/** solving process initialization method of variable pricer (called when branch and bound process is about to begin) */
static
SCIP_DECL_PRICERINITSOL(pricerInitsolStp)
{
SCIP_PRICERDATA* pricerdata;
SCIPdebugPrintf("pricerinitsol \n");
assert(scip != NULL);
assert(pricer != NULL);
pricerdata = SCIPpricerGetData(pricer);
assert(pricerdata != NULL);
/* allocate memory */
if( !pricerdata->bigt )
{
SCIP_CALL( SCIPallocMemoryArray(scip, &(pricerdata->pi), SCIPprobdataGetNEdges(scip) * SCIPprobdataGetRNTerms(scip)) );
}
else
{
SCIP_CALL( SCIPallocMemoryArray(scip, &(pricerdata->pi), SCIPprobdataGetNEdges(scip)) );
}
SCIP_CALL( SCIPallocMemoryArray(scip, &(pricerdata->mi), SCIPprobdataGetRNTerms(scip)) );
SCIP_CALL( SCIPallocMemoryArray(scip, &pricerdata->ncreatedvars, SCIPprobdataGetRNTerms(scip)) );
BMSclearMemoryArray(pricerdata->ncreatedvars, SCIPprobdataGetRNTerms(scip));
return SCIP_OKAY;
}
/** reads the next line from the input file into the line buffer; skips comments;
* returns whether a line could be read
*/
static
SCIP_Bool getNextLine(
BLKINPUT* blkinput /**< BLK reading data */
)
{
int i;
assert(blkinput != NULL);
/* clear the line */
BMSclearMemoryArray(blkinput->linebuf, BLK_MAX_LINELEN);
/* read next line */
blkinput->linepos = 0;
blkinput->linebuf[BLK_MAX_LINELEN-2] = '\0';
if( SCIPfgets(blkinput->linebuf, sizeof(blkinput->linebuf), blkinput->file) == NULL )
return FALSE;
blkinput->linenumber++;
if( blkinput->linebuf[BLK_MAX_LINELEN-2] != '\0' )
{
SCIPerrorMessage("Error: line %d exceeds %d characters\n", blkinput->linenumber, BLK_MAX_LINELEN-2);
blkinput->haserror = TRUE;
return FALSE;
}
blkinput->linebuf[BLK_MAX_LINELEN-1] = '\0';
blkinput->linebuf[BLK_MAX_LINELEN-2] = '\0'; /* we want to use lookahead of one char -> we need two \0 at the end */
/* skip characters after comment symbol */
for( i = 0; commentchars[i] != '\0'; ++i )
{
char* commentstart;
commentstart = strchr(blkinput->linebuf, commentchars[i]);
if( commentstart != NULL )
{
*commentstart = '\0';
*(commentstart+1) = '\0'; /* we want to use lookahead of one char -> we need two \0 at the end */
}
}
return TRUE;
}
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE createSubproblem(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_Real minfixingrate, /**< percentage of integer variables that have to be fixed */
unsigned int* randseed, /**< a seed value for the random number generator */
SCIP_Bool uselprows /**< should subproblem be created out of the rows in the LP rows? */
)
{
SCIP_VAR** vars; /* original scip variables */
SCIP_SOL* sol; /* pool of solutions */
SCIP_Bool* marked; /* array of markers, which variables to fixed */
SCIP_Bool fixingmarker; /* which flag should label a fixed variable? */
int nvars;
int nbinvars;
int nintvars;
int i;
int j;
int nmarkers;
/* get required data of the original problem */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
sol = SCIPgetBestSol(scip);
assert(sol != NULL);
SCIP_CALL( SCIPallocBufferArray(scip, &marked, nbinvars+nintvars) );
if( minfixingrate > 0.5 )
{
nmarkers = nbinvars + nintvars - (int) SCIPfloor(scip, minfixingrate*(nbinvars+nintvars));
fixingmarker = FALSE;
}
else
{
nmarkers = (int) SCIPceil(scip, minfixingrate*(nbinvars+nintvars));
fixingmarker = TRUE;
}
assert( 0 <= nmarkers && nmarkers <= SCIPceil(scip,(nbinvars+nintvars)/2.0 ) );
j = 0;
BMSclearMemoryArray(marked, nbinvars+nintvars);
while( j < nmarkers )
{
do
{
i = SCIPgetRandomInt(0, nbinvars+nintvars-1, randseed);
}
while( marked[i] );
marked[i] = TRUE;
j++;
}
assert( j == nmarkers );
/* change bounds of variables of the subproblem */
for( i = 0; i < nbinvars + nintvars; i++ )
{
/* fix all randomly marked variables */
if( marked[i] == fixingmarker )
{
SCIP_Real solval;
SCIP_Real lb;
SCIP_Real ub;
solval = SCIPgetSolVal(scip, sol, vars[i]);
lb = SCIPvarGetLbGlobal(subvars[i]);
ub = SCIPvarGetUbGlobal(subvars[i]);
assert(SCIPisLE(scip, lb, ub));
/* due to dual reductions, it may happen that the solution value is not in
the variable's domain anymore */
if( SCIPisLT(scip, solval, lb) )
solval = lb;
else if( SCIPisGT(scip, solval, ub) )
solval = ub;
/* perform the bound change */
if( !SCIPisInfinity(scip, solval) && !SCIPisInfinity(scip, -solval) )
{
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], solval) );
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], solval) );
}
}
}
if( uselprows )
{
SCIP_ROW** rows; /* original scip rows */
int nrows;
/* get the rows and their number */
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* copy all rows to linear constraints */
for( i = 0; i < nrows; i++ )
{
SCIP_CONS* cons;
SCIP_VAR** consvars;
SCIP_COL** cols;
SCIP_Real constant;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real* vals;
int nnonz;
/* ignore rows that are only locally valid */
if( SCIProwIsLocal(rows[i]) )
continue;
/* get the row's data */
constant = SCIProwGetConstant(rows[i]);
lhs = SCIProwGetLhs(rows[i]) - constant;
rhs = SCIProwGetRhs(rows[i]) - constant;
vals = SCIProwGetVals(rows[i]);
nnonz = SCIProwGetNNonz(rows[i]);
cols = SCIProwGetCols(rows[i]);
assert( lhs <= rhs );
/* allocate memory array to be filled with the corresponding subproblem variables */
SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nnonz) );
