Exemplo n.º 1
0
/** checks if a given branching candidate is better than a previous one and updates the best branching candidate accordingly */
static
SCIP_RETCODE updateBestCandidate(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_BRANCHRULEDATA*  branchruledata,     /**< branching rule data */
   SCIP_VAR**            bestvar,            /**< best branching candidate */
   SCIP_Real*            bestbrpoint,        /**< branching point for best branching candidate */
   SCIP_Real*            bestscore,          /**< score of best branching candidate */
   SCIP_VAR*             cand,               /**< branching candidate to consider */
   SCIP_Real             candscoremin,       /**< minimal score of branching candidate */
   SCIP_Real             candscoremax,       /**< maximal score of branching candidate */
   SCIP_Real             candscoresum,       /**< sum of scores of branching candidate */
   SCIP_Real             candsol             /**< proposed branching point of branching candidate */          
)
{
   SCIP_Real candbrpoint;
   SCIP_Real branchscore;

   SCIP_Real deltaminus;
   SCIP_Real deltaplus;

   SCIP_Real pscostdown;
   SCIP_Real pscostup;
   
   char strategy;

   assert(scip != NULL);
   assert(branchruledata != NULL);
   assert(bestvar != NULL);
   assert(bestbrpoint != NULL);
   assert(bestscore != NULL);
   assert(cand != NULL);

   /* a branching variable candidate should either be an active problem variable or a multi-aggregated variable */
   assert(SCIPvarIsActive(SCIPvarGetProbvar(cand)) ||
      SCIPvarGetStatus(SCIPvarGetProbvar(cand)) == SCIP_VARSTATUS_MULTAGGR);
   
   if( SCIPvarGetStatus(SCIPvarGetProbvar(cand)) == SCIP_VARSTATUS_MULTAGGR )
   {
      /* for a multi-aggregated variable, we call updateBestCandidate function recursively with all variables in the multi-aggregation */
      SCIP_VAR** multvars;
      int nmultvars;
      int i;
      SCIP_Bool success;
      SCIP_Real multvarlb;
      SCIP_Real multvarub;

      cand = SCIPvarGetProbvar(cand);
      multvars = SCIPvarGetMultaggrVars(cand);
      nmultvars = SCIPvarGetMultaggrNVars(cand);

      /* if we have a candidate branching point, then first register only aggregation variables
       * for which we can compute a corresponding branching point too (see also comments below)
       * if this fails, then register all (unfixed) aggregation variables, thereby forgetting about candsol
       */
      success = FALSE;
      if( candsol != SCIP_INVALID ) /*lint !e777*/
      {
         SCIP_Real* multscalars;
         SCIP_Real minact;
         SCIP_Real maxact;
         SCIP_Real aggrvarsol;
         SCIP_Real aggrvarsol1;
         SCIP_Real aggrvarsol2;

         multscalars = SCIPvarGetMultaggrScalars(cand);

         /* for computing the branching point, we need the current bounds of the multi-aggregated variable */
         minact = SCIPcomputeVarLbLocal(scip, cand);
         maxact = SCIPcomputeVarUbLocal(scip, cand);

         for( i = 0; i < nmultvars; ++i )
         {
            /* skip fixed variables */
            multvarlb = SCIPcomputeVarLbLocal(scip, multvars[i]);
            multvarub = SCIPcomputeVarUbLocal(scip, multvars[i]);
            if( SCIPisEQ(scip, multvarlb, multvarub) )
               continue;

            assert(multscalars != NULL);
            assert(multscalars[i] != 0.0);

            /* we cannot ensure that both the upper bound in the left node and the lower bound in the right node
             * will be candsol by a clever choice for the branching point of multvars[i],
             * but we can try to ensure that at least one of them will be at candsol
             */
            if( multscalars[i] > 0.0 )
            {
               /*    cand >= candsol
                * if multvars[i] >= (candsol - (maxact - multscalars[i] * ub(multvars[i]))) / multscalars[i]
                *                 = (candsol - maxact) / multscalars[i] + ub(multvars[i])
                */
               aggrvarsol1 = (candsol - maxact) / multscalars[i] + multvarub;

