Scippy

SCIP

Solving Constraint Integer Programs

heur_rins.c
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1/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
2/* */
3/* This file is part of the program and library */
4/* SCIP --- Solving Constraint Integer Programs */
5/* */
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23/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
24
25/**@file heur_rins.c
26 * @ingroup DEFPLUGINS_HEUR
27 * @brief LNS heuristic that combines the incumbent with the LP optimum
28 * @author Timo Berthold
29 */
30
31/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
32
34#include "scip/heuristics.h"
35#include "scip/heur_rins.h"
36#include "scip/pub_event.h"
37#include "scip/pub_heur.h"
38#include "scip/pub_message.h"
39#include "scip/pub_misc.h"
40#include "scip/pub_sol.h"
41#include "scip/pub_var.h"
42#include "scip/scip_branch.h"
43#include "scip/scip_cons.h"
44#include "scip/scip_copy.h"
45#include "scip/scip_event.h"
46#include "scip/scip_general.h"
47#include "scip/scip_heur.h"
48#include "scip/scip_lp.h"
49#include "scip/scip_mem.h"
50#include "scip/scip_message.h"
51#include "scip/scip_nodesel.h"
52#include "scip/scip_numerics.h"
53#include "scip/scip_param.h"
54#include "scip/scip_prob.h"
55#include "scip/scip_sol.h"
56#include "scip/scip_solve.h"
58#include <string.h>
59
60#define HEUR_NAME "rins"
61#define HEUR_DESC "relaxation induced neighborhood search by Danna, Rothberg, and Le Pape"
62#define HEUR_DISPCHAR SCIP_HEURDISPCHAR_LNS
63#define HEUR_PRIORITY -1101000
64#define HEUR_FREQ 25
65#define HEUR_FREQOFS 0
66#define HEUR_MAXDEPTH -1
67#define HEUR_TIMING SCIP_HEURTIMING_AFTERLPNODE
68#define HEUR_USESSUBSCIP TRUE /**< does the heuristic use a secondary SCIP instance? */
69
70#define DEFAULT_NODESOFS 500 /* number of nodes added to the contingent of the total nodes */
71#define DEFAULT_MAXNODES 5000 /* maximum number of nodes to regard in the subproblem */
72#define DEFAULT_MINNODES 50 /* minimum number of nodes to regard in the subproblem */
73#define DEFAULT_MINIMPROVE 0.01 /* factor by which RINS should at least improve the incumbent */
74#define DEFAULT_MINFIXINGRATE 0.3 /* minimum percentage of integer variables that have to be fixed */
75#define DEFAULT_NODESQUOT 0.3 /* subproblem nodes in relation to nodes of the original problem */
76#define DEFAULT_LPLIMFAC 2.0 /* factor by which the limit on the number of LP depends on the node limit */
77#define DEFAULT_NWAITINGNODES 200 /* number of nodes without incumbent change that heuristic should wait */
78#define DEFAULT_USELPROWS FALSE /* should subproblem be created out of the rows in the LP rows,
79 * otherwise, the copy constructors of the constraints handlers are used */
80#define DEFAULT_COPYCUTS TRUE /* if DEFAULT_USELPROWS is FALSE, then should all active cuts from the cutpool
81 * of the original scip be copied to constraints of the subscip
82 */
83#define DEFAULT_USEUCT FALSE /* should uct node selection be used at the beginning of the search? */
85/* event handler properties */
86#define EVENTHDLR_NAME "Rins"
87#define EVENTHDLR_DESC "LP event handler for " HEUR_NAME " heuristic"
88
89/*
90 * Data structures
91 */
92
93/** primal heuristic data */
94struct SCIP_HeurData
95{
96 int nodesofs; /**< number of nodes added to the contingent of the total nodes */
97 int maxnodes; /**< maximum number of nodes to regard in the subproblem */
98 int minnodes; /**< minimum number of nodes to regard in the subproblem */
99 SCIP_Real minfixingrate; /**< minimum percentage of integer variables that have to be fixed */
100 int nwaitingnodes; /**< number of nodes without incumbent change that heuristic should wait */
101 SCIP_Real minimprove; /**< factor by which RINS should at least improve the incumbent */
102 SCIP_Real nodelimit; /**< the nodelimit employed in the current sub-SCIP, for the event handler*/
103 SCIP_Real lplimfac; /**< factor by which the limit on the number of LP depends on the node limit */
104 SCIP_Longint usednodes; /**< nodes already used by RINS in earlier calls */
105 SCIP_Real nodesquot; /**< subproblem nodes in relation to nodes of the original problem */
106 SCIP_Bool uselprows; /**< should subproblem be created out of the rows in the LP rows? */
107 SCIP_Bool copycuts; /**< if uselprows == FALSE, should all active cuts from cutpool be copied
108 * to constraints in subproblem?