for( j = 0; j < nnonz; j++ )
consvars[j] = subvars[SCIPvarGetProbindex(SCIPcolGetVar(cols[j]))];
/* create a new linear constraint and add it to the subproblem */
SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, SCIProwGetName(rows[i]), nnonz, consvars, vals, lhs, rhs,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* free temporary memory */
SCIPfreeBufferArray(scip, &consvars);
}
}
SCIPfreeBufferArray(scip, &marked);
return SCIP_OKAY;
}
/** branches the searching tree, branching nodes are selected in decreasing order of their apriori bound,
* returns the level to which we should backtrack, or INT_MAX for continuing normally
*/
static
int branch(
TCLIQUE_GETNNODES((*getnnodes)), /**< user function to get the number of nodes */
TCLIQUE_GETWEIGHTS((*getweights)), /**< user function to get the node weights */
TCLIQUE_ISEDGE ((*isedge)), /**< user function to check for existence of an edge */
TCLIQUE_SELECTADJNODES((*selectadjnodes)), /**< user function to select adjacent edges */
TCLIQUE_GRAPH* tcliquegraph, /**< pointer to graph data structure */
TCLIQUE_NEWSOL ((*newsol)), /**< user function to call on every new solution */
TCLIQUE_DATA* tcliquedata, /**< user data to pass to user callback function */
BMS_CHKMEM* mem, /**< block memory */
CLIQUEHASH* cliquehash, /**< clique hash table */
int* buffer, /**< buffer of size nnodes */
int level, /**< level of b&b tree */
int* V, /**< non-zero weighted nodes for branching */
int nV, /**< number of non-zero weighted nodes for branching */
int* Vzero, /**< zero weighted nodes */
int nVzero, /**< number of zero weighted nodes */
NBC* gsd, /**< neighbour color information of all nodes */
TCLIQUE_Bool* iscolored, /**< coloring status of all nodes */
int* K, /**< nodes from the b&b tree */
TCLIQUE_WEIGHT weightK, /**< weight of the nodes from b&b tree */
int* maxcliquenodes, /**< pointer to store nodes of the maximum weight clique */
int* nmaxcliquenodes, /**< pointer to store number of nodes in the maximum weight clique */
TCLIQUE_WEIGHT* maxcliqueweight, /**< pointer to store weight of the maximum weight clique */
int* curcliquenodes, /**< pointer to store nodes of currenct clique */
int* ncurcliquenodes, /**< pointer to store number of nodes in current clique */
TCLIQUE_WEIGHT* curcliqueweight, /**< pointer to store weight of current clique */
int* tmpcliquenodes, /**< buffer for storing the temporary clique */
TCLIQUE_WEIGHT maxfirstnodeweight, /**< maximum weight of branching nodes in level 0; 0 if not used
** (for cliques with at least one fractional node) */
int* ntreenodes, /**< pointer to store number of nodes of b&b tree */
int maxntreenodes, /**< maximal number of nodes of b&b tree */
int backtrackfreq, /**< frequency to backtrack to first level of tree (0: no premature backtracking) */
int maxnzeroextensions, /**< maximal number of zero-valued variables extending the clique */
int fixednode, /**< node that is forced to be in the clique, or -1; must have positive weight */
TCLIQUE_STATUS* status /**< pointer to store the status of the solving call */
)
{
TCLIQUE_Bool isleaf;
const TCLIQUE_WEIGHT* weights;
TCLIQUE_WEIGHT* apbound;
TCLIQUE_WEIGHT subgraphweight;
TCLIQUE_WEIGHT weightKold;
TCLIQUE_WEIGHT tmpcliqueweight;
int backtracklevel;
int ntmpcliquenodes;
int i;
assert(getnnodes != NULL);
assert(getweights != NULL);
assert(selectadjnodes != NULL);
assert(mem != NULL);
assert(V != NULL);
assert(gsd != NULL);
assert(iscolored != NULL);
assert(K != NULL);
assert(maxcliqueweight != NULL);
assert(curcliquenodes != NULL);
assert(ncurcliquenodes != NULL);
assert(curcliqueweight != NULL);
assert(ntreenodes != NULL);
assert(maxfirstnodeweight >= 0);
assert(*ntreenodes >= 0);
assert(maxntreenodes >= 0);
assert(status != NULL);
/* increase the number of nodes, and stop solving, if the node limit is exceeded */
(*ntreenodes)++;
#ifdef TCLIQUE_DEBUG
debugMessage("(level %d, treenode %d) maxclique = %d, curclique = %d [mem=%lld (%lld), cliques=%d]\n",
level, *ntreenodes, *maxcliqueweight, *curcliqueweight,
BMSgetChunkMemoryUsed(mem), BMSgetMemoryUsed(), cliquehash == NULL ? 0 : cliquehash->ncliques);
debugMessage(" -> current branching (weight %d):", weightK);
for( i = 0; i < level; ++i )
debugPrintf(" %d", K[i]);
debugPrintf("\n");
debugMessage(" -> branching candidates:");
for( i = 0; i < nV; ++i )
debugPrintf(" %d", V[i]);
debugPrintf("\n");
#endif
if( *ntreenodes > maxntreenodes )
{
*status = TCLIQUE_NODELIMIT;
return TRUE;
}
weights = getweights(tcliquegraph);
backtracklevel = INT_MAX;
isleaf = TRUE;
/* allocate temporary memory for a priori bounds */
ALLOC_ABORT( BMSallocMemoryArray(&apbound, nV) );
BMSclearMemoryArray(apbound, nV);
/* use coloring relaxation to generate an upper bound for the current subtree and a heuristic solution */
subgraphweight = boundSubgraph(getnnodes, getweights, isedge, selectadjnodes, tcliquegraph,
mem, buffer, V, nV, gsd, iscolored, apbound,
tmpcliquenodes, &ntmpcliquenodes, &tmpcliqueweight);
#ifndef NDEBUG
/* check correctness of V and apbound arrays */
for( i = 0; i < nV; ++i )
{
assert(0 <= V[i] && V[i] < getnnodes(tcliquegraph));
assert(i == 0 || V[i-1] < V[i]);
assert(apbound[i] >= 0);
assert((apbound[i] == 0) == (weights[V[i]] == 0));
}
#endif