               /*     cand <= candsol
                * if multvars[i] <= (candsol - (minact - multscalar[i] * lb(multvars[i]))) / multscalars[i]
                *                 = (candsol - minact) / multscalars[i] + lb(multvars[i])
                */
               aggrvarsol2 = (candsol - minact) / multscalars[i] + multvarlb;
            }
            else
            {
               /*    cand >= candsol
                * if multvars[i] <= (candsol - (maxact - multscalars[i] * lb(multvars[i]))) / multscalars[i]
                *                 = (candsol - maxact) / multscalars[i] + lb(multvars[i])
                */
               aggrvarsol2 = (candsol - maxact) / multscalars[i] + multvarlb;

               /*    cand <= candsol
                * if multvars[i] >= (candsol - (minact - multscalar[i] * ub(multvars[i]))) / multscalars[i]
                *                 = (candsol - minact) / multscalars[i] + ub(multvars[i])
                */
               aggrvarsol1 = (candsol - minact) / multscalars[i] + multvarub;
            }

            /* by the above choice, aggrvarsol1 <= ub(multvars[i]) and aggrvarsol2 >= lb(multvars[i])
             * if aggrvarsol1 <= lb(multvars[i]) or aggrvarsol2 >= ub(multvars[i]), then choose the other one
             * if both are out of bounds, then give up
             * if both are inside bounds, then choose the one closer to 0.0 (someone has better idea???)
             */
            if( SCIPisFeasLE(scip, aggrvarsol1, multvarlb) )
            {
               if( SCIPisFeasGE(scip, aggrvarsol2, multvarub) )
                  continue;
               else
                  aggrvarsol = aggrvarsol2;
            }
            else
            {
               if( SCIPisFeasGE(scip, aggrvarsol2, multvarub) )
                  aggrvarsol = aggrvarsol1;
               else
                  aggrvarsol = REALABS(aggrvarsol1) < REALABS(aggrvarsol2) ? aggrvarsol1 : aggrvarsol2;
            }
            success = TRUE;

            SCIP_CALL( updateBestCandidate(scip, branchruledata, bestvar, bestbrpoint, bestscore,
                  multvars[i], candscoremin, candscoremax, candscoresum, aggrvarsol) );
         }
      }

      if( !success )
         for( i = 0; i < nmultvars; ++i )
         {
            /* skip fixed variables */
            multvarlb = SCIPcomputeVarLbLocal(scip, multvars[i]);
            multvarub = SCIPcomputeVarUbLocal(scip, multvars[i]);
            if( SCIPisEQ(scip, multvarlb, multvarub) )
               continue;

            SCIP_CALL( updateBestCandidate(scip, branchruledata, bestvar, bestbrpoint, bestscore,
               multvars[i], candscoremin, candscoremax, candscoresum, SCIP_INVALID) );
         }

      assert(*bestvar != NULL); /* if all variables were fixed, something is strange */
      
      return SCIP_OKAY;
   }
   
   /* select branching point for this variable */
   candbrpoint = SCIPgetBranchingPoint(scip, cand, candsol);
   assert(candbrpoint >= SCIPvarGetLbLocal(cand));
   assert(candbrpoint <= SCIPvarGetUbLocal(cand));

   /* we cannot branch on a huge value for a discrete variable, because we simply cannot enumerate such huge integer values in floating point
    * arithmetics
    */
   if( SCIPvarGetType(cand) != SCIP_VARTYPE_CONTINUOUS && (SCIPisHugeValue(scip, candbrpoint) || SCIPisHugeValue(scip, -candbrpoint)) )
      return SCIP_OKAY;

   assert(SCIPvarGetType(cand) == SCIP_VARTYPE_CONTINUOUS || !SCIPisIntegral(scip, candbrpoint));

   if( SCIPvarGetType(cand) == SCIP_VARTYPE_CONTINUOUS )
      strategy = (branchruledata->strategy == 'u' ? branchruledata->updatestrategy : branchruledata->strategy);
   else
      strategy = (branchruledata->strategy == 'u' ? 'l' : branchruledata->strategy);