109 */
110 SCIP_Bool useuct; /**< should uct node selection be used at the beginning of the search? */
111};
112
113/*
114 * Local methods
115 */
116
117
118
119
120/** determines variable fixings for RINS
121 *
122 * RINS fixes variables with matching solution values in the current LP and the
123 * incumbent solution
124 */
125static
127 SCIP* scip, /**< original SCIP data structure */
128 SCIP_VAR** fixedvars, /**< array to store source SCIP variables that should be fixed in the copy */
129 SCIP_Real* fixedvals, /**< array to store fixing values for variables that should be fixed in the copy */
130 int* nfixedvars, /**< pointer to store the number of variables that RINS can fix */
131 int fixedvarssize, /**< size of the buffer arrays to store potential fixings */
132 SCIP_Real minfixingrate, /**< percentage of integer variables that have to be fixed */
133 SCIP_Bool* success /**< pointer to store whether sufficiently many variable fixings were found */
134 )
135{
136 SCIP_SOL* bestsol; /* incumbent solution of the original problem */
137 SCIP_VAR** vars; /* original scip variables */
138 SCIP_Real fixingrate;
139
140 int nvars;
141 int nbinvars;
142 int nintvars;
143 int i;
144 int fixingcounter;
145
146 assert(fixedvals != NULL);
147 assert(fixedvars != NULL);
148 assert(nfixedvars != NULL);
149
150 /* get required data of the original problem */
151 SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
152 bestsol = SCIPgetBestSol(scip);
153 assert(bestsol != NULL);
154
155 fixingcounter = 0;
156 assert(fixedvarssize >= nbinvars + nintvars);
157
158 /* determine variables to fix in the subproblem */
159 for( i = 0; i < nbinvars + nintvars; i++ )
160 {
161 SCIP_Real lpsolval;
162 SCIP_Real solval;
163
164 /* get the current LP solution and the incumbent solution for each variable */
165 lpsolval = SCIPvarGetLPSol(vars[i]);
166 solval = SCIPgetSolVal(scip, bestsol, vars[i]);
167
168 /* iff both solutions are equal, variable is stored to be fixed */
169 if( SCIPisFeasEQ(scip, lpsolval, solval) )
170 {
171 /* store the fixing and increase the number of fixed variables */
172 fixedvars[fixingcounter] = vars[i];
173 fixedvals[fixingcounter] = solval;
174 fixingcounter++;
175 }
176 }
177
178 /* store the number of fixings */
179 *nfixedvars = fixingcounter;
180
181 /* abort, if all variables should be fixed */
182 if( fixingcounter == nbinvars + nintvars )
183 {
184 *success = FALSE;
185 return SCIP_OKAY;
186 }
187 else
188 fixingrate = (SCIP_Real)fixingcounter / (SCIP_Real)(MAX(nbinvars + nintvars, 1));
189
190 /* abort, if the amount of fixed variables is insufficient */
191 if( fixingrate < minfixingrate )
192 {
193 *success = FALSE;
194 return SCIP_OKAY;
195 }
196
197 *success = TRUE;
198 return SCIP_OKAY;
199}
200
201static
202SCIP_DECL_EVENTEXEC(eventExecRins);
204/** wrapper for the part of heuristic that runs a subscip. Wrapper is needed to avoid possible ressource leaks */
205static
207 SCIP* scip, /**< original SCIP data structure */
208 SCIP* subscip, /**< SCIP structure of the subproblem */
209 SCIP_HEUR* heur, /**< Heuristic pointer */
210 SCIP_HEURDATA* heurdata, /**< Heuristic's data */
211 SCIP_VAR** vars, /**< original problem's variables */
212 SCIP_VAR** fixedvars, /**< Fixed variables of original SCIP */
213 SCIP_Real* fixedvals, /**< Fixed values of original SCIP */
214 SCIP_RESULT* result, /**< Result pointer */
215 int nvars, /**< Number of variables */
216 int nfixedvars, /**< Number of fixed variables */
217 SCIP_Longint nnodes /**< Number of nodes in the b&b tree */
218 )
219{
220 SCIP_VAR** subvars; /* variables of the subscip */
221 SCIP_HASHMAP* varmapfw; /* hashmap for mapping between vars of scip and subscip */
222 SCIP_EVENTHDLR* eventhdlr; /* event handler for LP events */
223 SCIP_Real upperbound; /* upperbound of the original SCIP */
224 SCIP_Real cutoff; /* objective cutoff for the subproblem */
225
226 SCIP_Bool success;
227
228 int i;
229
230 /* create the variable mapping hash map */
231 SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), nvars) );
232
233 /* create a problem copy as sub SCIP */
234 SCIP_CALL( SCIPcopyLargeNeighborhoodSearch(scip, subscip, varmapfw, "rins", fixedvars, fixedvals, nfixedvars,