/* check, whether the heuristic solution is better than the current subtree's solution;
* if the user wanted to have a fixed variable inside the clique and we are in level 0, we first have to
* fix this variable in this level (the current clique might not contain the fixed node)
*/
if( weightK + tmpcliqueweight > *curcliqueweight && (level > 0 || fixednode == -1) )
{
/* install the newly generated clique as current clique */
for( i = 0; i < level; ++i )
curcliquenodes[i] = K[i];
for( i = 0; i < ntmpcliquenodes; ++i )
curcliquenodes[level+i] = tmpcliquenodes[i];
*ncurcliquenodes = level + ntmpcliquenodes;
*curcliqueweight = weightK + tmpcliqueweight;
#ifdef TCLIQUE_DEBUG
debugMessage(" -> new current clique with weight %d at node %d in level %d:",
*curcliqueweight, *ntreenodes, level);
for( i = 0; i < *ncurcliquenodes; ++i )
debugPrintf(" %d", curcliquenodes[i]);
debugPrintf("\n");
#endif
}
/* discard subtree, if the upper bound is not better than the weight of the currently best clique;
* if only 2 nodes are left, the maximal weighted clique was already calculated in boundSubgraph() and nothing
* more has to be done;
* however, if the user wanted to have a fixed node and we are in the first decision level, we have to continue
*/
if( weightK + subgraphweight > *maxcliqueweight && (nV > 2 || (fixednode >= 0 && level == 0)) )
{
int* Vcurrent;
int nVcurrent;
int nValive;
int branchingnode;
assert(nV > 0);
/* process current subtree */
level++;
/* set up data structures */
ALLOC_ABORT( BMSallocMemoryArray(&Vcurrent, nV-1) );
nValive = nV;
weightKold = weightK;
debugMessage("============================ branching level %d ===============================\n", level);
/* branch on the nodes of V by decreasing order of their apriori bound */
while( backtracklevel >= level && nValive > 0 )
{
int branchidx;
/* check if we meet the backtracking frequency - in this case abort the search until we have reached first level */
if( level > 1 && backtrackfreq > 0 && (*ntreenodes) % backtrackfreq == 0 )
{
backtracklevel = 1;
break;
}
/* get next branching node */
if( level == 1 && fixednode >= 0 )
{
/* select the fixed node as first "branching" candidate */
for( branchidx = 0; branchidx < nValive && V[branchidx] != fixednode; branchidx++ )
{}
assert(branchidx < nValive);
assert(V[branchidx] == fixednode);
}
else if( level == 1 && maxfirstnodeweight > 0 )
branchidx = getMaxApBoundIndexNotMaxWeight(V, nValive, apbound, weights, maxfirstnodeweight);
else
branchidx = getMaxApBoundIndex(nValive, apbound);
if( branchidx < 0 )
break;
assert(0 <= branchidx && branchidx < nValive && nValive <= nV);
assert(apbound[branchidx] > 0);
assert(weights[V[branchidx]] > 0);
/* test a priori bound */
if( (weightKold + apbound[branchidx]) <= *maxcliqueweight )
break;
debugMessage("%d. branching in level %d (treenode %d): bidx=%d, node %d, weight %d, upperbound: %d+%d = %d, maxclique=%d\n",
nV-nValive+1, level, *ntreenodes, branchidx, V[branchidx], weights[V[branchidx]], weightKold,
apbound[branchidx], weightKold + apbound[branchidx], *maxcliqueweight);
/* because we branch on this node, the node is no leaf in the tree */
isleaf = FALSE;
/* update the set of nodes from the b&b tree
* K = K & {branchingnode}
*/
branchingnode = V[branchidx];
K[level-1] = branchingnode;
weightK = weightKold + weights[branchingnode];
/* update the set of nodes for branching
* V = V \ {branchingnode}
*/
nValive--;
for( i = branchidx; i < nValive; ++i )
{
V[i] = V[i+1];
apbound[i] = apbound[i+1];
}
/* set the nodes for the next level of b&b tree
* Vcurrent = nodes of V, that are adjacent to branchingnode
*/
nVcurrent = selectadjnodes(tcliquegraph, branchingnode, V, nValive, Vcurrent);
/* process the selected subtree */
backtracklevel = branch(getnnodes, getweights, isedge, selectadjnodes, tcliquegraph, newsol, tcliquedata,
mem, cliquehash, buffer,
level, Vcurrent, nVcurrent, Vzero, nVzero, gsd, iscolored, K, weightK,
maxcliquenodes, nmaxcliquenodes, maxcliqueweight,
curcliquenodes, ncurcliquenodes, curcliqueweight, tmpcliquenodes,
maxfirstnodeweight, ntreenodes, maxntreenodes, backtrackfreq, maxnzeroextensions, -1, status);
/* if all other candidates stayed in the candidate list, the current branching was optimal and
* there is no need to try the remaining ones
*/
if( nVcurrent == nValive )
{
debugMessage("branching on node %d was optimal - ignoring remaining candidates\n", branchingnode);
nValive = 0;
}
/* if we had a fixed node, ignore all other nodes */
if( fixednode >= 0 )
nValive = 0;
}
debugMessage("========================== branching level %d end =============================\n\n", level);
/* free data structures */
BMSfreeMemoryArray(&Vcurrent);
}
/* check, whether any branchings have been applied, or if this node is a leaf of the branching tree */
if( isleaf )
{
/* the current clique is the best clique found on the path to this leaf
* -> check, whether it is an improvement to the currently best clique
*/
if( *curcliqueweight > *maxcliqueweight )
{
TCLIQUE_Bool stopsolving;
debugMessage("found clique of weight %d at node %d in level %d\n", *curcliqueweight, *ntreenodes, level);
newSolution(selectadjnodes, tcliquegraph, newsol, tcliquedata, cliquehash, buffer, Vzero, nVzero,