   switch( strategy )
   {
   case 'l':
      if( SCIPisInfinity(scip,  SCIPgetSolVal(scip, NULL, cand)) || SCIPgetSolVal(scip, NULL, cand) <= SCIPadjustedVarUb(scip, cand, candbrpoint) )
         deltaminus = 0.0;
      else
         deltaminus = SCIPgetSolVal(scip, NULL, cand) - SCIPadjustedVarUb(scip, cand, candbrpoint);
      if( SCIPisInfinity(scip, -SCIPgetSolVal(scip, NULL, cand)) || SCIPgetSolVal(scip, NULL, cand) >= SCIPadjustedVarLb(scip, cand, candbrpoint) )
         deltaplus = 0.0;
      else
         deltaplus = SCIPadjustedVarLb(scip, cand, candbrpoint) - SCIPgetSolVal(scip, NULL, cand);
      break;

   case 'd':
      if( SCIPisInfinity(scip, -SCIPvarGetLbLocal(cand)) )
         deltaminus = SCIPisInfinity(scip, candscoremax) ? SCIPinfinity(scip) : WEIGHTEDSCORING(branchruledata, candscoremin, candscoremax, candscoresum);
      else
         deltaminus = SCIPadjustedVarUb(scip, cand, candbrpoint) - SCIPvarGetLbLocal(cand);

      if( SCIPisInfinity(scip,  SCIPvarGetUbLocal(cand)) )
         deltaplus = SCIPisInfinity(scip, candscoremax) ? SCIPinfinity(scip) : WEIGHTEDSCORING(branchruledata, candscoremin, candscoremax, candscoresum);
      else
         deltaplus = SCIPvarGetUbLocal(cand) - SCIPadjustedVarLb(scip, cand, candbrpoint);
      break;
      
   case 's':
      if( SCIPisInfinity(scip, -SCIPvarGetLbLocal(cand)) )
         deltaplus = SCIPisInfinity(scip, candscoremax) ? SCIPinfinity(scip) : WEIGHTEDSCORING(branchruledata, candscoremin, candscoremax, candscoresum);
      else
         deltaplus = SCIPadjustedVarUb(scip, cand, candbrpoint) - SCIPvarGetLbLocal(cand);

      if( SCIPisInfinity(scip,  SCIPvarGetUbLocal(cand)) )
         deltaminus = SCIPisInfinity(scip, candscoremax) ? SCIPinfinity(scip) : WEIGHTEDSCORING(branchruledata, candscoremin, candscoremax, candscoresum);
      else
         deltaminus = SCIPvarGetUbLocal(cand) - SCIPadjustedVarLb(scip, cand, candbrpoint);
      break;

   case 'v':
      deltaplus = SCIPisInfinity(scip, candscoremax) ? SCIPinfinity(scip) : WEIGHTEDSCORING(branchruledata, candscoremin, candscoremax, candscoresum);
      deltaminus = deltaplus;
      break;

   default :
      SCIPerrorMessage("branching strategy %c unknown\n", strategy);
      SCIPABORT();
      return SCIP_INVALIDDATA;  /*lint !e527*/
   }

   if( SCIPisInfinity(scip, deltaminus) || SCIPisInfinity(scip, deltaplus) )
   {
      branchscore = SCIPinfinity(scip);
   }
   else
   {
      pscostdown  = SCIPgetVarPseudocostVal(scip, cand, -deltaminus);
      pscostup    = SCIPgetVarPseudocostVal(scip, cand,  deltaplus);
      branchscore = SCIPgetBranchScore(scip, cand, pscostdown, pscostup);
      assert(!SCIPisNegative(scip, branchscore));
   }
   SCIPdebugMessage("branching score variable <%s>[%g,%g] = %g; wscore = %g; type=%d bestbrscore=%g\n",
      SCIPvarGetName(cand), SCIPvarGetLbLocal(cand), SCIPvarGetUbLocal(cand), branchscore, WEIGHTEDSCORING(branchruledata, candscoremin, candscoremax, candscoresum),
      SCIPvarGetType(cand), *bestscore);