235 heurdata->uselprows, heurdata->copycuts, &success, NULL) );
236
237 eventhdlr = NULL;
238 /* create event handler for LP events */
239 SCIP_CALL( SCIPincludeEventhdlrBasic(subscip, &eventhdlr, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecRins, NULL) );
240 if( eventhdlr == NULL )
241 {
242 SCIPerrorMessage("event handler for " HEUR_NAME " heuristic not found.\n");
243 return SCIP_PLUGINNOTFOUND;
244 }
245
246 /* copy subproblem variables from map to obtain the same order */
247 SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
248 for( i = 0; i < nvars; i++ )
249 subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
250
251 /* free hash map */
252 SCIPhashmapFree(&varmapfw);
253
254 /* do not abort subproblem on CTRL-C */
255 SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
256
257#ifdef SCIP_DEBUG
258 /* for debugging, enable full output */
259 SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", SCIP_VERBLEVEL_FULL) );
260 SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
261#else
262 /* disable statistic timing inside sub SCIP and output to console */
263 SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", (int) SCIP_VERBLEVEL_NONE) );
264 SCIP_CALL( SCIPsetBoolParam(subscip, "timing/statistictiming", FALSE) );
265#endif
266
267 /* set limits for the subproblem */
268 SCIP_CALL( SCIPcopyLimits(scip, subscip) );
269 heurdata->nodelimit = nnodes;
270 SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nnodes) );
271 SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", MAX(10, nnodes/10)) );
272 SCIP_CALL( SCIPsetIntParam(subscip, "limits/bestsol", 3) );
273
274 /* forbid recursive call of heuristics and separators solving subMIPs */
275 SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
276
277 /* disable cutting plane separation */
279
280 /* disable expensive presolving */
282
283 /* use best estimate node selection */
284 if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
285 {
286 SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
287 }
288
289 /* activate uct node selection at the top of the tree */
290 if( heurdata->useuct && SCIPfindNodesel(subscip, "uct") != NULL && !SCIPisParamFixed(subscip, "nodeselection/uct/stdpriority") )
291 {
292 SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/uct/stdpriority", INT_MAX/2) );
293 }
294
295 /* use inference branching */
296 if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
297 {
298 SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
299 }
300
301 /* enable conflict analysis, disable analysis of boundexceeding LPs, and restrict conflict pool */
302 if( !SCIPisParamFixed(subscip, "conflict/enable") )
303 {
304 SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/enable", TRUE) );
305 }
306 if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
307 {
308 SCIP_CALL( SCIPsetCharParam(subscip, "conflict/useboundlp", 'o') );
309 }
310 if( !SCIPisParamFixed(subscip, "conflict/maxstoresize") )
311 {
312 SCIP_CALL( SCIPsetIntParam(subscip, "conflict/maxstoresize", 100) );
313 }
314
315 /* speed up sub-SCIP by not checking dual LP feasibility */
316 SCIP_CALL( SCIPsetBoolParam(subscip, "lp/checkdualfeas", FALSE) );
317
318 /* add an objective cutoff */
320
321 upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
323 {
324 cutoff = (1 - heurdata->minimprove) * SCIPgetUpperbound(scip) + heurdata->minimprove * SCIPgetLowerbound(scip);
325 }
326 else
327 {
328 if( SCIPgetUpperbound(scip) >= 0 )
329 cutoff = (1 - heurdata->minimprove) * SCIPgetUpperbound(scip);
330 else
331 cutoff = (1 + heurdata->minimprove) * SCIPgetUpperbound(scip);
332 }
333 cutoff = MIN(upperbound, cutoff);
334 SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );
335
336 /* catch LP events of sub-SCIP */
337 SCIP_CALL( SCIPtransformProb(subscip) );
338 SCIP_CALL( SCIPcatchEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, NULL) );
339
340 /* Errors in solving the subproblem should not kill the overall solving process
341 * Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
342 */
343 /* solve the subproblem */
344 SCIP_CALL_ABORT( SCIPsolve(subscip) );
345
346 /* drop LP events of sub-SCIP */