maxnzeroextensions, curcliquenodes, *ncurcliquenodes, *curcliqueweight,
maxcliquenodes, nmaxcliquenodes, maxcliqueweight, &stopsolving);
if( stopsolving )
{
debugMessage(" -> solving terminated by callback method\n");
backtracklevel = 0;
}
}
/* discard the current clique */
*ncurcliquenodes = 0;
*curcliqueweight = 0;
}
#ifdef TCLIQUE_DEBUG
if( level > backtracklevel )
{
debugMessage("premature backtracking after %d nodes - level %d\n", *ntreenodes, level);
}
#endif
/* free data structures */
BMSfreeMemoryArray(&apbound);
return backtracklevel;
}
/** 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;
}
/** 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;
}
/** reads an BLK file */
static
SCIP_RETCODE readBLKFile(
SCIP* scip, /**< SCIP data structure */
SCIP_READER* reader, /**< reader data structure */
BLKINPUT* blkinput, /**< BLK reading data */
const char* filename /**< name of the input file */
)
{
DEC_DECOMP *decdecomp;
int i;
int nconss;
int nblocksread;
int nvars;
SCIP_READERDATA* readerdata;
SCIP_CONS** conss;
nblocksread = FALSE;
assert(scip != NULL);
assert(reader != NULL);
assert(blkinput != NULL);
if( SCIPgetStage(scip) < SCIP_STAGE_TRANSFORMED )
SCIP_CALL( SCIPtransformProb(scip) );
readerdata = SCIPreaderGetData(reader);
assert(readerdata != NULL);
readerdata->nlinkingcons = SCIPgetNConss(scip);
readerdata->nlinkingvars = 0;
nvars = SCIPgetNVars(scip);
conss = SCIPgetConss(scip);
nconss = SCIPgetNConss(scip);
/* alloc: var -> block mapping */
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->varstoblock, nvars) );
for( i = 0; i < nvars; i ++ )
{
readerdata->varstoblock[i] = NOVALUE;
}
/* alloc: linkingvar -> blocks mapping */
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->linkingvarsblocks, nvars) );
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->nlinkingvarsblocks, nvars) );
BMSclearMemoryArray(readerdata->linkingvarsblocks, nvars);
BMSclearMemoryArray(readerdata->nlinkingvarsblocks, nvars);
/* cons -> block mapping */
SCIP_CALL( SCIPhashmapCreate(&readerdata->constoblock, SCIPblkmem(scip), nconss) );
for( i = 0; i < SCIPgetNConss(scip); i ++ )
{
SCIP_CALL( SCIPhashmapInsert(readerdata->constoblock, conss[i], (void*)(size_t) NOVALUE) );
}
/* open file */
blkinput->file = SCIPfopen(filename, "r");
if( blkinput->file == NULL )
{
SCIPerrorMessage("cannot open file <%s> for reading\n", filename);
SCIPprintSysError(filename);
return SCIP_NOFILE;
}
/* parse the file */
blkinput->section = BLK_START;
while( blkinput->section != BLK_END && !hasError(blkinput) )
{
switch( blkinput->section )
{
case BLK_START:
SCIP_CALL( readStart(scip, blkinput) );
break;
case BLK_PRESOLVED:
SCIP_CALL( readPresolved(scip, blkinput) );
if( blkinput->presolved && SCIPgetStage(scip) < SCIP_STAGE_PRESOLVED )
{
assert(blkinput->haspresolvesection);
/** @bug GCG should be able to presolve the problem first */
SCIPverbMessage(scip, SCIP_VERBLEVEL_MINIMAL, NULL, "decomposition belongs to the presolved problem, please presolve the problem first.\n");
goto TERMINATE;
}
break;
case BLK_NBLOCKS:
SCIP_CALL( readNBlocks(scip, blkinput) );
if( blkinput->haspresolvesection && !blkinput->presolved && SCIPgetStage(scip) >= SCIP_STAGE_PRESOLVED )
{
SCIPverbMessage(scip, SCIP_VERBLEVEL_MINIMAL, NULL, "decomposition belongs to the unpresolved problem, please re-read the problem and read the decomposition without presolving.\n");
goto TERMINATE;
}
if( !blkinput->haspresolvesection )
{
SCIPwarningMessage(scip, "decomposition has no presolve section at beginning. The behaviour is undefined. See the FAQ for further information.\n");
}
break;
case BLK_BLOCK:
if( nblocksread == FALSE )
{
/* alloc n vars per block */
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->nblockvars, blkinput->nblocks) );
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->nblockcons, blkinput->nblocks) );
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->blockcons, blkinput->nblocks) );
for( i = 0; i < blkinput->nblocks; ++i )
{
readerdata->nblockvars[i] = 0;
readerdata->nblockcons[i] = 0;
SCIP_CALL( SCIPallocMemoryArray(scip, &(readerdata->blockcons[i]), nconss) ); /*lint !e866*/
}
nblocksread = TRUE;
}
SCIP_CALL( readBlock(scip, blkinput, readerdata) );
break;
case BLK_MASTERCONSS:
SCIP_CALL( readMasterconss(scip, blkinput, readerdata) );
break;
case BLK_END: /* this is already handled in the while() loop */
default:
SCIPerrorMessage("invalid BLK file section <%d>\n", blkinput->section);
return SCIP_INVALIDDATA;
}
}
SCIP_CALL( DECdecompCreate(scip, &decdecomp) );
/* fill decomp */
SCIP_CALL( fillDecompStruct(scip, blkinput, decdecomp, readerdata) );
/* add decomp to cons_decomp */
SCIP_CALL( SCIPconshdlrDecompAddDecdecomp(scip, decdecomp) );
for( i = 0; i < nvars; ++i )
{
assert(readerdata->linkingvarsblocks[i] != NULL || readerdata->nlinkingvarsblocks[i] == 0);
if( readerdata->nlinkingvarsblocks[i] > 0 )
{
SCIPfreeMemoryArray(scip, &readerdata->linkingvarsblocks[i]);
}
}
TERMINATE:
if( nblocksread )
{
for( i = blkinput->nblocks - 1; i >= 0; --i )
{
SCIPfreeMemoryArray(scip, &(readerdata->blockcons[i]));
}
SCIPfreeMemoryArray(scip, &readerdata->blockcons);
SCIPfreeMemoryArray(scip, &readerdata->nblockcons);
SCIPfreeMemoryArray(scip, &readerdata->nblockvars);
}
SCIPhashmapFree(&readerdata->constoblock);