   if( SCIPisInfinity(scip, branchscore) )
      branchscore = 0.9*SCIPinfinity(scip);
   
   if( SCIPisSumGT(scip, branchscore, *bestscore) )
   {
      (*bestscore)   = branchscore;
      (*bestvar)     = cand;
      (*bestbrpoint) = candbrpoint;
   }
   else if( SCIPisSumEQ(scip, branchscore, *bestscore)
      && !(SCIPisInfinity(scip, -SCIPvarGetLbLocal(*bestvar)) && SCIPisInfinity(scip, SCIPvarGetUbLocal(*bestvar))) )
   {
      /* if best candidate so far is not unbounded to both sides, maybe take new candidate */
      if( (SCIPisInfinity(scip, -SCIPvarGetLbLocal(cand))     || SCIPisInfinity(scip, SCIPvarGetUbLocal(cand))) &&
          (SCIPisInfinity(scip, -SCIPvarGetLbLocal(*bestvar)) || SCIPisInfinity(scip, SCIPvarGetUbLocal(*bestvar))) )
      { 
         /* if both variables are unbounded but one of them is bounded on one side, take the one with the larger bound on this side (hope that this avoids branching on always the same variable) */
         if( SCIPvarGetUbLocal(cand) > SCIPvarGetUbLocal(*bestvar) || SCIPvarGetLbLocal(cand) < SCIPvarGetLbLocal(*bestvar) )
         {
            (*bestscore)   = branchscore;
            (*bestvar)     = cand;
            (*bestbrpoint) = candbrpoint;
         }
      }
      else if( SCIPvarGetType(*bestvar) == SCIPvarGetType(cand) )
      { 
         /* if both have the same type, take the one with larger diameter */
         if( SCIPvarGetUbLocal(*bestvar) - SCIPvarGetLbLocal(*bestvar) < SCIPvarGetUbLocal(cand) - SCIPvarGetLbLocal(cand) )
         {
            (*bestscore)   = branchscore;
            (*bestvar)     = cand;
            (*bestbrpoint) = candbrpoint;
         }
      }
      else if( SCIPvarGetType(*bestvar) > SCIPvarGetType(cand) )
      { 
         /* take the one with better type ("more discrete") */
         (*bestscore)   = branchscore;
         (*bestvar)     = cand;
         (*bestbrpoint) = candbrpoint;
      }
   }

   return SCIP_OKAY;
}
Exemplo n.º 2
0
/** compares the so far best branching candidate with a new candidate and updates best candidate, if new candidate is better */
static
void updateBestCandidate(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_VAR**            bestvar,            /**< best branching candidate */
   SCIP_Real*            bestscore,          /**< score of best branching candidate */
   SCIP_Real*            bestobj,            /**< absolute objective value of best branching candidate */
   SCIP_Real*            bestsol,            /**< proposed branching point of best branching candidate */
   SCIP_VAR*             cand,               /**< branching candidate to consider */
   SCIP_Real             candscore,          /**< scoring of branching candidate */
   SCIP_Real             candsol             /**< proposed branching point of branching candidate */
   )
{
   SCIP_Real obj;

   assert(scip != NULL);
   assert(bestvar != NULL);
   assert(bestscore != NULL);
   assert(bestobj != NULL);
   assert(*bestobj >= 0.0);
   assert(cand != NULL);

   /* a branching variable candidate should either be an active problem variable or a multi-aggregated variable */
   assert(SCIPvarIsActive(SCIPvarGetProbvar(cand)) ||
      SCIPvarGetStatus(SCIPvarGetProbvar(cand)) == SCIP_VARSTATUS_MULTAGGR);

   if( SCIPvarGetStatus(SCIPvarGetProbvar(cand)) == SCIP_VARSTATUS_MULTAGGR )
   {
      /* for a multi-aggregated variable, we call updateBestCandidate function recursively with all variables in the multi-aggregation */
      SCIP_VAR** multvars;
      int nmultvars;
      int i;
      SCIP_Bool success;
      SCIP_Real multvarlb;
      SCIP_Real multvarub;

      cand = SCIPvarGetProbvar(cand);
      multvars = SCIPvarGetMultaggrVars(cand);
      nmultvars = SCIPvarGetMultaggrNVars(cand);