347 SCIP_CALL( SCIPdropEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, -1) );
348
349 /* we try to merge variable statistics with those of our main SCIP */
350 SCIP_CALL( SCIPmergeVariableStatistics(subscip, scip, subvars, vars, nvars) );
351
352 /* print solving statistics of subproblem if we are in SCIP's debug mode */
354
355 heurdata->usednodes += SCIPgetNNodes(subscip);
356
357 SCIP_CALL( SCIPtranslateSubSols(scip, subscip, heur, subvars, &success, NULL) );
358 if( success )
359 *result = SCIP_FOUNDSOL;
360
361 /* free subproblem */
362 SCIPfreeBufferArray(scip, &subvars);
363
364 return SCIP_OKAY;
365}
366
367/* ---------------- Callback methods of event handler ---------------- */
368
369/* exec the event handler
370 *
371 * we interrupt the solution process
372 */
373static
374SCIP_DECL_EVENTEXEC(eventExecRins)
375{
376 SCIP_HEURDATA* heurdata;
377
378 assert(eventhdlr != NULL);
379 assert(eventdata != NULL);
380 assert(strcmp(SCIPeventhdlrGetName(eventhdlr), EVENTHDLR_NAME) == 0);
381 assert(event != NULL);
383
384 heurdata = (SCIP_HEURDATA*)eventdata;
385 assert(heurdata != NULL);
386
387 /* interrupt solution process of sub-SCIP */
388 if( SCIPgetNLPs(scip) > heurdata->lplimfac * heurdata->nodelimit )
389 {
390 SCIPdebugMsg(scip, "interrupt after %" SCIP_LONGINT_FORMAT " LPs\n",SCIPgetNLPs(scip));
392 }
393
394 return SCIP_OKAY;
395}
396
397
398/*
399 * Callback methods of primal heuristic
400 */
402/** copy method for primal heuristic plugins (called when SCIP copies plugins) */
403static
404SCIP_DECL_HEURCOPY(heurCopyRins)
405{ /*lint --e{715}*/
406 assert(scip != NULL);
407 assert(heur != NULL);
408 assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
409
410 /* call inclusion method of primal heuristic */
412
413 return SCIP_OKAY;
414}
416/** destructor of primal heuristic to free user data (called when SCIP is exiting) */
417static
418SCIP_DECL_HEURFREE(heurFreeRins)
419{ /*lint --e{715}*/
420 SCIP_HEURDATA* heurdata;
421
422 assert( heur != NULL );
423 assert( scip != NULL );
424
425 /* get heuristic data */
426 heurdata = SCIPheurGetData(heur);
427 assert( heurdata != NULL );
428
429 /* free heuristic data */
430 SCIPfreeBlockMemory(scip, &heurdata);
431 SCIPheurSetData(heur, NULL);
432
433 return SCIP_OKAY;
434}
435
437/** initialization method of primal heuristic (called after problem was transformed) */
438static
439SCIP_DECL_HEURINIT(heurInitRins)
440{ /*lint --e{715}*/
441 SCIP_HEURDATA* heurdata;
442
443 assert( heur != NULL );
444 assert( scip != NULL );
445
446 /* get heuristic's data */
447 heurdata = SCIPheurGetData(heur);
448 assert( heurdata != NULL );
449
450 /* initialize data */
451 heurdata->usednodes = 0;
452
453 return SCIP_OKAY;
454}
455
457/** execution method of primal heuristic */
458static
459SCIP_DECL_HEUREXEC(heurExecRins)
460{ /*lint --e{715}*/
462
463 SCIP_HEURDATA* heurdata; /* heuristic's data */
464 SCIP* subscip; /* the subproblem created by RINS */
465 SCIP_VAR** vars; /* original problem's variables */
466 SCIP_VAR** fixedvars;
467 SCIP_Real* fixedvals;
468
469 SCIP_RETCODE retcode; /* retcode needed for wrapper method */
470
471 int nvars;
472 int nbinvars;
473 int nintvars;
474 int nfixedvars;
475
476 SCIP_Bool success;
477
478 assert( heur != NULL );
479 assert( scip != NULL );
480 assert( result != NULL );
481 assert( SCIPhasCurrentNodeLP(scip) );
482
483 *result = SCIP_DELAYED;
484
485 /* do not call heuristic of node was already detected to be infeasible */
486 if( nodeinfeasible )
487 return SCIP_OKAY;
488
489 /* get heuristic's data */
490 heurdata = SCIPheurGetData(heur);
491 assert( heurdata != NULL );
492
493 /* only call heuristic, if an optimal LP solution and a feasible solution are at hand */
495 return SCIP_OKAY;
496
497 /* only call heuristic, if the LP objective value is smaller than the cutoff bound */
499 return SCIP_OKAY;
500
501 /* only call heuristic, if the best solution comes from transformed problem */
502 assert( SCIPgetBestSol(scip) != NULL );
504 return SCIP_OKAY;
505
506 /* only call heuristic, if enough nodes were processed since last incumbent */
507 if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip)) < heurdata->nwaitingnodes)