SCIPfreeMemoryArray(scip, &readerdata->nlinkingvarsblocks);
SCIPfreeMemoryArray(scip, &readerdata->linkingvarsblocks);
SCIPfreeMemoryArray(scip, &readerdata->varstoblock);
/* close file */
SCIPfclose(blkinput->file);
return SCIP_OKAY;
}
/** get next input line; this are all characters until the next semicolon */
static
SCIP_RETCODE getInputString(
SCIP* scip, /**< SCIP data structure */
CIPINPUT* cipinput /**< CIP parsing data */
)
{
char* endline;
char* endcharacter;
char* windowsendlinechar;
assert(cipinput != NULL);
/* read next line */
cipinput->endfile = (SCIPfgets(cipinput->strbuf, cipinput->len, cipinput->file) == NULL);
if( cipinput->endfile )
{
/* clear the line for safety reason */
BMSclearMemoryArray(cipinput->strbuf, cipinput->len);
return SCIP_OKAY;
}
cipinput->linenumber++;
endline = strchr(cipinput->strbuf, '\n');
endcharacter = strchr(cipinput->strbuf, ';');
while( endline == NULL || (endcharacter == NULL && cipinput->section == CIP_CONSTRAINTS && strncmp(cipinput->strbuf, "END", 3) != 0 ) )
{
int pos;
/* we refill the buffer from the '\n' character */
if( endline == NULL )
pos = cipinput->len - 1;
else
pos = (int) (endline - cipinput->strbuf);
/* don't erase the '\n' from all buffers for constraints */
if( endline != NULL && cipinput->section == CIP_CONSTRAINTS )
pos++;
/* if necessary reallocate memory */
if( pos + cipinput->readingsize >= cipinput->len )
{
cipinput->len = SCIPcalcMemGrowSize(scip, pos + cipinput->readingsize);
SCIP_CALL( SCIPreallocBufferArray(scip, &(cipinput->strbuf), cipinput->len) );
}
/* read next line */
cipinput->endfile = (SCIPfgets(&(cipinput->strbuf[pos]), cipinput->len - pos, cipinput->file) == NULL);
if( cipinput->endfile )
{
/* clear the line for safety reason */
BMSclearMemoryArray(cipinput->strbuf, cipinput->len);
return SCIP_OKAY;
}
cipinput->linenumber++;
endline = strrchr(cipinput->strbuf, '\n');
endcharacter = strchr(cipinput->strbuf, ';');
}
assert(endline != NULL);
/*SCIPdebugMessage("read line: %s\n", cipinput->strbuf);*/
/* check for windows "carriage return" endline character */
windowsendlinechar = strrchr(cipinput->strbuf, '\r');
if( windowsendlinechar != NULL && windowsendlinechar + 1 == endline )
--endline;
else
/* if the assert should not hold we found a windows "carriage return" which was not at the end of the line */
assert(windowsendlinechar == NULL);
if( cipinput->section == CIP_CONSTRAINTS && endcharacter != NULL && endline - endcharacter != 1 )
{
SCIPerrorMessage("Constraint line has to end with ';\\n' (line: %d).\n", cipinput->linenumber);
cipinput->haserror = TRUE;
return SCIP_OKAY; /* return error at hightest level */
}
*endline = '\0';
return SCIP_OKAY;
}
/** execution method of presolver */
static
SCIP_DECL_PRESOLEXEC(presolExecDualagg)
{ /*lint --e{715}*/
SCIPMILPMATRIX* matrix;
SCIP_Bool initialized;
SCIP_Bool complete;
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
if( (SCIPgetStage(scip) != SCIP_STAGE_PRESOLVING) || SCIPinProbing(scip) || SCIPisNLPEnabled(scip) )
return SCIP_OKAY;
if( SCIPisStopped(scip) || SCIPgetNActivePricers(scip) > 0 )
return SCIP_OKAY;
if( SCIPgetNBinVars(scip) == 0 )
return SCIP_OKAY;
if( !SCIPallowDualReds(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
matrix = NULL;
SCIP_CALL( SCIPmatrixCreate(scip, &matrix, &initialized, &complete) );
/* we only work on pure MIPs currently */
if( initialized && complete )
{
AGGRTYPE* aggtypes;
SCIP_VAR** binvars;
int nvaragg;
int ncols;
ncols = SCIPmatrixGetNColumns(matrix);
nvaragg = 0;
SCIP_CALL( SCIPallocBufferArray(scip, &aggtypes, ncols) );
BMSclearMemoryArray(aggtypes, ncols);
SCIP_CALL( SCIPallocBufferArray(scip, &binvars, ncols) );
SCIPdebug( BMSclearMemoryArray(binvars, ncols) );
/* search for aggregations */
SCIP_CALL( findUplockAggregations(scip, matrix, &nvaragg, aggtypes, binvars) );
SCIP_CALL( findDownlockAggregations(scip, matrix, &nvaragg, aggtypes, binvars) );
/* apply aggregations, if we found any */
if( nvaragg > 0 )
{
int v;
for( v = 0; v < ncols; v++ )
{
if( aggtypes[v] != NOAGG )
{
SCIP_Bool infeasible;
SCIP_Bool redundant;
SCIP_Bool aggregated;
SCIP_Real ub;
SCIP_Real lb;
ub = SCIPmatrixGetColUb(matrix, v);
lb = SCIPmatrixGetColLb(matrix, v);
/* aggregate variable */
assert(binvars[v] != NULL);
if( aggtypes[v] == BIN0UBOUND )
{
SCIP_CALL( SCIPaggregateVars(scip, SCIPmatrixGetVar(matrix, v), binvars[v], 1.0, ub-lb,
ub, &infeasible, &redundant, &aggregated) );
}
else
{
assert(aggtypes[v] == BIN0LBOUND);
SCIP_CALL( SCIPaggregateVars(scip, SCIPmatrixGetVar(matrix, v), binvars[v], 1.0, lb-ub,
lb, &infeasible, &redundant, &aggregated) );
}
/* infeasible aggregation */
if( infeasible )
{
SCIPdebugMessage(" -> infeasible aggregation\n");
*result = SCIP_CUTOFF;
return SCIP_OKAY;
}
if( aggregated )
(*naggrvars)++;
}
}
/* set result pointer */
if( (*naggrvars) > 0 )
*result = SCIP_SUCCESS;
}
SCIPfreeBufferArray(scip, &binvars);
SCIPfreeBufferArray(scip, &aggtypes);
}
SCIPmatrixFree(scip, &matrix);
return SCIP_OKAY;
}
/** colors the positive weighted nodes of a given set of nodes V with the lowest possible number of colors and
* finds a clique in the graph induced by V, an upper bound and an apriori bound for further branching steps
*/
TCLIQUE_WEIGHT tcliqueColoring(
