Scippy

SCIP

Solving Constraint Integer Programs

sepa_eccuts.c
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1/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
2/* */
3/* This file is part of the program and library */
4/* SCIP --- Solving Constraint Integer Programs */
5/* */
6/* Copyright (c) 2002-2024 Zuse Institute Berlin (ZIB) */
7/* */
8/* Licensed under the Apache License, Version 2.0 (the "License"); */
9/* you may not use this file except in compliance with the License. */
10/* You may obtain a copy of the License at */
11/* */
12/* http://www.apache.org/licenses/LICENSE-2.0 */
13/* */
14/* Unless required by applicable law or agreed to in writing, software */
15/* distributed under the License is distributed on an "AS IS" BASIS, */
16/* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. */
17/* See the License for the specific language governing permissions and */
18/* limitations under the License. */
19/* */
20/* You should have received a copy of the Apache-2.0 license */
21/* along with SCIP; see the file LICENSE. If not visit scipopt.org. */
22/* */
23/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
24
25/**@file sepa_eccuts.c
26 * @ingroup DEFPLUGINS_SEPA
27 * @brief edge concave cut separator
28 * @author Benjamin Mueller
29 */
30
31/**@todo only count number of fixed variables in the edge concave terms */
32/**@todo only add nonlinear row aggregations where at least ...% of the variables (bilinear terms?) are in edge concave
33 * terms */
34/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
35
36#include <assert.h>
37#include <string.h>
38
39#include "scip/scipdefplugins.h"
40#include "scip/sepa_eccuts.h"
41#include "scip/cons_xor.h"
42#include "scip/nlp.h"
43#include "tclique/tclique.h"
44
45#define SEPA_NAME "eccuts"
46#define SEPA_DESC "separator for edge-concave functions"
47#define SEPA_PRIORITY -13000
48#define SEPA_FREQ -1
49#define SEPA_MAXBOUNDDIST 1.0
50#define SEPA_USESSUBSCIP FALSE /**< does the separator use a secondary SCIP instance? */
51#define SEPA_DELAY FALSE /**< should separation method be delayed, if other separators found cuts? */
52
53#define CLIQUE_MAXFIRSTNODEWEIGHT 1000 /**< maximum weight of branching nodes in level 0; 0 if not used for cliques
54 * with at least one fractional node) */
55#define CLIQUE_MINWEIGHT 0 /**< lower bound for weight of generated cliques */
56#define CLIQUE_MAXNTREENODES 10000 /**< maximal number of nodes of b&b tree */
57#define CLIQUE_BACKTRACKFREQ 10000 /**< frequency to backtrack to first level of tree (0: no premature backtracking) */
58
59#define DEFAULT_DYNAMICCUTS TRUE /**< should generated cuts be removed from the LP if they are no longer tight? */
60#define DEFAULT_MAXROUNDS 10 /**< maximal number of separation rounds per node (-1: unlimited) */
61#define DEFAULT_MAXROUNDSROOT 250 /**< maximal number of separation rounds in the root node (-1: unlimited) */
62#define DEFAULT_MAXDEPTH -1 /**< maximal depth at which the separator is applied */
63#define DEFAULT_MAXSEPACUTS 10 /**< maximal number of e.c. cuts separated per separation round */
64#define DEFAULT_MAXSEPACUTSROOT 50 /**< maximal number of e.c. cuts separated per separation round in root node */
65#define DEFAULT_CUTMAXRANGE 1e+7 /**< maximal coefficient range of a cut (maximal coefficient divided by minimal
66 * coefficient) in order to be added to LP relaxation */
67#define DEFAULT_MINVIOLATION 0.3 /**< minimal violation of an e.c. cut to be separated */
68#define DEFAULT_MINAGGRSIZE 3 /**< search for e.c. aggregation of at least this size (has to be >= 3) */
69#define DEFAULT_MAXAGGRSIZE 4 /**< search for e.c. aggregation of at most this size (has to be >= minaggrsize) */
70#define DEFAULT_MAXBILINTERMS 500 /**< maximum number of bilinear terms allowed to be in a quadratic constraint */
71#define DEFAULT_MAXSTALLROUNDS 5 /**< maximum number of unsuccessful rounds in the e.c. aggregation search */
72
73#define SUBSCIP_NODELIMIT 100LL /**< node limit to solve the sub-SCIP */
74
75#define ADJUSTFACETTOL 1e-6 /**< adjust resulting facets in checkRikun() up to a violation of this value */
76#define USEDUALSIMPLEX TRUE /**< use dual or primal simplex algorithm? */
77
78/** first values for \f$2^n\f$ */
79static const int poweroftwo[] = { 1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 4096, 8192 };
80
81/*
82 * Data structures
83 */
84
85/** data to store a single edge-concave aggregations; an edge-concave aggregation of a quadratic constraint is a subset
86 * of nonconvex bilinear terms
87 */
88struct EcAggr
89{
90 SCIP_VAR** vars; /**< variables */
91 int nvars; /**< number of variables */
92 int varsize; /**< size of vars array */
93
94 SCIP_Real* termcoefs; /**< coefficients of bilinear terms */
95 int* termvars1; /**< index of the first variable of each bilinear term */
96 int* termvars2; /**< index of the second variable of each bilinear term*/
97 int nterms; /**< number of bilinear terms in the aggregation */