508 return SCIP_OKAY;
509
510 *result = SCIP_DIDNOTRUN;
511
512 /* calculate the maximal number of branching nodes until heuristic is aborted */
513 nnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));
514
515 /* reward RINS if it succeeded often */
517 nnodes -= (SCIP_Longint)(100.0 * SCIPheurGetNCalls(heur)); /* count the setup costs for the sub-MIP as 100 nodes */
518 nnodes += heurdata->nodesofs;
519
520 /* determine the node limit for the current process */
521 nnodes -= heurdata->usednodes;
522 nnodes = MIN(nnodes, heurdata->maxnodes);
523
524 /* check whether we have enough nodes left to call subproblem solving */
525 if( nnodes < heurdata->minnodes )
526 return SCIP_OKAY;
527
528 SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
529
530 /* check whether discrete variables are available */
531 if( nbinvars == 0 && nintvars == 0 )
532 return SCIP_OKAY;
533
534 if( SCIPisStopped(scip) )
535 return SCIP_OKAY;
536
537 /* allocate buffer storage to hold the RINS fixings */
538 SCIP_CALL( SCIPallocBufferArray(scip, &fixedvars, nbinvars + nintvars) );
539 SCIP_CALL( SCIPallocBufferArray(scip, &fixedvals, nbinvars + nintvars) );
540
541 success = FALSE;
542
543 nfixedvars = 0;
544 /* determine possible fixings for RINS: variables with same value in bestsol and LP relaxation */
545 SCIP_CALL( determineFixings(scip, fixedvars, fixedvals, &nfixedvars, nbinvars + nintvars, heurdata->minfixingrate, &success) );
546
547 /* too few variables could be fixed by the RINS scheme */
548 if( !success )
549 goto TERMINATE;
550
551 /* check whether there is enough time and memory left */
552 SCIP_CALL( SCIPcheckCopyLimits(scip, &success) );
553
554 /* abort if no time is left or not enough memory to create a copy of SCIP */
555 if( !success )
556 goto TERMINATE;
557
558 assert(nfixedvars > 0 && nfixedvars < nbinvars + nintvars);
559
560 *result = SCIP_DIDNOTFIND;
561
562 SCIPdebugMsg(scip, "RINS heuristic fixes %d out of %d binary+integer variables\n", nfixedvars, nbinvars + nintvars);
563 SCIP_CALL( SCIPcreate(&subscip) );
564
565 retcode = wrapperRins(scip, subscip, heur, heurdata, vars, fixedvars, fixedvals, result, nvars, nfixedvars, nnodes);
566
567 SCIP_CALL( SCIPfree(&subscip) );
568
569 SCIP_CALL( retcode );
570
571TERMINATE:
572 SCIPfreeBufferArray(scip, &fixedvals);
573 SCIPfreeBufferArray(scip, &fixedvars);
574
575 return SCIP_OKAY;
576}
577
578/*
579 * primal heuristic specific interface methods
580 */
581
582/** creates the RINS primal heuristic and includes it in SCIP */
584 SCIP* scip /**< SCIP data structure */
585 )
586{
587 SCIP_HEURDATA* heurdata;
588 SCIP_HEUR* heur;
589
590 /* create Rins primal heuristic data */
591 SCIP_CALL( SCIPallocBlockMemory(scip, &heurdata) );
592
593 /* include primal heuristic */
596 HEUR_MAXDEPTH, HEUR_TIMING, HEUR_USESSUBSCIP, heurExecRins, heurdata) );
597
598 assert(heur != NULL);
599
600 /* set non-NULL pointers to callback methods */
601 SCIP_CALL( SCIPsetHeurCopy(scip, heur, heurCopyRins) );
602 SCIP_CALL( SCIPsetHeurFree(scip, heur, heurFreeRins) );
603 SCIP_CALL( SCIPsetHeurInit(scip, heur, heurInitRins) );
604
605 /* add RINS primal heuristic parameters */
606 SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/nodesofs",
607 "number of nodes added to the contingent of the total nodes",
608 &heurdata->nodesofs, FALSE, DEFAULT_NODESOFS, 0, INT_MAX, NULL, NULL) );
609
610 SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/maxnodes",
611 "maximum number of nodes to regard in the subproblem",
612 &heurdata->maxnodes, TRUE, DEFAULT_MAXNODES, 0, INT_MAX, NULL, NULL) );
613
614 SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/minnodes",
615 "minimum number of nodes required to start the subproblem",
616 &heurdata->minnodes, TRUE, DEFAULT_MINNODES, 0, INT_MAX, NULL, NULL) );
617
618 SCIP_CALL( SCIPaddRealParam(scip, "heuristics/" HEUR_NAME "/nodesquot",
619 "contingent of sub problem nodes in relation to the number of nodes of the original problem",
620 &heurdata->nodesquot, FALSE, DEFAULT_NODESQUOT, 0.0, 1.0, NULL, NULL) );
621
622 SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/nwaitingnodes",
623 "number of nodes without incumbent change that heuristic should wait",