TCLIQUE_GETNNODES((*getnnodes)), /**< user function to get the number of nodes */
TCLIQUE_GETWEIGHTS((*getweights)), /**< user function to get the node weights */
TCLIQUE_SELECTADJNODES((*selectadjnodes)), /**< user function to select adjacent edges */
TCLIQUE_GRAPH* tcliquegraph, /**< pointer to graph data structure */
BMS_CHKMEM* mem, /**< block memory */
int* buffer, /**< buffer of size nnodes */
int* V, /**< non-zero weighted nodes for branching */
int nV, /**< number of non-zero weighted nodes for branching */
NBC* gsd, /**< neighbor color information of all nodes */
TCLIQUE_Bool* iscolored, /**< coloring status of all nodes */
TCLIQUE_WEIGHT* apbound, /**< pointer to store apriori bound of nodes for branching */
int* clique, /**< buffer for storing the clique */
int* nclique, /**< pointer to store number of nodes in the clique */
TCLIQUE_WEIGHT* weightclique /**< pointer to store the weight of the clique */
)
{
const TCLIQUE_WEIGHT* weights;
TCLIQUE_WEIGHT maxsatdegree;
TCLIQUE_WEIGHT range;
TCLIQUE_Bool growclique;
int node;
int nodeVindex;
int i;
int j;
LIST_ITV* colorinterval;
LIST_ITV nwcitv;
LIST_ITV* pnc;
LIST_ITV* lcitv;
LIST_ITV* item;
LIST_ITV* tmpitem;
int* workclique;
int* currentclique;
int ncurrentclique;
int weightcurrentclique;
int* Vadj;
int nVadj;
int adjidx;
assert(getnnodes != NULL);
assert(getweights != NULL);
assert(selectadjnodes != NULL);
assert(buffer != NULL);
assert(V != NULL);
assert(nV > 0);
assert(clique != NULL);
assert(nclique != NULL);
assert(weightclique != NULL);
assert(gsd != NULL);
assert(iscolored != NULL);
weights = getweights(tcliquegraph);
assert(weights != NULL);
/* initialize maximum weight clique found so far */
growclique = TRUE;
*nclique = 0;
*weightclique = 0;
/* get node of V with maximum weight */
nodeVindex = getMaxWeightIndex(getnnodes, getweights, tcliquegraph, V, nV);
node = V[nodeVindex];
assert(0 <= node && node < getnnodes(tcliquegraph));
range = weights[node];
assert(range > 0);
/* set up data structures for coloring */
BMSclearMemoryArray(iscolored, nV); /* new-memory */
BMSclearMemoryArray(gsd, nV); /* new-memory */
iscolored[nodeVindex] = TRUE;
/* color the first node */
debugMessage("---------------coloring-----------------\n");
debugMessage("1. node choosen: vindex=%d, vertex=%d, satdeg=%d, range=%d)\n",
nodeVindex, node, gsd[nodeVindex].satdeg, range);
/* set apriori bound: apbound(v_i) = satdeg(v_i) + weight(v_i) */
apbound[nodeVindex] = range;
assert(apbound[nodeVindex] > 0);
/* update maximum saturation degree: maxsatdeg = max { satdeg(v_i) + weight(v_i) | v_i in V } */
maxsatdegree = range;
debugMessage("-> updated neighbors:\n");
/* set neighbor color of the adjacent nodes of node */
Vadj = buffer;
nVadj = selectadjnodes(tcliquegraph, node, V, nV, Vadj);
for( i = 0, adjidx = 0; i < nV && adjidx < nVadj; ++i )
{
assert(V[i] <= Vadj[adjidx]); /* Vadj is a subset of V */
if( V[i] == Vadj[adjidx] )
{
/* node is adjacent to itself, but we do not need to color it again */
if( i == nodeVindex )
{
/* go to the next node in Vadj */
adjidx++;
continue;
}
debugMessage(" nodeVindex=%d, node=%d, weight=%d, satdegold=%d -> ",
i, V[i], weights[V[i]], gsd[i].satdeg);
/* sets satdeg for adjacent node */
gsd[i].satdeg = range;
/* creates new color interval [1,range] */
ALLOC_ABORT( BMSallocChunkMemory(mem, &colorinterval) );
colorinterval->next = NULL;
colorinterval->itv.inf = 1;
colorinterval->itv.sup = range;
/* colorinterval is the first added element of the list of neighborcolors of the adjacent node */
gsd[i].lcitv = colorinterval;
/* go to the next node in Vadj */
adjidx++;
debugPrintf("satdegnew=%d, nbc=[%d,%d]\n", gsd[i].satdeg, gsd[i].lcitv->itv.inf, gsd[i].lcitv->itv.sup);
}
}
/* set up data structures for the current clique */
ALLOC_ABORT( BMSallocMemoryArray(¤tclique, nV) );
workclique = clique;
/* add node to the current clique */
currentclique[0] = node;
ncurrentclique = 1;
weightcurrentclique = range;
/* color all other nodes of V */
for( i = 0 ; i < nV-1; i++ )
{
assert((workclique == clique) != (currentclique == clique));
/* selects the next uncolored node to color */
nodeVindex = getMaxSatdegIndex(V, nV, gsd, iscolored, weights);
if( nodeVindex == -1 ) /* no uncolored nodes left */
break;
node = V[nodeVindex];
assert(0 <= node && node < getnnodes(tcliquegraph));
range = weights[node];
assert(range > 0);
iscolored[nodeVindex] = TRUE;
debugMessage("%d. node choosen: vindex=%d, vertex=%d, satdeg=%d, range=%d, growclique=%u, weight=%d)\n",
i+2, nodeVindex, node, gsd[nodeVindex].satdeg, range, growclique, weightcurrentclique);
/* set apriori bound: apbound(v_i) = satdeg(v_i) + weight(v_i) */
apbound[nodeVindex] = gsd[nodeVindex].satdeg + range;
assert(apbound[nodeVindex] > 0);
/* update maximum saturation degree: maxsatdeg = max { satdeg(v_i) + weight(v_i) | v_i in V } */
if( maxsatdegree < apbound[nodeVindex] )
maxsatdegree = apbound[nodeVindex];
/* update clique */
if( gsd[nodeVindex].satdeg == 0 )
{
/* current node is not adjacent to nodes of current clique,
* i.e. current clique can not be increased
*/
debugMessage("current node not adjacend to current clique (weight:%d) -> starting new clique\n",
weightcurrentclique);
/* check, if weight of current clique is larger than weight of maximum weight clique found so far */