98 int termsize; /**< size of term{coefs,vars1,vars2} arrays */
99};
100typedef struct EcAggr SCIP_ECAGGR;
101
102/** data to store all edge-concave aggregations and the remaining part of a nonlinear row of the form g(x) <= rhs */
104{
105 SCIP_NLROW* nlrow; /**< nonlinear row aggregation */
106 SCIP_Bool rhsaggr; /**< consider nonlinear row aggregation for g(x) <= rhs (TRUE) or
107 * g(x) >= lhs (FALSE) */
108
109 SCIP_ECAGGR** ecaggr; /**< array with all edge-concave aggregations */
110 int necaggr; /**< number of edge-concave aggregation */
111
112 SCIP_VAR** linvars; /**< linear variables */
113 SCIP_Real* lincoefs; /**< linear coefficients */
114 int nlinvars; /**< number of linear variables */
115 int linvarssize; /**< size of linvars array */
116
117 SCIP_VAR** quadvars; /**< quadratic variables */
118 int* quadvar2aggr; /**< stores in which edge-concave aggregation the i-th quadratic variable
119 * is contained (< 0: in no edge-concave aggregation) */
120 int nquadvars; /**< number of quadratic variables */
121 int quadvarssize; /**< size of quadvars array */
122
123 SCIP_VAR** remtermvars1; /**< first quadratic variable of remaining bilinear terms */
124 SCIP_VAR** remtermvars2; /**< second quadratic variable of remaining bilinear terms */
125 SCIP_Real* remtermcoefs; /**< coefficients for each remaining bilinear term */
126 int nremterms; /**< number of remaining bilinear terms */
127 int remtermsize; /**< size of remterm* arrays */
128
129 SCIP_Real rhs; /**< rhs of the nonlinear row */
130 SCIP_Real constant; /**< constant part of the nonlinear row */
131};
133
134/** separator data */
135struct SCIP_SepaData
136{
137 SCIP_NLROWAGGR** nlrowaggrs; /**< array containing all nonlinear row aggregations */
138 int nnlrowaggrs; /**< number of nonlinear row aggregations */
139 int nlrowaggrssize; /**< size of nlrowaggrs array */
140 SCIP_Bool searchedforaggr; /**< flag if we already searched for nlrow aggregation candidates */
141 int minaggrsize; /**< only search for e.c. aggregations of at least this size (has to be >= 3) */
142 int maxaggrsize; /**< only search for e.c. aggregations of at most this size (has to be >= minaggrsize) */
143 int maxecsize; /**< largest edge concave aggregation size */
144 int maxbilinterms; /**< maximum number of bilinear terms allowed to be in a quadratic constraint */
145 int maxstallrounds; /**< maximum number of unsuccessful rounds in the e.c. aggregation search */
146
147 SCIP_LPI* lpi; /**< LP interface to solve the LPs to compute the facets of the convex envelopes */
148 int lpisize; /**< maximum size of e.c. aggregations which can be handled by the LP interface */
149
150 SCIP_Real cutmaxrange; /**< maximal coef range of a cut (maximal coefficient divided by minimal
151 * coefficient) in order to be added to LP relaxation */
152 SCIP_Bool dynamiccuts; /**< should generated cuts be removed from the LP if they are no longer tight? */
153 SCIP_Real minviolation; /**< minimal violation of an e.c. cut to be separated */
154
155 int maxrounds; /**< maximal number of separation rounds per node (-1: unlimited) */
156 int maxroundsroot; /**< maximal number of separation rounds in the root node (-1: unlimited) */
157 int maxdepth; /**< maximal depth at which the separator is applied */
158 int maxsepacuts; /**< maximal number of e.c. cuts separated per separation round */
159 int maxsepacutsroot; /**< maximal number of e.c. cuts separated per separation round in root node */
160
161#ifdef SCIP_STATISTIC
162 SCIP_Real aggrsearchtime; /**< total time spent for searching edge concave aggregations */
163 int nlhsnlrowaggrs; /**< number of found nonlinear row aggregations for SCIP_NLROWs of the form g(x) <= rhs */
164 int nrhsnlrowaggrs; /**< number of found nonlinear row aggregations for SCIP_NLROWs of the form g(x) >= lhs */
165#endif
166};
167
168
169/*
170 * Local methods
171 */
172
173/** creates an empty edge-concave aggregation (without bilinear terms) */
174static
176 SCIP* scip, /**< SCIP data structure */
177 SCIP_ECAGGR** ecaggr, /**< pointer to store the edge-concave aggregation */
178 int nquadvars, /**< number of quadratic variables */
179 int nquadterms /**< number of bilinear terms */
180 )
181{
182 assert(scip != NULL);
183 assert(ecaggr != NULL);
184 assert(nquadvars > 0);
185 assert(nquadterms >= nquadvars);
186
188
189 (*ecaggr)->nvars = 0;
190 (*ecaggr)->nterms = 0;
191 (*ecaggr)->varsize = nquadvars;
192 (*ecaggr)->termsize = nquadterms;
193
194 /* allocate enough memory for the quadratic variables and bilinear terms */
195 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*ecaggr)->vars, nquadvars) );
196 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*ecaggr)->termcoefs, nquadterms) );
197 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*ecaggr)->termvars1, nquadterms) );
198 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*ecaggr)->termvars2, nquadterms) );
199
200 return SCIP_OKAY;
201}
202
203/** frees an edge-concave aggregation */
204static
206 SCIP* scip, /**< SCIP data structure */