      /* if we have a candidate branching point, then first register only aggregation variables
       * for which we can compute a corresponding branching point too (see also comments below)
       * if this fails, then register all (unfixed) aggregation variables, thereby forgetting about candsol
       */
      success = FALSE;
      if( candsol != SCIP_INVALID ) /*lint !e777*/
      {
         SCIP_Real* multscalars;
         SCIP_Real minact;
         SCIP_Real maxact;
         SCIP_Real aggrvarsol;
         SCIP_Real aggrvarsol1;
         SCIP_Real aggrvarsol2;

         multscalars = SCIPvarGetMultaggrScalars(cand);

         /* for computing the branching point, we need the current bounds of the multi-aggregated variable */
         minact = SCIPcomputeVarLbLocal(scip, cand);
         maxact = SCIPcomputeVarUbLocal(scip, cand);

         for( i = 0; i < nmultvars; ++i )
         {
            /* skip fixed variables */
            multvarlb = SCIPcomputeVarLbLocal(scip, multvars[i]);
            multvarub = SCIPcomputeVarUbLocal(scip, multvars[i]);
            if( SCIPisEQ(scip, multvarlb, multvarub) )
               continue;

            assert(multscalars != NULL);
            assert(multscalars[i] != 0.0);

            /* we cannot ensure that both the upper bound in the left node and the lower bound in the right node
             * will be candsol by a clever choice for the branching point of multvars[i],
             * but we can try to ensure that at least one of them will be at candsol
             */
            if( multscalars[i] > 0.0 )
            {
               /*    cand >= candsol
                * if multvars[i] >= (candsol - (maxact - multscalars[i] * ub(multvars[i]))) / multscalars[i]
                *                 = (candsol - maxact) / multscalars[i] + ub(multvars[i])
                */
               aggrvarsol1 = (candsol - maxact) / multscalars[i] + multvarub;

               /*     cand <= candsol
                * if multvars[i] <= (candsol - (minact - multscalar[i] * lb(multvars[i]))) / multscalars[i]
                *                 = (candsol - minact) / multscalars[i] + lb(multvars[i])
                */
               aggrvarsol2 = (candsol - minact) / multscalars[i] + multvarlb;
            }
            else
            {
               /*    cand >= candsol
                * if multvars[i] <= (candsol - (maxact - multscalars[i] * lb(multvars[i]))) / multscalars[i]
                *                 = (candsol - maxact) / multscalars[i] + lb(multvars[i])
                */
               aggrvarsol2 = (candsol - maxact) / multscalars[i] + multvarlb;

               /*    cand <= candsol
                * if multvars[i] >= (candsol - (minact - multscalar[i] * ub(multvars[i]))) / multscalars[i]
                *                 = (candsol - minact) / multscalars[i] + ub(multvars[i])
                */
               aggrvarsol1 = (candsol - minact) / multscalars[i] + multvarub;
            }

            /* by the above choice, aggrvarsol1 <= ub(multvars[i]) and aggrvarsol2 >= lb(multvars[i])
             * if aggrvarsol1 <= lb(multvars[i]) or aggrvarsol2 >= ub(multvars[i]), then choose the other one
             * if both are out of bounds, then give up
             * if both are inside bounds, then choose the one closer to 0.0 (someone has better idea???)
             */
            if( SCIPisFeasLE(scip, aggrvarsol1, multvarlb) )
            {
               if( SCIPisFeasGE(scip, aggrvarsol2, multvarub) )
                  continue;
               else
                  aggrvarsol = aggrvarsol2;
            }
            else
            {
               if( SCIPisFeasGE(scip, aggrvarsol2, multvarub) )
                  aggrvarsol = aggrvarsol1;
               else
                  aggrvarsol = REALABS(aggrvarsol1) < REALABS(aggrvarsol2) ? aggrvarsol1 : aggrvarsol2;
            }
            success = TRUE;

            updateBestCandidate(scip, bestvar, bestscore, bestobj, bestsol,
                  multvars[i], candscore, aggrvarsol);
         }
      }

