCIP_STAGE_SOLVING )
      return SCIP_OKAY;

   /* we cannot apply reduced cost fixing, if we want to solve exactly */
   /**@todo implement reduced cost fixing with interval arithmetics */
   if( SCIPisExactSolve(scip) )
      return SCIP_OKAY;

   /* only call propagator, if the current node has an LP */
   if( !SCIPhasCurrentNodeLP(scip) )
      return SCIP_OKAY;

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

   /* only call propagator, if the current LP is a valid relaxation */
   if( !SCIPisLPRelax(scip) )
      return SCIP_OKAY;

   /* we cannot apply reduced cost strengthening, if no simplex basis is available */
   if( !SCIPisLPSolBasic(scip) )
      return SCIP_OKAY;

   /* get current cutoff bound */
   cutoffbound = SCIPgetCutoffbound(scip);

   /* reduced cost strengthening can only be applied, if we have a finite cutoff */
   if( SCIPisInfinity(scip, cutoffbound) )
      return SCIP_OKAY;

   /* get LP columns */
   cols = SCIPgetLPCols(scip);
   ncols = SCIPgetNLPCols(scip);

   /* do nothing if the LP has no columns (is empty) */
   if( ncols == 0 )
      return SCIP_OKAY;

   /* get propagator data */
   propdata = SCIPpropGetData(prop);
   assert(propdata != NULL);

   /* chack if all integral variables are fixed and the continuous variables should not be propagated */
   if( !propdata->continuous && SCIPgetNPseudoBranchCands(scip) == 0 )
      return SCIP_OKAY;

   /* get LP objective value */
   lpobjval = SCIPgetLPObjval(scip);

   /* check if binary variables should be propagated */
   propbinvars = (SCIPgetDepth(scip) == 0) || (cutoffbound - lpobjval < 5 * propdata->maxredcost);

   /* skip the propagator if the problem has only binary variables and those should not be propagated */
   if( !propbinvars && SCIPgetNVars(scip) == SCIPgetNBinVars(scip) )
      return SCIP_OKAY;

   *result = SCIP_DIDNOTFIND;
   cutoff = FALSE;
   nchgbds = 0;

   /* compute the required reduced cost which are needed for a binary variable to be fixed */
   requiredredcost = cutoffbound - lpobjval;

   SCIPdebugMessage("lpobjval <%g>, cutoffbound <%g>, max reduced <%g>, propgate binary %u, use implics %u\n",
      lpobjval, cutoffbound, propdata->maxredcost, propbinvars, propdata->usefullimplics);

   /* check reduced costs for non-basic columns */
   for( c = 0; c < ncols && !cutoff; ++c )
   {
      SCIP_VAR* var;

      var = SCIPcolGetVar(cols[c]);

      /* skip continuous variables in case the corresponding parameter is set */
      if( !propdata->continuous && !SCIPvarIsIntegral(var) )
         continue;

      if( SCIPvarIsBinary(var) )
      {
         if( propbinvars )
         {
            if( SCIPgetDepth(scip) == 0 )
            {
               SCIP_CALL( propagateRootRedcostBinvar(scip, propdata, var, cols[c], cutoffbound, &nchgbds) );
            }
            else
            {
               SCIP_CALL( propagateRedcostBinvar(scip, propdata, var, cols[c], requiredredcost, &nchgbds, &cutoff) );
            }
         }
      }
      else
      {
         SCIP_CALL( propagateRedcostVar(scip, var, cols[c], lpobjval, cutoffbound, &nchgbds) );
      }
   }

   if( cutoff )
   {
      *result = SCIP_CUTOFF;

      SCIPdebugMessage("node %"SCIP_LONGINT_FORMAT": detected cutoff\n",
         SCIPnodeGetNumber(SCIPgetCurrentNode(scip)));
   }
   else if( nchgbds > 0 )
   {
      *result = SCIP_REDUCEDDOM;

      SCIPdebugMessage("node %"SCIP_LONGINT_FORMAT": %d bound changes (max redcost <%g>)\n",
         SCIPnodeGetNumber(SCIPgetCurrentNode(scip)) , nchgbds, propdata->maxredcost);
   }

   return SCIP_OKAY;
}
Exemplo n.º 21
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;
}
Exemplo n.º 22
0
/** method for either Farkas or Redcost pricing */
static
SCIP_RETCODE pricing(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_PRICER*          pricer,             /**< pricer */
   SCIP_Real*            lowerbound,         /**< lowerbound pointer */
   SCIP_Bool             farkas              /**< TRUE: Farkas pricing; FALSE: Redcost pricing */
   )
{
   SCIP_PRICERDATA* pricerdata; /* the data of the pricer */
   SCIP_PROBDATA* probdata;
   GRAPH* graph;
   SCIP_VAR* var;
   PATH* path;
   SCIP_Real* edgecosts;  /* edgecosts of the current subproblem */
   char varname[SCIP_MAXSTRLEN];
   SCIP_Real newlowerbound = -SCIPinfinity(scip);
   SCIP_Real redcost;   /* reduced cost */
   int tail;
   int e;
   int t;
   int i;

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

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

   /* get problem data */
   probdata = SCIPgetProbData(scip);
   assert(probdata != NULL);

   SCIPdebugMessage("solstat=%d\n", SCIPgetLPSolstat(scip));

   if( !farkas && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
      newlowerbound = SCIPgetSolTransObj(scip, NULL);