207 SCIP_ECAGGR** ecaggr /**< pointer to store the edge-concave aggregation */
208 )
209{
210 assert(scip != NULL);
211 assert(ecaggr != NULL);
212
213 SCIPfreeBlockMemoryArray(scip, &((*ecaggr)->termcoefs), (*ecaggr)->termsize);
214 SCIPfreeBlockMemoryArray(scip, &((*ecaggr)->termvars1), (*ecaggr)->termsize);
215 SCIPfreeBlockMemoryArray(scip, &((*ecaggr)->termvars2), (*ecaggr)->termsize);
216 SCIPfreeBlockMemoryArray(scip, &((*ecaggr)->vars), (*ecaggr)->varsize);
217
218 SCIPfreeBlockMemory(scip, ecaggr);
219 *ecaggr = NULL;
220
221 return SCIP_OKAY;
222}
223
224/** adds a quadratic variable to an edge-concave aggregation */
225static
227 SCIP_ECAGGR* ecaggr, /**< pointer to store the edge-concave aggregation */
228 SCIP_VAR* x /**< first variable */
229 )
230{
231 ecaggr->vars[ ecaggr->nvars++ ] = x;
232 return SCIP_OKAY;
233}
234
235/** adds a bilinear term to an edge-concave aggregation */
236static
238 SCIP* scip, /**< SCIP data structure */
239 SCIP_ECAGGR* ecaggr, /**< pointer to store the edge-concave aggregation */
240 SCIP_VAR* x, /**< first variable */
241 SCIP_VAR* y, /**< second variable */
242 SCIP_Real coef /**< bilinear coefficient */
243 )
244{
245 int idx1;
246 int idx2;
247 int i;
248
249 assert(x != NULL);
250 assert(y != NULL);
251 assert(ecaggr->nterms + 1 <= ((ecaggr->nvars + 1) * ecaggr->nvars) / 2);
252 assert(!SCIPisZero(scip, coef));
253
254 idx1 = -1;
255 idx2 = -1;
256
257 /* search for the quadratic variables in the e.c. aggregation */
258 for( i = 0; i < ecaggr->nvars && (idx1 == -1 || idx2 == -1); ++i )
259 {
260 if( ecaggr->vars[i] == x )
261 idx1 = i;
262 if( ecaggr->vars[i] == y )
263 idx2 = i;
264 }
265
266 assert(idx1 != -1 && idx2 != -1);
267
268 ecaggr->termcoefs[ ecaggr->nterms ] = coef;
269 ecaggr->termvars1[ ecaggr->nterms ] = idx1;
270 ecaggr->termvars2[ ecaggr->nterms ] = idx2;
271 ++(ecaggr->nterms);
272
273 return SCIP_OKAY;
274}
275
276#ifdef SCIP_DEBUG
277/** prints an edge-concave aggregation */
278static
279void ecaggrPrint(
280 SCIP* scip, /**< SCIP data structure */
281 SCIP_ECAGGR* ecaggr /**< pointer to store the edge-concave aggregation */
282 )
283{
284 int i;
285
286 assert(scip != NULL);
287 assert(ecaggr != NULL);
288
289 SCIPdebugMsg(scip, " nvars = %d nterms = %d\n", ecaggr->nvars, ecaggr->nterms);
290 SCIPdebugMsg(scip, " vars: ");
291 for( i = 0; i < ecaggr->nvars; ++i )
292 SCIPdebugMsgPrint(scip, "%s ", SCIPvarGetName(ecaggr->vars[i]));
293 SCIPdebugMsgPrint(scip, "\n");
294
295 SCIPdebugMsg(scip, " terms: ");
296 for( i = 0; i < ecaggr->nterms; ++i )
297 {
298 SCIP_VAR* x;
299 SCIP_VAR* y;
300
301 x = ecaggr->vars[ ecaggr->termvars1[i] ];
302 y = ecaggr->vars[ ecaggr->termvars2[i] ];
303 SCIPdebugMsgPrint(scip, "%e %s * %s ", ecaggr->termcoefs[i], SCIPvarGetName(x), SCIPvarGetName(y) );
304 }
305 SCIPdebugMsgPrint(scip, "\n");
306}
307#endif
308
309/** stores linear terms in a given nonlinear row aggregation */
310static
312 SCIP* scip, /**< SCIP data structure */
313 SCIP_NLROWAGGR* nlrowaggr, /**< nonlinear row aggregation */
314 SCIP_VAR** linvars, /**< linear variables */
315 SCIP_Real* lincoefs, /**< linear coefficients */
316 int nlinvars /**< number of linear variables */
317 )
318{
319 assert(scip != NULL);
320 assert(nlrowaggr != NULL);
321 assert(linvars != NULL || nlinvars == 0);
322 assert(lincoefs != NULL || nlinvars == 0);
323 assert(nlinvars >= 0);
324
325 nlrowaggr->nlinvars = 0;
326 nlrowaggr->linvarssize = 0;
327 nlrowaggr->linvars = NULL;
328 nlrowaggr->lincoefs = NULL;
329
330 if( nlinvars == 0 )
331 return SCIP_OKAY;
332
333 SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &nlrowaggr->linvars, linvars, nlinvars) );
334 SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &nlrowaggr->lincoefs, lincoefs, nlinvars) );
335 nlrowaggr->nlinvars = nlinvars;
336 nlrowaggr->linvarssize = nlinvars;
337
338 /* if we have a nlrow of the form g(x) >= lhs, multiply every coefficient by -1 */
339 if( !nlrowaggr->rhsaggr )
340 {
341 int i;
342
343 for( i = 0; i < nlrowaggr->nlinvars; ++i )
344 nlrowaggr->lincoefs[i] *= -1.0;
345 }
346
347 return SCIP_OKAY;
348}
349
350/** adds linear term to a given nonlinear row aggregation */
351static
353 SCIP* scip, /**< SCIP data structure */
354 SCIP_NLROWAGGR* nlrowaggr, /**< nonlinear row aggregation */
355 SCIP_VAR* linvar, /**< linear variable */
356 SCIP_Real lincoef /**< coefficient */
357 )
358{
359 assert(scip != NULL);
360 assert(nlrowaggr != NULL);
361 assert(linvar != NULL);
362
363 if( nlrowaggr->nlinvars == nlrowaggr->linvarssize )
364 {
365 int newsize = SCIPcalcMemGrowSize(scip, nlrowaggr->linvarssize+1);
366 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &nlrowaggr->linvars, nlrowaggr->linvarssize, newsize) );
367 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &nlrowaggr->lincoefs, nlrowaggr->linvarssize, newsize) );
368 nlrowaggr->linvarssize = newsize;
369 }
370 assert(nlrowaggr->linvarssize > nlrowaggr->nlinvars);
371