624 &heurdata->nwaitingnodes, TRUE, DEFAULT_NWAITINGNODES, 0, INT_MAX, NULL, NULL) );
625
626 SCIP_CALL( SCIPaddRealParam(scip, "heuristics/" HEUR_NAME "/minimprove",
627 "factor by which " HEUR_NAME " should at least improve the incumbent",
628 &heurdata->minimprove, TRUE, DEFAULT_MINIMPROVE, 0.0, 1.0, NULL, NULL) );
629
630 SCIP_CALL( SCIPaddRealParam(scip, "heuristics/" HEUR_NAME "/minfixingrate",
631 "minimum percentage of integer variables that have to be fixed",
632 &heurdata->minfixingrate, FALSE, DEFAULT_MINFIXINGRATE, 0.0, 1.0, NULL, NULL) );
633
634 SCIP_CALL( SCIPaddRealParam(scip, "heuristics/" HEUR_NAME "/lplimfac",
635 "factor by which the limit on the number of LP depends on the node limit",
636 &heurdata->lplimfac, TRUE, DEFAULT_LPLIMFAC, 1.0, SCIP_REAL_MAX, NULL, NULL) );
637
638 SCIP_CALL( SCIPaddBoolParam(scip, "heuristics/" HEUR_NAME "/uselprows",
639 "should subproblem be created out of the rows in the LP rows?",
640 &heurdata->uselprows, TRUE, DEFAULT_USELPROWS, NULL, NULL) );
641
642 SCIP_CALL( SCIPaddBoolParam(scip, "heuristics/" HEUR_NAME "/copycuts",
643 "if uselprows == FALSE, should all active cuts from cutpool be copied to constraints in subproblem?",
644 &heurdata->copycuts, TRUE, DEFAULT_COPYCUTS, NULL, NULL) );
645
646 SCIP_CALL( SCIPaddBoolParam(scip, "heuristics/" HEUR_NAME "/useuct",
647 "should uct node selection be used at the beginning of the search?",
648 &heurdata->useuct, TRUE, DEFAULT_USEUCT, NULL, NULL) );
649
650 return SCIP_OKAY;
651}
#define NULL
Definition: def.h:266
#define SCIP_Longint
Definition: def.h:157
#define SCIP_REAL_MAX
Definition: def.h:173
#define SCIP_Bool
Definition: def.h:91
#define MIN(x, y)
Definition: def.h:242
#define SCIP_Real
Definition: def.h:172
#define TRUE
Definition: def.h:93
#define FALSE
Definition: def.h:94
#define MAX(x, y)
Definition: def.h:238
#define SCIP_CALL_ABORT(x)
Definition: def.h:352
#define SCIP_LONGINT_FORMAT
Definition: def.h:164
#define SCIP_CALL(x)
Definition: def.h:373
#define nnodes
Definition: gastrans.c:74
SCIP_RETCODE SCIPtranslateSubSols(SCIP *scip, SCIP *subscip, SCIP_HEUR *heur, SCIP_VAR **subvars, SCIP_Bool *success, int *solindex)
Definition: scip_copy.c:1448
SCIP_RETCODE SCIPcheckCopyLimits(SCIP *sourcescip, SCIP_Bool *success)
Definition: scip_copy.c:3253
SCIP_RETCODE SCIPmergeVariableStatistics(SCIP *sourcescip, SCIP *targetscip, SCIP_VAR **sourcevars, SCIP_VAR **targetvars, int nvars)
Definition: scip_copy.c:1265
SCIP_RETCODE SCIPcopyLimits(SCIP *sourcescip, SCIP *targetscip)
Definition: scip_copy.c:3296
SCIP_Bool SCIPisStopped(SCIP *scip)
Definition: scip_general.c:734
SCIP_RETCODE SCIPfree(SCIP **scip)
Definition: scip_general.c:349
SCIP_RETCODE SCIPcreate(SCIP **scip)
Definition: scip_general.c:317
SCIP_RETCODE SCIPsetObjlimit(SCIP *scip, SCIP_Real objlimit)
Definition: scip_prob.c:1422
SCIP_RETCODE SCIPgetVarsData(SCIP *scip, SCIP_VAR ***vars, int *nvars, int *nbinvars, int *nintvars, int *nimplvars, int *ncontvars)
Definition: scip_prob.c:1866
void SCIPhashmapFree(SCIP_HASHMAP **hashmap)
Definition: misc.c:3111
void * SCIPhashmapGetImage(SCIP_HASHMAP *hashmap, void *origin)
Definition: misc.c:3264
SCIP_RETCODE SCIPhashmapCreate(SCIP_HASHMAP **hashmap, BMS_BLKMEM *blkmem, int mapsize)
Definition: misc.c:3077
#define SCIPdebugMsg
Definition: scip_message.h:78
SCIP_Bool SCIPisParamFixed(SCIP *scip, const char *name)
Definition: scip_param.c:219
SCIP_RETCODE SCIPaddIntParam(SCIP *scip, const char *name, const char *desc, int *valueptr, SCIP_Bool isadvanced, int defaultvalue, int minvalue, int maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:83
SCIP_RETCODE SCIPsetLongintParam(SCIP *scip, const char *name, SCIP_Longint value)
Definition: scip_param.c:545
SCIP_RETCODE SCIPaddRealParam(SCIP *scip, const char *name, const char *desc, SCIP_Real *valueptr, SCIP_Bool isadvanced, SCIP_Real defaultvalue, SCIP_Real minvalue, SCIP_Real maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:139
SCIP_RETCODE SCIPsetIntParam(SCIP *scip, const char *name, int value)
Definition: scip_param.c:487
SCIP_RETCODE SCIPsetSubscipsOff(SCIP *scip, SCIP_Bool quiet)
Definition: scip_param.c:904