if( weightcurrentclique > *weightclique )
{
int* tmp;
/* update maximum weight clique found so far */
assert((workclique == clique) != (currentclique == clique));
tmp = workclique;
*weightclique = weightcurrentclique;
*nclique = ncurrentclique;
workclique = currentclique;
currentclique = tmp;
assert((workclique == clique) != (currentclique == clique));
}
weightcurrentclique = 0;
ncurrentclique = 0;
growclique = TRUE;
}
if( growclique )
{
/* check, if the current node is still adjacent to all nodes in the clique */
if( gsd[nodeVindex].satdeg == weightcurrentclique )
{
assert(ncurrentclique < nV);
currentclique[ncurrentclique] = node;
ncurrentclique++;
weightcurrentclique += range;
#ifdef TCLIQUE_DEBUG
{
int k;
debugMessage("current clique (size:%d, weight:%d):", ncurrentclique, weightcurrentclique);
for( k = 0; k < ncurrentclique; ++k )
debugPrintf(" %d", currentclique[k]);
debugPrintf("\n");
}
#endif
}
else
{
debugMessage("node satdeg: %d, clique weight: %d -> stop growing clique\n",
gsd[nodeVindex].satdeg, weightcurrentclique);
growclique = FALSE;
}
}
/* search for fitting color intervals for current node */
pnc = &nwcitv;
if( gsd[nodeVindex].lcitv == NULL )
{
/* current node has no colored neighbors yet: create new color interval [1,range] */
ALLOC_ABORT( BMSallocChunkMemory(mem, &colorinterval) );
colorinterval->next = NULL;
colorinterval->itv.inf = 1;
colorinterval->itv.sup = range;
/* add the new colorinterval [1, range] to the list of chosen colorintervals for node */
pnc->next = colorinterval;
pnc = colorinterval;
}
else
{
int tocolor;
int dif;
/* current node has colored neighbors */
tocolor = range;
lcitv = gsd[nodeVindex].lcitv;
/* check, if first neighbor color interval [inf, sup] has inf > 1 */
if( lcitv->itv.inf != 1 )
{
/* create new interval [1, min{range, inf}] */
dif = lcitv->itv.inf - 1 ;
if( dif > tocolor )
dif = tocolor;
ALLOC_ABORT( BMSallocChunkMemory(mem, &colorinterval) );
colorinterval->next = NULL;
colorinterval->itv.inf = 1;
colorinterval->itv.sup = dif;
tocolor -= dif;
pnc->next = colorinterval;
pnc = colorinterval;
}
/* as long as node is not colored with all colors, create new color interval by filling
* the gaps in the existing neighbor color intervals of the neighbors of node
*/
while( tocolor > 0 )
{
dif = tocolor;
ALLOC_ABORT( BMSallocChunkMemory(mem, &colorinterval) );
colorinterval->next = NULL;
colorinterval->itv.inf = lcitv->itv.sup+1;
if( lcitv->next != NULL )
{
int min;
min = lcitv->next->itv.inf - lcitv->itv.sup - 1;
if( dif > min )
dif = min;
lcitv = lcitv->next;
}
colorinterval->itv.sup = colorinterval->itv.inf + dif - 1;
tocolor -= dif;
pnc->next = colorinterval;
pnc = colorinterval;
}
}
debugMessage("-> updated neighbors:\n");
/* update saturation degree and neighbor colorintervals of all neighbors of node */
Vadj = buffer;
nVadj = selectadjnodes(tcliquegraph, node, V, nV, Vadj);
for( j = 0, adjidx = 0; j < nV && adjidx < nVadj; ++j )
{
assert(V[j] <= Vadj[adjidx]); /* Vadj is a subset of V */
if( V[j] == Vadj[adjidx] )
{
if( !iscolored[j] )
{
debugMessage(" nodeVindex=%d, node=%d, weight=%d, satdegold=%d -> ",
j, V[j], weights[V[j]], gsd[j].satdeg);
updateNeighbor(mem, &gsd[j], nwcitv.next);
debugPrintf("satdegnew=%d, nbc=[%d,%d]\n", gsd[j].satdeg, gsd[j].lcitv->itv.inf, gsd[j].lcitv->itv.sup);
}
/* go to the next node in Vadj */
adjidx++;
}
}
/* free data structure of created colorintervals */
item = nwcitv.next;
while( item != NULL )
{
tmpitem = item->next;
BMSfreeChunkMemory(mem, &item);
item = tmpitem;
}
/* free data structure of neighbor colorinterval of node just colored */
item = gsd[nodeVindex].lcitv;
while( item != NULL )
{
tmpitem = item->next;
BMSfreeChunkMemory(mem, &item);
item = tmpitem;
}
}
assert((workclique == clique) != (currentclique == clique));
/* update maximum weight clique found so far */
if( weightcurrentclique > *weightclique )
{
int* tmp;
tmp = workclique;
*weightclique = weightcurrentclique;
*nclique = ncurrentclique;
workclique = currentclique;
currentclique = tmp;
}
assert((workclique == clique) != (currentclique == clique));
/* move the found clique to the provided clique pointer, if it is not the memory array */
if( workclique != clique )
{
assert(clique == currentclique);
assert(*nclique <= nV);
BMScopyMemoryArray(clique, workclique, *nclique);
currentclique = workclique;
}
/* free data structures */
BMSfreeMemoryArray(¤tclique);
/* clear chunk memory */
BMSclearChunkMemory(mem);
debugMessage("------------coloringend-----------------\n");
return maxsatdegree;
}
/** performs the all fullstrong branching */
static
SCIP_RETCODE branch(
SCIP* scip, /**< SCIP data structure */
SCIP_BRANCHRULE* branchrule, /**< branching rule */
SCIP_Bool allowaddcons, /**< should adding constraints be allowed to avoid a branching? */
SCIP_RESULT* result /**< pointer to store the result of the callback method */
)
{
SCIP_BRANCHRULEDATA* branchruledata;
SCIP_VAR** pseudocands;
SCIP_Real bestdown;
SCIP_Real bestup;
SCIP_Real bestscore;
SCIP_Real provedbound;
SCIP_Bool exactsolve;
SCIP_Bool allcolsinlp;
SCIP_Bool bestdownvalid;
SCIP_Bool bestupvalid;
int npseudocands;
int npriopseudocands;
int bestpseudocand;
#ifndef NDEBUG
SCIP_Real cutoffbound;