372 /* if we have a nlrow of the form g(x) >= lhs, multiply coefficient by -1 */
373 if( !nlrowaggr->rhsaggr )
374 lincoef = -lincoef;
375
376 nlrowaggr->linvars[nlrowaggr->nlinvars] = linvar;
377 nlrowaggr->lincoefs[nlrowaggr->nlinvars] = lincoef;
378 ++nlrowaggr->nlinvars;
379
380 return SCIP_OKAY;
381}
382
383/** adds quadratic variable to a given nonlinear row aggregation */
384static
386 SCIP* scip, /**< SCIP data structure */
387 SCIP_NLROWAGGR* nlrowaggr, /**< nonlinear row aggregation */
388 SCIP_VAR* quadvar /**< quadratic variable */
389 )
390{
391 assert(scip != NULL);
392 assert(nlrowaggr != NULL);
393 assert(quadvar != NULL);
394
395 SCIP_CALL( SCIPensureBlockMemoryArray(scip, &nlrowaggr->quadvars, &nlrowaggr->quadvarssize, nlrowaggr->nquadvars+1) );
396 assert(nlrowaggr->quadvarssize > nlrowaggr->nquadvars);
397 nlrowaggr->quadvars[nlrowaggr->nquadvars] = quadvar;
398 ++nlrowaggr->nquadvars;
399
400 return SCIP_OKAY;
401}
402
403/** adds a remaining bilinear term to a given nonlinear row aggregation */
404static
406 SCIP_NLROWAGGR* nlrowaggr, /**< nonlinear row aggregation */
407 SCIP_VAR* x, /**< first variable */
408 SCIP_VAR* y, /**< second variable */
409 SCIP_Real coef /**< bilinear coefficient */
410 )
411{
412 assert(nlrowaggr != NULL);
413 assert(x != NULL);
414 assert(y != NULL);
415 assert(coef != 0.0);
416 assert(nlrowaggr->remtermcoefs != NULL);
417 assert(nlrowaggr->remtermvars1 != NULL);
418 assert(nlrowaggr->remtermvars2 != NULL);
419
420 nlrowaggr->remtermcoefs[ nlrowaggr->nremterms ] = coef;
421 nlrowaggr->remtermvars1[ nlrowaggr->nremterms ] = x;
422 nlrowaggr->remtermvars2[ nlrowaggr->nremterms ] = y;
423 ++(nlrowaggr->nremterms);
424
425 return SCIP_OKAY;
426}
427
428/** creates a nonlinear row aggregation */
429static
431 SCIP* scip, /**< SCIP data structure */
432 SCIP_NLROW* nlrow, /**< nonlinear row */
433 SCIP_NLROWAGGR** nlrowaggr, /**< pointer to store the nonlinear row aggregation */
434 int* quadvar2aggr, /**< mapping between quadratic variables and edge-concave aggregation
435 * stores a negative value if the quadratic variables does not belong
436 * to any aggregation */
437 int nfound, /**< number of edge-concave aggregations */
438 SCIP_Bool rhsaggr /**< consider nonlinear row aggregation for g(x) <= rhs (TRUE) or
439 * lhs <= g(x) (FALSE) */
440 )
441{
442 SCIP_EXPR* expr;
443 int* aggrnvars; /* count the number of variables in each e.c. aggregations */
444 int* aggrnterms; /* count the number of bilinear terms in each e.c. aggregations */
445 int nquadvars;
446 int nremterms;
447 int i;
448
449 assert(scip != NULL);
450 assert(nlrow != NULL);
451 assert(nlrowaggr != NULL);
452 assert(quadvar2aggr != NULL);
453 assert(nfound > 0);
454
455 expr = SCIPnlrowGetExpr(nlrow);
456 SCIPexprGetQuadraticData(expr, NULL, NULL, NULL, NULL, &nquadvars, NULL, NULL, NULL);
457 nremterms = 0;
458
459 SCIP_CALL( SCIPallocClearBufferArray(scip, &aggrnvars, nfound) );
460 SCIP_CALL( SCIPallocClearBufferArray(scip, &aggrnterms, nfound) );
461
462 /* create an empty nonlinear row aggregation */
463 SCIP_CALL( SCIPallocBlockMemory(scip, nlrowaggr) );
464 (*nlrowaggr)->nlrow = nlrow;
465 (*nlrowaggr)->rhsaggr = rhsaggr;
466 (*nlrowaggr)->rhs = rhsaggr ? SCIPnlrowGetRhs(nlrow) : -SCIPnlrowGetLhs(nlrow);
467 (*nlrowaggr)->constant = rhsaggr ? SCIPnlrowGetConstant(nlrow) : -SCIPnlrowGetConstant(nlrow);
468
469 (*nlrowaggr)->quadvars = NULL;
470 (*nlrowaggr)->nquadvars = 0;
471 (*nlrowaggr)->quadvarssize = 0;
472 (*nlrowaggr)->quadvar2aggr = NULL;
473 (*nlrowaggr)->remtermcoefs = NULL;
474 (*nlrowaggr)->remtermvars1 = NULL;
475 (*nlrowaggr)->remtermvars2 = NULL;
476 (*nlrowaggr)->nremterms = 0;
477
478 /* copy quadvar2aggr array */
479 SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*nlrowaggr)->quadvar2aggr, quadvar2aggr, nquadvars) );
480
481 /* store all linear terms */
483 SCIPnlrowGetNLinearVars(nlrow)) );
484
485 /* store all quadratic variables and additional linear terms */
486 /* count the number of variables in each e.c. aggregation */
487 /* count the number of square and bilinear terms in each e.c. aggregation */
488 for( i = 0; i < nquadvars; ++i )
489 {
490 SCIP_EXPR* qterm;
491 SCIP_Real lincoef;
492 SCIP_Real sqrcoef;
493 int idx1;
494 int nadjbilin;
495 int* adjbilin;
496 int j;
497
498 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, &lincoef, &sqrcoef, &nadjbilin, &adjbilin, NULL);
499 assert(SCIPisExprVar(scip, qterm));
500
502
503 if( lincoef != 0.0 )
504 {
505 SCIP_CALL( nlrowaggrAddLinearTerm(scip, *nlrowaggr, SCIPgetVarExprVar(qterm), lincoef) );
506 }
507
508 if( quadvar2aggr[i] >= 0)
509 ++aggrnvars[ quadvar2aggr[i] ];
510
511 idx1 = quadvar2aggr[i];
512 if( rhsaggr )
513 sqrcoef = -sqrcoef;
514
515 /* variable has to belong to an e.c. aggregation; square term has to be concave */
516 if( idx1 >= 0 && SCIPisNegative(scip, sqrcoef) )
517 ++aggrnterms[idx1];
518 else
519 ++nremterms;
520
521 for( j = 0; j < nadjbilin; ++j )
522 {
523 SCIP_EXPR* qterm1;
524 int pos2;
525 int idx2;
526