SCIP_RETCODE SCIPsetPresolving(SCIP *scip, SCIP_PARAMSETTING paramsetting, SCIP_Bool quiet)
Definition: scip_param.c:953
SCIP_RETCODE SCIPsetCharParam(SCIP *scip, const char *name, char value)
Definition: scip_param.c:661
SCIP_RETCODE SCIPaddBoolParam(SCIP *scip, const char *name, const char *desc, SCIP_Bool *valueptr, SCIP_Bool isadvanced, SCIP_Bool defaultvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:57
SCIP_RETCODE SCIPsetBoolParam(SCIP *scip, const char *name, SCIP_Bool value)
Definition: scip_param.c:429
SCIP_RETCODE SCIPsetSeparating(SCIP *scip, SCIP_PARAMSETTING paramsetting, SCIP_Bool quiet)
Definition: scip_param.c:979
SCIP_RETCODE SCIPincludeHeurRins(SCIP *scip)
Definition: heur_rins.c:580
SCIP_BRANCHRULE * SCIPfindBranchrule(SCIP *scip, const char *name)
Definition: scip_branch.c:297
SCIP_RETCODE SCIPincludeEventhdlrBasic(SCIP *scip, SCIP_EVENTHDLR **eventhdlrptr, const char *name, const char *desc, SCIP_DECL_EVENTEXEC((*eventexec)), SCIP_EVENTHDLRDATA *eventhdlrdata)
Definition: scip_event.c:104
const char * SCIPeventhdlrGetName(SCIP_EVENTHDLR *eventhdlr)
Definition: event.c:324
SCIP_EVENTTYPE SCIPeventGetType(SCIP_EVENT *event)
Definition: event.c:1030
SCIP_RETCODE SCIPcatchEvent(SCIP *scip, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int *filterpos)
Definition: scip_event.c:286
SCIP_RETCODE SCIPdropEvent(SCIP *scip, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int filterpos)
Definition: scip_event.c:320
SCIP_RETCODE SCIPsetHeurCopy(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURCOPY((*heurcopy)))
Definition: scip_heur.c:162
SCIP_HEURDATA * SCIPheurGetData(SCIP_HEUR *heur)
Definition: heur.c:1364
SCIP_RETCODE SCIPincludeHeurBasic(SCIP *scip, SCIP_HEUR **heur, const char *name, const char *desc, char dispchar, int priority, int freq, int freqofs, int maxdepth, SCIP_HEURTIMING timingmask, SCIP_Bool usessubscip, SCIP_DECL_HEUREXEC((*heurexec)), SCIP_HEURDATA *heurdata)
Definition: scip_heur.c:117
SCIP_RETCODE SCIPsetHeurFree(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURFREE((*heurfree)))
Definition: scip_heur.c:178
SCIP_Longint SCIPheurGetNBestSolsFound(SCIP_HEUR *heur)
Definition: heur.c:1599
SCIP_Longint SCIPheurGetNCalls(SCIP_HEUR *heur)
Definition: heur.c:1579
SCIP_RETCODE SCIPsetHeurInit(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURINIT((*heurinit)))
Definition: scip_heur.c:194
const char * SCIPheurGetName(SCIP_HEUR *heur)
Definition: heur.c:1453
void SCIPheurSetData(SCIP_HEUR *heur, SCIP_HEURDATA *heurdata)
Definition: heur.c:1374
SCIP_Bool SCIPhasCurrentNodeLP(SCIP *scip)
Definition: scip_lp.c:83
SCIP_LPSOLSTAT SCIPgetLPSolstat(SCIP *scip)
Definition: scip_lp.c:168
SCIP_Real SCIPgetLPObjval(SCIP *scip)
Definition: scip_lp.c:247
#define SCIPallocBufferArray(scip, ptr, num)
Definition: scip_mem.h:124
#define SCIPfreeBufferArray(scip, ptr)
Definition: scip_mem.h:136
#define SCIPfreeBlockMemory(scip, ptr)
Definition: scip_mem.h:108
#define SCIPallocBlockMemory(scip, ptr)
Definition: scip_mem.h:89
SCIP_NODESEL * SCIPfindNodesel(SCIP *scip, const char *name)
Definition: scip_nodesel.c:234
SCIP_SOL * SCIPgetBestSol(SCIP *scip)
Definition: scip_sol.c:2165
int SCIPgetNSols(SCIP *scip)
Definition: scip_sol.c:2066
SCIP_Bool SCIPsolIsOriginal(SCIP_SOL *sol)
Definition: sol.c:2721
SCIP_Longint SCIPgetSolNodenum(SCIP *scip, SCIP_SOL *sol)
Definition: scip_sol.c:1509
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1213
SCIP_RETCODE SCIPtransformProb(SCIP *scip)
Definition: scip_solve.c:223
SCIP_RETCODE SCIPinterruptSolve(SCIP *scip)
Definition: scip_solve.c:3436
SCIP_RETCODE SCIPsolve(SCIP *scip)
Definition: scip_solve.c:2502
SCIP_Real SCIPgetUpperbound(SCIP *scip)
SCIP_Longint SCIPgetNNodes(SCIP *scip)
SCIP_RETCODE SCIPprintStatistics(SCIP *scip, FILE *file)
SCIP_Real SCIPgetLowerbound(SCIP *scip)
SCIP_Longint SCIPgetNLPs(SCIP *scip)
SCIP_Real SCIPgetCutoffbound(SCIP *scip)
SCIP_RETCODE SCIPcopyLargeNeighborhoodSearch(SCIP *sourcescip, SCIP *subscip, SCIP_HASHMAP *varmap, const char *suffix, SCIP_VAR **fixedvars, SCIP_Real *fixedvals, int nfixedvars, SCIP_Bool uselprows, SCIP_Bool copycuts, SCIP_Bool *success, SCIP_Bool *valid)
Definition: heuristics.c:951