   SCIPdebug( SCIP_CALL( SCIPprintSol(scip, NULL, NULL, FALSE) ) );

# if 0
   if ( pricerdata->lowerbound <= 4 )
   {
      char label[SCIP_MAXSTRLEN];
      (void)SCIPsnprintf(label, SCIP_MAXSTRLEN, "X%g.gml", pricerdata->lowerbound);
      SCIP_CALL( SCIPprobdataPrintGraph(scip, label , NULL, TRUE) );
      pricerdata->lowerbound++;
   }
#endif
   /* get the graph*/
   graph = SCIPprobdataGetGraph(probdata);

   /* get dual solutions and save them in mi and pi */
   for( t = 0; t < pricerdata->realnterms; ++t )
   {
      if( farkas )
      {
	 pricerdata->mi[t] = SCIPgetDualfarkasLinear(scip, pricerdata->pathcons[t]);
      }
      else
      {
         pricerdata->mi[t] = SCIPgetDualsolLinear(scip, pricerdata->pathcons[t]);
         assert(!SCIPisNegative(scip, pricerdata->mi[t]));
      }
   }

   for( e = 0; e < pricerdata->nedges; ++e )
   {
      if( !pricerdata->bigt )
      {
         for( t = 0; t < pricerdata->realnterms; ++t )
         {
            if( farkas )
	    {
               pricerdata->pi[t * pricerdata->nedges + e] = SCIPgetDualfarkasLinear(
                  scip, pricerdata->edgecons[t * pricerdata->nedges + e]);
	    }
            else
	    {
               pricerdata->pi[t * pricerdata->nedges + e] = SCIPgetDualsolLinear(
                  scip, pricerdata->edgecons[t * pricerdata->nedges + e]);
	    }
         }
      }
      else
      {
         if( farkas )
	 {
	    pricerdata->pi[e] = SCIPgetDualfarkasLinear(
               scip, pricerdata->edgecons[e]);
	 }
	 else
	 {
	    pricerdata->pi[e] = SCIPgetDualsolLinear(
               scip, pricerdata->edgecons[e]);
	 }
      }
   }

   SCIP_CALL( SCIPallocMemoryArray(scip, &path, graph->knots) );
   SCIP_CALL( SCIPallocMemoryArray(scip, &edgecosts, pricerdata->nedges) );

   if( pricerdata->bigt )
   {
      for( e = 0; e < pricerdata->nedges; ++e )
      {
         edgecosts[e] = (-pricerdata->pi[e]);
      }
   }
   /* find shortest r-t (r root, t terminal) paths and create corresponding variables iff reduced cost < 0 */
   for( t = 0; t < pricerdata->realnterms; ++t )
   {
      for( e = 0; e < pricerdata->nedges; ++e )
      {
	 if( !pricerdata->bigt )
	 {
            edgecosts[e] = (-pricerdata->pi[t * pricerdata->nedges + e]);
	 }

         assert(!SCIPisNegative(scip, edgecosts[e]));
      }

      for( i = 0; i < graph->knots; i++ )
         graph->mark[i] = 1;

      graph_path_exec(scip, graph, FSP_MODE, pricerdata->root, edgecosts, path);

      /* compute reduced cost of shortest path to terminal t */
      redcost = 0.0;
      tail = pricerdata->realterms[t];
      while( tail != pricerdata->root )
      {
         redcost += edgecosts[path[tail].edge];
	 tail = graph->tail[path[tail].edge];
      }
      redcost -= pricerdata->mi[t];

      if( !farkas && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
      {
         newlowerbound += redcost;
      }
      /* check if reduced cost < 0 */
      if( SCIPisNegative(scip, redcost) )
      {
	 /* create variable to the shortest path (having reduced cost < 0) */
         var = NULL;
	 sprintf(varname, "PathVar%d_%d", t, pricerdata->ncreatedvars[t]);
         ++(pricerdata->ncreatedvars[t]);

         SCIP_CALL( SCIPcreateVarBasic(scip, &var, varname, 0.0, SCIPinfinity(scip), 0.0, SCIP_VARTYPE_CONTINUOUS) );
         SCIP_CALL( SCIPaddPricedVar(scip, var, -redcost) );
         tail = pricerdata->realterms[t];
         while( tail != pricerdata->root )
         {
            /* add variable to constraints */
	    if( !pricerdata->bigt )
	    {
	       SCIP_CALL( SCIPaddCoefLinear(scip, pricerdata->edgecons[t * pricerdata->nedges + path[tail].edge], var, 1.0) );
	    }
	    else
	    {
	       SCIP_CALL( SCIPaddCoefLinear(scip, pricerdata->edgecons[path[tail].edge], var, 1.0) );
	    }

	    tail = graph->tail[path[tail].edge];
         }
         SCIP_CALL( SCIPaddCoefLinear(scip, pricerdata->pathcons[t], var, 1.0) );
      }
   }

   if( !farkas && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
      *lowerbound = newlowerbound;

   SCIPfreeMemoryArray(scip, &edgecosts);
   SCIPfreeMemoryArray(scip, &path);

   return SCIP_OKAY;
}
Exemplo n.º 23
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;
}
Exemplo n.º 24
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;
}
Exemplo n.º 25
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;
}