527 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, NULL, NULL, &pos2, NULL);
528
529 /* only handle qterm1 == qterm here; the other case will be handled when its turn for qterm2 to be qterm */
530 if( qterm1 != qterm )
531 continue;
532
533 idx2 = quadvar2aggr[pos2];
534
535 /* variables have to belong to the same e.c. aggregation; bilinear term has to be concave */
536 if( idx1 >= 0 && idx2 >= 0 && idx1 == idx2 )
537 ++aggrnterms[idx1];
538 else
539 ++nremterms;
540 }
541 }
542 assert((*nlrowaggr)->nquadvars == nquadvars);
543
544 /* create all edge-concave aggregations (empty) and remaining terms */
545 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*nlrowaggr)->ecaggr, nfound) );
546 if( nremterms > 0 )
547 {
548 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*nlrowaggr)->remtermcoefs, nremterms) );
549 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*nlrowaggr)->remtermvars1, nremterms) );
550 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*nlrowaggr)->remtermvars2, nremterms) );
551 (*nlrowaggr)->remtermsize = nremterms;
552 }
553 (*nlrowaggr)->necaggr = nfound;
554
555 for( i = 0; i < nfound; ++i )
556 {
557 SCIP_CALL( ecaggrCreateEmpty(scip, &(*nlrowaggr)->ecaggr[i], aggrnvars[i], aggrnterms[i]) );
558 }
559
560 /* add quadratic variables to the edge-concave aggregations */
561 for( i = 0; i < nquadvars; ++i )
562 {
563 int idx;
564
565 idx = quadvar2aggr[i];
566
567 if( idx >= 0)
568 {
569 SCIP_EXPR* qterm;
570
571 SCIPdebugMsg(scip, "add quadvar %d to aggr. %d\n", i, idx);
572
573 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, NULL, NULL, NULL, NULL);
574 assert(SCIPisExprVar(scip, qterm));
575
576 SCIP_CALL( ecaggrAddQuadvar((*nlrowaggr)->ecaggr[idx], SCIPgetVarExprVar(qterm)) );
577 }
578 }
579
580 /* add the bilinear/square terms to the edge-concave aggregations or in the remaining part */
581 for( i = 0; i < nquadvars; ++i )
582 {
583 SCIP_EXPR* qterm;
584 SCIP_VAR* x;
585 SCIP_Real coef;
586 int idx1;
587 int nadjbilin;
588 int* adjbilin;
589 int j;
590
591 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, &coef, &nadjbilin, &adjbilin, NULL);
592
593 x = SCIPgetVarExprVar(qterm);
594
595 idx1 = quadvar2aggr[i];
596 if( rhsaggr )
597 coef = -coef;
598
599 if( idx1 >= 0 && SCIPisNegative(scip, coef) )
600 {
601 SCIP_CALL( ecaggrAddBilinTerm(scip, (*nlrowaggr)->ecaggr[idx1], x, x, coef) );
602 SCIPdebugMsg(scip, "add term %e *%d^2 to aggr. %d\n", coef, i, idx1);
603 }
604 else
605 {
606 SCIP_CALL( nlrowaggrAddRemBilinTerm(*nlrowaggr, x, x, coef) );
607 SCIPdebugMsg(scip, "add term %e *%d^2 to the remaining part\n", coef, idx1);
608 }
609
610 for( j = 0; j < nadjbilin; ++j )
611 {
612 SCIP_EXPR* qterm1;
613 SCIP_EXPR* qterm2;
614 int pos2;
615 int idx2;
616 SCIP_VAR* y;
617
618 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, &qterm2, &coef, &pos2, NULL);
619
620 /* only handle qterm1 == qterm here; the other case will be handled when its turn for qterm2 to be qterm */
621 if( qterm1 != qterm )
622 continue;
623
624 y = SCIPgetVarExprVar(qterm2);
625
626 idx2 = quadvar2aggr[pos2];
627 if( rhsaggr )
628 coef = -coef;
629
630 if( idx1 >= 0 && idx2 >= 0 && idx1 == idx2 )
631 {
632 SCIP_CALL( ecaggrAddBilinTerm(scip, (*nlrowaggr)->ecaggr[idx1], x, y, coef) );
633 SCIPdebugMsg(scip, "add term %e *%d*%d to aggr. %d\n", coef, i, pos2, idx1);
634 }
635 else
636 {
637 SCIP_CALL( nlrowaggrAddRemBilinTerm(*nlrowaggr, x, y, coef) );
638 SCIPdebugMsg(scip, "add term %e *%d*%d to the remaining part\n", coef, i, pos2);
639 }
640 }
641 }
642
643 /* free allocated memory */
644 SCIPfreeBufferArray(scip, &aggrnterms);
645 SCIPfreeBufferArray(scip, &aggrnvars);
646
647 return SCIP_OKAY;
648}
649
650/** frees a nonlinear row aggregation */
651static
653 SCIP* scip, /**< SCIP data structure */
654 SCIP_NLROWAGGR** nlrowaggr /**< pointer to free the nonlinear row aggregation */
655 )
656{
657 int i;
658
659 assert(scip != NULL);
660 assert(nlrowaggr != NULL);
661 assert(*nlrowaggr != NULL);
662 (*nlrowaggr)->nlrow = NULL;
663 assert((*nlrowaggr)->quadvars != NULL);
664 assert((*nlrowaggr)->nquadvars > 0);
665 assert((*nlrowaggr)->nremterms >= 0);
666
667 /* free remaining part */
668 SCIPfreeBlockMemoryArrayNull(scip, &(*nlrowaggr)->remtermcoefs, (*nlrowaggr)->remtermsize);
669 SCIPfreeBlockMemoryArrayNull(scip, &(*nlrowaggr)->remtermvars1, (*nlrowaggr)->remtermsize);
670 SCIPfreeBlockMemoryArrayNull(scip, &(*nlrowaggr)->remtermvars2, (*nlrowaggr)->remtermsize);
671
672 /* free quadratic variables */
673 SCIPfreeBlockMemoryArray(scip, &(*nlrowaggr)->quadvars, (*nlrowaggr)->quadvarssize);
674 SCIPfreeBlockMemoryArray(scip, &(*nlrowaggr)->quadvar2aggr, (*nlrowaggr)->nquadvars);
675
676 /* free linear part */
677 if( (*nlrowaggr)->nlinvars > 0 )
678 {
679 SCIPfreeBlockMemoryArray(scip, &(*nlrowaggr)->linvars, (*nlrowaggr)->linvarssize);
680 SCIPfreeBlockMemoryArray(scip, &(*nlrowaggr)->lincoefs, (*nlrowaggr)->linvarssize);
681 }
682
683 /* free edge-concave aggregations */