      if( !success )
         for( i = 0; i < nmultvars; ++i )
         {
            /* skip fixed variables */
            multvarlb = SCIPcomputeVarLbLocal(scip, multvars[i]);
            multvarub = SCIPcomputeVarUbLocal(scip, multvars[i]);
            if( SCIPisEQ(scip, multvarlb, multvarub) )
               continue;

            updateBestCandidate(scip, bestvar, bestscore, bestobj, bestsol,
               multvars[i], candscore, SCIP_INVALID);
         }

      assert(*bestvar != NULL); /* if all variables were fixed, something is strange */

      return;
   }

   candscore *= SCIPvarGetBranchFactor(cand);
   obj = SCIPvarGetObj(cand);
   obj = REALABS(obj);
   if( SCIPisInfinity(scip, *bestscore)
      || (!SCIPisInfinity(scip, candscore) && 
          (SCIPisLT(scip, candscore, *bestscore) || (SCIPisLE(scip, candscore, *bestscore) && obj > *bestobj))) )
   {
      *bestvar = cand;
      *bestscore = candscore;
      *bestobj = obj;
      *bestsol = candsol;
   }
}
Exemplo n.º 3
0
/** selects the branching variable from given candidate array */
static
SCIP_RETCODE selectBranchVar(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_BRANCHRULE*      branchrule,         /**< branching rule */
   SCIP_VAR**            cands,              /**< array of branching candidates */
   SCIP_Real*            candssol,           /**< array of candidate solution values */
   SCIP_Real*            candsscore,         /**< array of candidate scores */
   int                   ncands,             /**< the number of candidates */
   SCIP_VAR**            brvar,              /**< pointer to store the selected branching candidate or NULL if none */
   SCIP_Real*            brpoint             /**< pointer to store branching point of selected branching variable */
   )
{ /*lint --e{850}*/ 
   SCIP_BRANCHRULEDATA* branchruledata;

   SCIP_VAR* cand;
   SCIP_Real candsol;

   SCIP_Real bestbranchscore;

   SCIP_Real scoremin;
   SCIP_Real scoresum;
   SCIP_Real scoremax;

   SCIP_VAR** candssorted;
   int* candsorigidx;
   
   int i;
   int j;
   
   assert(brvar   != NULL);
   assert(brpoint != NULL);
   
   (*brvar)   = NULL;
   (*brpoint) = SCIP_INVALID;

   if( ncands == 0 )
      return SCIP_OKAY;

   branchruledata = SCIPbranchruleGetData(branchrule);
   assert(branchruledata != NULL);
   
   /* sort branching candidates (in a copy), such that same variables are on consecutive positions */
   SCIP_CALL( SCIPduplicateBufferArray(scip, &candssorted, cands, ncands) );
   SCIP_CALL( SCIPallocBufferArray(scip, &candsorigidx, ncands) );
   for( i = 0; i < ncands; ++i )
      candsorigidx[i] = i;
   
   SCIPsortPtrInt((void**)candssorted, candsorigidx, SCIPvarComp, ncands);

   bestbranchscore = -1.0;

   for( i = 0; i < ncands; ++i )
   {
      cand = candssorted[i];

      /* there should be no fixed branching candidates */
      assert(!SCIPisEQ(scip, SCIPvarGetLbLocal(cand), SCIPvarGetUbLocal(cand)));

      /* compute min, sum, and max of all registered scores for this variables
       * set candsol to a valid value, if someone registered one */
      scoremin = candsscore[candsorigidx[i]];
      scoresum = scoremin;
      scoremax = scoremin;
      candsol  = candssol[candsorigidx[i]];
      for( j = i+1 ; j < ncands && SCIPvarCompare(candssorted[j], cand) == 0; ++j )
      {
         assert(candsscore[candsorigidx[j]] >= 0.0);
         scoresum += candsscore[candsorigidx[j]];
         if( candsscore[candsorigidx[j]] < scoremin )
            scoremin = candsscore[candsorigidx[j]];
         else if( candsscore[candsorigidx[j]] > scoremax )
            scoremax = candsscore[candsorigidx[j]];