cutoffbound = SCIPgetCutoffbound(scip);
#endif
assert(branchrule != NULL);
assert(strcmp(SCIPbranchruleGetName(branchrule), BRANCHRULE_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
/* check, if all existing columns are in LP, and thus the strong branching results give lower bounds */
allcolsinlp = SCIPallColsInLP(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);
/* get branching rule data */
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
if( branchruledata->skipdown == NULL )
{
int nvars;
nvars = SCIPgetNVars(scip);
assert(branchruledata->skipup == NULL);
SCIP_CALL( SCIPallocMemoryArray(scip, &branchruledata->skipdown, nvars) );
SCIP_CALL( SCIPallocMemoryArray(scip, &branchruledata->skipup, nvars) );
BMSclearMemoryArray(branchruledata->skipdown, nvars);
BMSclearMemoryArray(branchruledata->skipup, nvars);
}
/* get all non-fixed variables (not only the fractional ones) */
SCIP_CALL( SCIPgetPseudoBranchCands(scip, &pseudocands, &npseudocands, &npriopseudocands) );
assert(npseudocands > 0);
assert(npriopseudocands > 0);
SCIP_CALL( SCIPselectVarPseudoStrongBranching(scip, pseudocands, branchruledata->skipdown, branchruledata->skipup, npseudocands, npriopseudocands,
allowaddcons, &bestpseudocand, &bestdown, &bestup, &bestscore, &bestdownvalid, &bestupvalid, &provedbound, result) );
if( *result != SCIP_CUTOFF && *result != SCIP_REDUCEDDOM && *result != SCIP_CONSADDED )
{
SCIP_NODE* downchild;
SCIP_NODE* eqchild;
SCIP_NODE* upchild;
SCIP_VAR* var;
assert(*result == SCIP_DIDNOTRUN);
assert(0 <= bestpseudocand && bestpseudocand < npseudocands);
assert(SCIPisLT(scip, provedbound, cutoffbound));
var = pseudocands[bestpseudocand];
/* perform the branching */
SCIPdebugMessage(" -> %d candidates, selected candidate %d: variable <%s>[%g,%g] (solval=%g, down=%g, up=%g, score=%g)\n",
npseudocands, bestpseudocand, SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), SCIPvarGetLPSol(var),
bestdown, bestup, bestscore);
SCIP_CALL( SCIPbranchVarVal(scip, var, SCIPvarGetLPSol(var), &downchild, &eqchild, &upchild) );
/* update the lower bounds in the children */
if( allcolsinlp && !exactsolve )
{
if( downchild != NULL )
{
SCIP_CALL( SCIPupdateNodeLowerbound(scip, downchild, bestdownvalid ? MAX(bestdown, provedbound) : provedbound) );
SCIPdebugMessage(" -> down child's lowerbound: %g\n", SCIPnodeGetLowerbound(downchild));
}
if( eqchild != NULL )
{
SCIP_CALL( SCIPupdateNodeLowerbound(scip, eqchild, provedbound) );
SCIPdebugMessage(" -> eq child's lowerbound: %g\n", SCIPnodeGetLowerbound(eqchild));
}
if( upchild != NULL )
{
SCIP_CALL( SCIPupdateNodeLowerbound(scip, upchild, bestupvalid ? MAX(bestup, provedbound) : provedbound) );
SCIPdebugMessage(" -> up child's lowerbound: %g\n", SCIPnodeGetLowerbound(upchild));
}
}
*result = SCIP_BRANCHED;
}
return SCIP_OKAY;
}
/** 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;
}
/** reads the next line from the input file into the line buffer; skips comments;
* returns whether a line could be read
*/
static
SCIP_Bool getNextLine(
SCIP* scip, /**< SCIP data structure */
LPINPUT* lpinput /**< LP reading data */
)
{
int i;
assert(lpinput != NULL);
/* if we previously detected a comment we have to parse the remaining line away if there is something left */
if( !lpinput->endline && lpinput->comment )
{
SCIPdebugMessage("Throwing rest of comment away.\n");
do
{
lpinput->linebuf[LP_MAX_LINELEN-2] = '\0';
(void)SCIPfgets(lpinput->linebuf, (int) sizeof(lpinput->linebuf), lpinput->file);
}
while( lpinput->linebuf[LP_MAX_LINELEN-2] != '\0' );
lpinput->comment = FALSE;
lpinput->endline = TRUE;
}
/* read next line */
lpinput->linepos = 0;
lpinput->linebuf[LP_MAX_LINELEN-2] = '\0';
if( SCIPfgets(lpinput->linebuf, (int) sizeof(lpinput->linebuf), lpinput->file) == NULL )
{
/* clear the line, this is really necessary here! */
BMSclearMemoryArray(lpinput->linebuf, LP_MAX_LINELEN);
return FALSE;
}
lpinput->linenumber++;
/* if line is too long for our buffer correct the buffer and correct position in file */
if( lpinput->linebuf[LP_MAX_LINELEN-2] != '\0' )
{
char* last;
/* buffer is full; erase last token since it might be incomplete */
lpinput->endline = FALSE;
last = strrchr(lpinput->linebuf, ' ');
if( last == NULL )
{
SCIPwarningMessage(scip, "we read %d characters from the file; this might indicate a corrupted input file!",
LP_MAX_LINELEN - 2);
lpinput->linebuf[LP_MAX_LINELEN-2] = '\0';
SCIPdebugMessage("the buffer might be corrupted\n");
}
else
{
SCIPfseek(lpinput->file, -(long) strlen(last) - 1, SEEK_CUR);
SCIPdebugMessage("correct buffer, reread the last %ld characters\n", (long) strlen(last) + 1);
*last = '\0';
}
}
else
{
/* found end of line */
lpinput->endline = TRUE;
}
lpinput->linebuf[LP_MAX_LINELEN-1] = '\0'; /* we want to use lookahead of one char -> we need two \0 at the end */
lpinput->comment = FALSE;
/* skip characters after comment symbol */
for( i = 0; commentchars[i] != '\0'; ++i )
{
char* commentstart;
commentstart = strchr(lpinput->linebuf, commentchars[i]);
if( commentstart != NULL )
{
*commentstart = '\0';
*(commentstart+1) = '\0'; /* we want to use lookahead of one char -> we need two \0 at the end */
lpinput->comment = TRUE;
break;
}
}
return TRUE;
}
/** 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;
}