684 for( i = 0; i < (*nlrowaggr)->necaggr; ++i )
685 {
686 SCIP_CALL( ecaggrFree(scip, &(*nlrowaggr)->ecaggr[i]) );
687 }
688 SCIPfreeBlockMemoryArray(scip, &(*nlrowaggr)->ecaggr, (*nlrowaggr)->necaggr);
689
690 /* free nlrow aggregation */
691 SCIPfreeBlockMemory(scip, nlrowaggr);
692
693 return SCIP_OKAY;
694}
695
696#ifdef SCIP_DEBUG
697/** prints a nonlinear row aggregation */
698static
699void nlrowaggrPrint(
700 SCIP* scip, /**< SCIP data structure */
701 SCIP_NLROWAGGR* nlrowaggr /**< nonlinear row aggregation */
702 )
703{
704 int i;
705
706 SCIPdebugMsg(scip, " nlrowaggr rhs = %e\n", nlrowaggr->rhs);
707 SCIPdebugMsg(scip, " #remaining terms = %d\n", nlrowaggr->nremterms);
708
709 SCIPdebugMsg(scip, "remaining terms: ");
710 for( i = 0; i < nlrowaggr->nremterms; ++i )
711 SCIPdebugMsgPrint(scip, "%e %s * %s + ", nlrowaggr->remtermcoefs[i], SCIPvarGetName(nlrowaggr->remtermvars1[i]),
712 SCIPvarGetName(nlrowaggr->remtermvars2[i]) );
713 for( i = 0; i < nlrowaggr->nlinvars; ++i )
714 SCIPdebugMsgPrint(scip, "%e %s + ", nlrowaggr->lincoefs[i], SCIPvarGetName(nlrowaggr->linvars[i]) );
715 SCIPdebugMsgPrint(scip, "\n");
716
717 for( i = 0; i < nlrowaggr->necaggr; ++i )
718 {
719 SCIPdebugMsg(scip, "print e.c. aggr %d\n", i);
720 ecaggrPrint(scip, nlrowaggr->ecaggr[i]);
721 }
722 return;
723}
724#endif
725
726/** creates separator data */
727static
729 SCIP* scip, /**< SCIP data structure */
730 SCIP_SEPADATA** sepadata /**< pointer to store separator data */
731 )
732{
733 assert(scip != NULL);
734 assert(sepadata != NULL);
735
736 SCIP_CALL( SCIPallocBlockMemory(scip, sepadata) );
737 BMSclearMemory(*sepadata);
738
739 return SCIP_OKAY;
740}
741
742/** frees all nonlinear row aggregations */
743static
745 SCIP* scip, /**< SCIP data structure */
746 SCIP_SEPADATA* sepadata /**< pointer to store separator data */
747 )
748{
749 assert(scip != NULL);
750 assert(sepadata != NULL);
751
752 /* free nonlinear row aggregations */
753 if( sepadata->nlrowaggrs != NULL )
754 {
755 int i;
756
757 for( i = sepadata->nnlrowaggrs - 1; i >= 0; --i )
758 {
759 SCIP_CALL( nlrowaggrFree(scip, &sepadata->nlrowaggrs[i]) );
760 }
761
762 SCIPfreeBlockMemoryArray(scip, &sepadata->nlrowaggrs, sepadata->nlrowaggrssize);
763
764 sepadata->nlrowaggrs = NULL;
765 sepadata->nnlrowaggrs = 0;
766 sepadata->nlrowaggrssize = 0;
767 }
768
769 return SCIP_OKAY;
770}
771
772/** frees separator data */
773static
775 SCIP* scip, /**< SCIP data structure */
776 SCIP_SEPADATA** sepadata /**< pointer to store separator data */
777 )
778{
779 assert(scip != NULL);
780 assert(sepadata != NULL);
781 assert(*sepadata != NULL);
782
783 /* free nonlinear row aggregations */
784 SCIP_CALL( sepadataFreeNlrows(scip, *sepadata) );
785
786 /* free LP interface */
787 if( (*sepadata)->lpi != NULL )
788 {
789 SCIP_CALL( SCIPlpiFree(&((*sepadata)->lpi)) );
790 (*sepadata)->lpisize = 0;
791 }
792
793 SCIPfreeBlockMemory(scip, sepadata);
794
795 return SCIP_OKAY;
796}
797
798/** adds a nonlinear row aggregation to the separator data */
799static
801 SCIP* scip, /**< SCIP data structure */
802 SCIP_SEPADATA* sepadata, /**< separator data */
803 SCIP_NLROWAGGR* nlrowaggr /**< non-linear row aggregation */
804 )
805{
806 int i;
807
808 assert(scip != NULL);
809 assert(sepadata != NULL);
810 assert(nlrowaggr != NULL);
811
812 if( sepadata->nlrowaggrssize == 0 )
813 {
814 SCIP_CALL( SCIPallocBlockMemoryArray(scip, &sepadata->nlrowaggrs, 2) ); /*lint !e506*/
815 sepadata->nlrowaggrssize = 2;
816 }
817 else if( sepadata->nlrowaggrssize < sepadata->nnlrowaggrs + 1 )
818 {
819 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &sepadata->nlrowaggrs, sepadata->nlrowaggrssize, 2 * sepadata->nlrowaggrssize) ); /*lint !e506 !e647*/
820 sepadata->nlrowaggrssize *= 2;
821 assert(sepadata->nlrowaggrssize >= sepadata->nnlrowaggrs + 1);
822 }
823
824 sepadata->nlrowaggrs[ sepadata->nnlrowaggrs ] = nlrowaggr;
825 ++(sepadata->nnlrowaggrs);
826
827 /* update maximum e.c. aggregation size */
828 for( i = 0; i < nlrowaggr->necaggr; ++i )
829 sepadata->maxecsize = MAX(sepadata->maxecsize, nlrowaggr->ecaggr[i]->nvars);
830
831#ifdef SCIP_STATISTIC
832 /* update statistics */
833 if( nlrowaggr->rhsaggr )
834 ++(sepadata->nrhsnlrowaggrs);
835 else
836 ++(sepadata->nlhsnlrowaggrs);
837#endif
838
839 return SCIP_OKAY;
840}
841
842/** returns min{val-lb,ub-val} / (ub-lb) */
843static
845 SCIP* scip, /**< SCIP data structure */
846 SCIP_Real val, /**< solution value */
847 SCIP_Real lb, /**< lower bound */
848 SCIP_Real ub /**< upper bound */
849 )
850{
851 if( SCIPisFeasEQ(scip, lb, ub) )
852 return 0.0;
853
854 /* adjust */
855 val = MAX(val, lb);
856 val = MIN(val, ub);
857
858 return MIN(ub - val, val - lb) / (ub - lb);
859}
860
861/** creates an MIP to search for cycles with an odd number of positive edges in the graph representation of a nonlinear row
862 *
863 * The model uses directed binary arc flow variables.
864 * We introduce for all quadratic elements a forward and backward edge.