         /* @todo if there are two valid externcandssol available for the same variable, should we take the one closer to the middle of the domain? */
         if( SCIPisInfinity(scip, REALABS(candsol)) )
            candsol = candssol[candsorigidx[j]];
      }
      /* set i to last occurrence of cand in candssorted (instead of first one as before), so in next round we look at another variable */
      i = j-1;
      assert(candssorted[i] == cand);

      /* check if new candidate is better than previous candidate (if any) */
      SCIP_CALL( updateBestCandidate(scip, branchruledata, brvar, brpoint, &bestbranchscore, cand, scoremin, scoremax, scoresum, candsol) );
   }

   /* there were candidates, but no variable was selected; this can only happen if the branching points are huge values
    * for all variables on which we cannot branch
    * @todo delay the node?
    */
   if( (*brvar) == NULL )
   {
      SCIPerrorMessage("no branching could be created: all external candidates have huge bounds\n");
      SCIPABORT();
      return SCIP_BRANCHERROR; /*lint !e527*/
   }

   /* free buffer arrays */
   SCIPfreeBufferArray(scip, &candssorted);
   SCIPfreeBufferArray(scip, &candsorigidx);

   return SCIP_OKAY;
}
Exemplo n.º 4
0
/** branching execution method for external candidates */
static
SCIP_DECL_BRANCHEXECEXT(branchExecextLeastinf)
{  /*lint --e{715}*/
   SCIP_VAR** externcands;
   SCIP_Real* externcandssol;
   SCIP_Real* externcandsscore;
   int nexterncands;
   SCIP_VAR* bestcand;
   SCIP_Real bestscore;
   SCIP_Real bestobj;
   SCIP_Real bestsol;
   SCIP_Real brpoint;
   int i;
   SCIP_NODE* downchild;
   SCIP_NODE* eqchild;
   SCIP_NODE* upchild;

   assert(branchrule != NULL);
   assert(strcmp(SCIPbranchruleGetName(branchrule), BRANCHRULE_NAME) == 0);
   assert(scip != NULL);
   assert(result != NULL);

   SCIPdebugMessage("Execext method of leastinf branching\n");

   /* get branching candidates */
   SCIP_CALL( SCIPgetExternBranchCands(scip, &externcands, &externcandssol, &externcandsscore, NULL, &nexterncands, NULL, NULL, NULL) );
   assert(nexterncands > 0);

   /* search the least infeasible candidate */
   bestscore = SCIPinfinity(scip);
   bestobj  = 0.0;
   bestcand = NULL;
   bestsol = SCIP_INVALID;
   for( i = 0; i < nexterncands; ++i )
   {
      updateBestCandidate(scip, &bestcand, &bestscore, &bestobj, &bestsol, externcands[i], externcandsscore[i], externcandssol[i]);
   }

   if( bestcand == NULL )
   {
      SCIPerrorMessage("branchExecextLeastinf failed to select a branching variable from %d candidates\n", nexterncands);
      *result = SCIP_DIDNOTRUN;
      return SCIP_OKAY;
   }

   brpoint = SCIPgetBranchingPoint(scip, bestcand, bestsol);

   SCIPdebugMessage(" -> %d candidates, selected variable <%s> (infeas=%g, obj=%g, factor=%g, score=%g), branching point=%g\n",
      nexterncands, SCIPvarGetName(bestcand), bestsol, bestobj,
      SCIPvarGetBranchFactor(bestcand), bestscore, brpoint);

   /* perform the branching */
   SCIP_CALL( SCIPbranchVarVal(scip, bestcand, brpoint, &downchild, &eqchild, &upchild) );

   if( downchild != NULL || eqchild != NULL || upchild != NULL )
   {
      *result = SCIP_BRANCHED;
   }
   else
   {
      /* if there are no children, then variable should have been fixed by SCIPbranchVarVal */
      assert(SCIPisEQ(scip, SCIPvarGetLbLocal(bestcand), SCIPvarGetUbLocal(bestcand)));
      *result = SCIP_REDUCEDDOM;
   }

   return SCIP_OKAY;
}