SCIP_Bool SCIPisGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisInfinity(SCIP *scip, SCIP_Real val)
SCIP_Real SCIPsumepsilon(SCIP *scip)
SCIP_Real SCIPvarGetLPSol(SCIP_VAR *var)
Definition: var.c:18451
#define DEFAULT_NODESQUOT
Definition: heur_rins.c:75
#define DEFAULT_NWAITINGNODES
Definition: heur_rins.c:77
static SCIP_DECL_HEUREXEC(heurExecRins)
Definition: heur_rins.c:456
#define DEFAULT_NODESOFS
Definition: heur_rins.c:70
#define DEFAULT_COPYCUTS
Definition: heur_rins.c:79
#define DEFAULT_MAXNODES
Definition: heur_rins.c:71
static SCIP_RETCODE determineFixings(SCIP *scip, SCIP_VAR **fixedvars, SCIP_Real *fixedvals, int *nfixedvars, int fixedvarssize, SCIP_Real minfixingrate, SCIP_Bool *success)
Definition: heur_rins.c:123
#define HEUR_TIMING
Definition: heur_rins.c:67
#define DEFAULT_MINNODES
Definition: heur_rins.c:72
#define HEUR_FREQOFS
Definition: heur_rins.c:65
#define HEUR_DESC
Definition: heur_rins.c:61
#define DEFAULT_LPLIMFAC
Definition: heur_rins.c:76
#define DEFAULT_MINFIXINGRATE
Definition: heur_rins.c:74
#define DEFAULT_USEUCT
Definition: heur_rins.c:80
static SCIP_RETCODE wrapperRins(SCIP *scip, SCIP *subscip, SCIP_HEUR *heur, SCIP_HEURDATA *heurdata, SCIP_VAR **vars, SCIP_VAR **fixedvars, SCIP_Real *fixedvals, SCIP_RESULT *result, int nvars, int nfixedvars, SCIP_Longint nnodes)
Definition: heur_rins.c:203
#define HEUR_DISPCHAR
Definition: heur_rins.c:62
#define HEUR_MAXDEPTH
Definition: heur_rins.c:66
#define HEUR_PRIORITY
Definition: heur_rins.c:63
#define DEFAULT_MINIMPROVE
Definition: heur_rins.c:73
#define HEUR_NAME
Definition: heur_rins.c:60
#define DEFAULT_USELPROWS
Definition: heur_rins.c:78
static SCIP_DECL_HEURFREE(heurFreeRins)
Definition: heur_rins.c:415
static SCIP_DECL_EVENTEXEC(eventExecRins)
Definition: heur_rins.c:371
#define EVENTHDLR_DESC
Definition: heur_rins.c:84
#define HEUR_FREQ
Definition: heur_rins.c:64
#define HEUR_USESSUBSCIP
Definition: heur_rins.c:68
static SCIP_DECL_HEURCOPY(heurCopyRins)
Definition: heur_rins.c:401
#define EVENTHDLR_NAME
Definition: heur_rins.c:83
static SCIP_DECL_HEURINIT(heurInitRins)
Definition: heur_rins.c:436
LNS heuristic that combines the incumbent with the LP optimum.
methods commonly used by primal heuristics
memory allocation routines
BMS_BLKMEM * SCIPblkmem(SCIP *scip)
Definition: scip_mem.c:57
public methods for managing events
public methods for primal heuristics
public methods for message output
#define SCIPerrorMessage
Definition: pub_message.h:64
#define SCIPdebug(x)
Definition: pub_message.h:93
public data structures and miscellaneous methods
public methods for primal CIP solutions
public methods for problem variables
public methods for branching rule plugins and branching
public methods for constraint handler plugins and constraints
public methods for problem copies
public methods for event handler plugins and event handlers
general public methods
public methods for primal heuristic plugins and divesets
public methods for the LP relaxation, rows and columns
public methods for memory management
public methods for message handling
public methods for node selector plugins
public methods for numerical tolerances
public methods for SCIP parameter handling
public methods for global and local (sub)problems
public methods for solutions
public solving methods
public methods for querying solving statistics
struct SCIP_EventData SCIP_EVENTDATA
Definition: type_event.h:173
#define SCIP_EVENTTYPE_LPSOLVED
Definition: type_event.h:101
struct SCIP_HeurData SCIP_HEURDATA
Definition: type_heur.h:77
@ SCIP_LPSOLSTAT_OPTIMAL
Definition: type_lp.h:43
@ SCIP_VERBLEVEL_NONE
Definition: type_message.h:52
@ SCIP_VERBLEVEL_FULL
Definition: type_message.h:57
@ SCIP_PARAMSETTING_OFF
Definition: type_paramset.h:63
@ SCIP_PARAMSETTING_FAST
Definition: type_paramset.h:62
@ SCIP_DIDNOTRUN
Definition: type_result.h:42
@ SCIP_DELAYED
Definition: type_result.h:43
@ SCIP_DIDNOTFIND
Definition: type_result.h:44
@ SCIP_FOUNDSOL
Definition: type_result.h:56
enum SCIP_Result SCIP_RESULT
Definition: type_result.h:61
@ SCIP_PLUGINNOTFOUND
Definition: type_retcode.h:54
@ SCIP_OKAY
Definition: type_retcode.h:42
enum SCIP_Retcode SCIP_RETCODE
Definition: type_retcode.h:63