865 * If the term is quadratic (e.g., loop in the graph) we fix the corresponding variables to zero.
866 * This leads to an easy mapping between quadratic elements and the variables of the MIP.
867 */
868static
870 SCIP* scip, /**< SCIP data structure */
871 SCIP* subscip, /**< auxiliary SCIP to search aggregations */
872 SCIP_SEPADATA* sepadata, /**< separator data */
873 SCIP_NLROW* nlrow, /**< nonlinear row */
874 SCIP_Bool rhsaggr, /**< consider nonlinear row aggregation for g(x) <= rhs (TRUE) or
875 * lhs <= g(x) (FALSE) */
876 SCIP_VAR** forwardarcs, /**< array to store all forward arc variables */
877 SCIP_VAR** backwardarcs, /**< array to store all backward arc variables */
878 SCIP_Real* nodeweights, /**< weights for each node of the graph */
879 int* nedges, /**< pointer to store the number of nonexcluded edges in the graph */
880 int* narcs /**< pointer to store the number of created arc variables (number of square and bilinear terms) */
881 )
882{
883 SCIP_VAR** oddcyclearcs;
884 SCIP_CONS** flowcons;
885 SCIP_CONS* cyclelengthcons;
886 SCIP_CONS* oddcyclecons;
887 char name[SCIP_MAXSTRLEN];
888 SCIP_EXPR* expr;
889 int noddcyclearcs;
890 int nnodes;
891 int nquadexprs;
892 int nbilinexprs;
893 int i;
894 int arcidx;
895
896 assert(subscip != NULL);
897 assert(forwardarcs != NULL);
898 assert(backwardarcs != NULL);
899 assert(nedges != NULL);
900 assert(sepadata->minaggrsize <= sepadata->maxaggrsize);
901
902 expr = SCIPnlrowGetExpr(nlrow);
903 SCIPexprGetQuadraticData(expr, NULL, NULL, NULL, NULL, &nquadexprs, &nbilinexprs, NULL, NULL);
904
905 nnodes = nquadexprs;
906 *nedges = 0;
907 *narcs = 0;
908
909 assert(nnodes > 0);
910
911 noddcyclearcs = 0;
912 SCIP_CALL( SCIPallocBufferArray(subscip, &oddcyclearcs, 2*nbilinexprs) );
913
914 /* create problem with default plug-ins */
915 SCIP_CALL( SCIPcreateProbBasic(subscip, "E.C. aggregation MIP") );
918
919 /* create forward and backward arc variables */
920 for( i = 0; i < nquadexprs; ++i )
921 {
922 SCIP_EXPR* qterm;
923 SCIP_Real coef;
924 int nadjbilin;
925 int* adjbilin;
926 int j;
927
928 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, &coef, &nadjbilin, &adjbilin, NULL);
929
930 if( !SCIPisZero(scip, coef) )
931 {
932 /* squares (loops) are fixed to zero */
933 SCIPdebugMsg(scip, "edge {%d,%d} = {%s,%s} coeff=%e edgeweight=0\n", i, i,
935 coef);
936
937 (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "x#%d#%d", i, i);
938 SCIP_CALL( SCIPcreateVarBasic(subscip, &forwardarcs[*narcs], name, 0.0, 0.0, 0.01, SCIP_VARTYPE_BINARY) );
939 SCIP_CALL( SCIPaddVar(subscip, forwardarcs[*narcs]) );
940
941 SCIP_CALL( SCIPcreateVarBasic(subscip, &backwardarcs[*narcs], name, 0.0, 0.0, 0.01, SCIP_VARTYPE_BINARY) );
942 SCIP_CALL( SCIPaddVar(subscip, backwardarcs[*narcs]) );
943
944 ++*narcs;
945 }
946
947 for( j = 0 ; j < nadjbilin; ++j )
948 {
949 SCIP_EXPR* qterm1;
950 SCIP_EXPR* qterm2;
951 int pos2;
952 SCIP_Real edgeweight;
953 SCIP_CONS* noparallelcons;
954
955 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, &qterm2, &coef, &pos2, NULL);
956
957 /* handle qterm == qterm2 later */
958 if( qterm1 != qterm )
959 continue;
960
961 edgeweight = nodeweights[i] + nodeweights[pos2];
962 SCIPdebugMsg(scip, "edge {%d,%d} = {%s,%s} coeff=%e edgeweight=%e\n", i, pos2,
964 coef, edgeweight);
965
966 (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "x#%d#%d", i, pos2);
967 SCIP_CALL( SCIPcreateVarBasic(subscip, &forwardarcs[*narcs], name, 0.0, 1.0, 0.01 + edgeweight, SCIP_VARTYPE_BINARY) );
968 SCIP_CALL( SCIPaddVar(subscip, forwardarcs[*narcs]) );
969
970 (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "x#%d#%d", i, pos2);
971 SCIP_CALL( SCIPcreateVarBasic(subscip, &backwardarcs[*narcs], name, 0.0, 1.0, 0.01 + edgeweight, SCIP_VARTYPE_BINARY) );
972 SCIP_CALL( SCIPaddVar(subscip, backwardarcs[*narcs]) );
973
974 ++(*nedges);
975
976 /* store all arcs which are important for the odd cycle property (no loops) */
977 if( rhsaggr && SCIPisPositive(scip, coef) )
978 {
979 assert(noddcyclearcs < 2*nbilinexprs-1);
980 oddcyclearcs[noddcyclearcs++] = forwardarcs[i];
981 oddcyclearcs[noddcyclearcs++] = backwardarcs[i];
982 }
983
984 if( !rhsaggr && SCIPisNegative(scip, coef) )
985 {
986 assert(noddcyclearcs < 2*nbilinexprs-1);
987 oddcyclearcs[noddcyclearcs++] = forwardarcs[i];
988 oddcyclearcs[noddcyclearcs++] = backwardarcs[i];
989 }
990
991 /* add constraints to ensure no parallel edges */
992 (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "cons_noparalleledges");
993 SCIP_CALL( SCIPcreateConsBasicLinear(subscip, &noparallelcons, name, 0, NULL, NULL, 0.0, 1.0) );
994 SCIP_CALL( SCIPaddCoefLinear(subscip, noparallelcons, forwardarcs[*narcs], 1.0) );
995 SCIP_CALL( SCIPaddCoefLinear(subscip, noparallelcons, backwardarcs[*narcs], 1.0) );
996 SCIP_CALL( SCIPaddCons(subscip, noparallelcons) );
997 SCIP_CALL( SCIPreleaseCons(subscip, &noparallelcons) );
998
999 ++*narcs;
1000 }
1001 }
1002 assert(*narcs > 0);
1003
1004 /* odd cycle property constraint */
1005 (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "cons_oddcycle");
1006 SCIP_CALL( SCIPcreateConsBasicXor(subscip, &oddcyclecons, name, TRUE, noddcyclearcs, oddcyclearcs) );
1007 SCIP_CALL( SCIPaddCons(subscip, oddcyclecons) );
1008 SCIP_CALL( SCIPreleaseCons(subscip, &oddcyclecons) );
1009 SCIPfreeBufferArray(subscip, &oddcyclearcs);
1010
1011 /* cycle length constraint */
1012 (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "cons_cyclelength");
1013 SCIP_CALL( SCIPcreateConsBasicLinear(subscip, &cyclelengthcons, name, 0, NULL, NULL,
1014 (SCIP_Real) sepadata->minaggrsize, (SCIP_Real) sepadata->maxaggrsize) );
1015
1016 for( i = 0; i < *narcs; ++i )
1017 {
1018 SCIP_CALL( SCIPaddCoefLinear(subscip, cyclelengthcons, forwardarcs[i], 1.0) );
1019 SCIP_CALL( SCIPaddCoefLinear(subscip, cyclelengthcons, backwardarcs[i], 1.0) );
1020 }
1021
1022 SCIP_CALL( SCIPaddCons(subscip, cyclelengthcons) );
1023 SCIP_CALL( SCIPreleaseCons(subscip, &cyclelengthcons) );
1024
1025 /* create flow conservation constraints */
1026 SCIP_CALL( SCIPallocBufferArray(subscip, &flowcons, nnodes) );
1027
1028 for( i = 0; i < nnodes; ++i )
1029 {
1030 (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "cons_flowconservation#%d", i);
1031 SCIP_CALL( SCIPcreateConsBasicLinear(subscip, &flowcons[i], name, 0, NULL, NULL, 0.0, 0.0) );
1032 }
1033
1034 arcidx = 0;
1035 for( i = 0; i < nquadexprs; ++i )
1036 {
1037 SCIP_EXPR* qterm;
1038 SCIP_Real coef;
1039 int nadjbilin;
1040 int* adjbilin;
1041 int j;
1042
1043 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, &coef, &nadjbilin, &adjbilin, NULL);
1044
1045 if( !SCIPisZero(scip, coef) )
1046 ++arcidx;
1047
1048 for( j = 0 ; j < nadjbilin; ++j )
1049 {
1050 SCIP_EXPR* qterm1;
1051 int pos2;
1052
1053 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, NULL, NULL, &pos2, NULL);
1054
1055 /* handle qterm == qterm2 later */
1056 if( qterm1 != qterm )
1057 continue;
1058
1059 SCIP_CALL( SCIPaddCoefLinear(subscip, flowcons[i], forwardarcs[arcidx], 1.0) );
1060 SCIP_CALL( SCIPaddCoefLinear(subscip, flowcons[i], backwardarcs[arcidx], -1.0) );
1061
1062 SCIP_CALL( SCIPaddCoefLinear(subscip, flowcons[pos2], forwardarcs[arcidx], -1.0) );
1063 SCIP_CALL( SCIPaddCoefLinear(subscip, flowcons[pos2], backwardarcs[arcidx], 1.0) );
1064
1065 ++arcidx;
1066 }
1067 }
1068 assert(arcidx == *narcs);
1069
1070 for( i = 0; i < nnodes; ++i )
1071 {
1072 SCIP_CALL( SCIPaddCons(subscip, flowcons[i]) );
1073 SCIP_CALL( SCIPreleaseCons(subscip, &flowcons[i]) );
1074 }
1075
1076 SCIPfreeBufferArray(subscip, &flowcons);
1077
1078 return SCIP_OKAY;
1079}
1080
1081/** fixed all arc variables (u,v) for which u or v is already in an edge-concave aggregation */
1082static
1084 SCIP* subscip, /**< auxiliary SCIP to search aggregations */
1085 SCIP_NLROW* nlrow, /**< nonlinear row */
1086 SCIP_VAR** forwardarcs, /**< forward arc variables */
1087 SCIP_VAR** backwardarcs, /**< backward arc variables */
1088 int* quadvar2aggr, /**< mapping of quadvars to e.c. aggr. index (< 0: in no aggr.) */
1089 int* nedges /**< pointer to store the number of nonexcluded edges */
1090 )
1091{
1092 SCIP_EXPR* expr;
1093 int nquadexprs;
1094 int arcidx;
1095 int i;
1096
1097 assert(subscip != NULL);
1098 assert(nlrow != NULL);
1099 assert(forwardarcs != NULL);
1100 assert(backwardarcs != NULL);
1101 assert(quadvar2aggr != NULL);
1102 assert(nedges != NULL);
1103
1104 SCIP_CALL( SCIPfreeTransform(subscip) );
1105
1106 /* recompute the number of edges */
1107 *nedges = 0;
1108
1109 expr = SCIPnlrowGetExpr(nlrow);
1110 SCIPexprGetQuadraticData(expr, NULL, NULL, NULL, NULL, &nquadexprs, NULL, NULL, NULL);
1111
1112 /* fix each arc to 0 if at least one of its nodes is contained in an e.c. aggregation */
1113 arcidx = 0;
1114 for( i = 0; i < nquadexprs; ++i )
1115 {
1116 SCIP_EXPR* qterm;
1117 SCIP_Real coef;
1118 int nadjbilin;
1119 int* adjbilin;
1120 int j;
1121
1122 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, &coef, &nadjbilin, &adjbilin, NULL);
1123
1124 if( !SCIPisZero(subscip, coef) )
1125 {
1126 if( quadvar2aggr[i] != -1 )
1127 {
1128 SCIP_CALL( SCIPchgVarUb(subscip, forwardarcs[arcidx], 0.0) );
1129 SCIP_CALL( SCIPchgVarUb(subscip, backwardarcs[arcidx], 0.0) );
1130 }
1131 ++arcidx;
1132 }
1133
1134 for( j = 0 ; j < nadjbilin; ++j )
1135 {
1136 SCIP_EXPR* qterm1;
1137 int pos2;
1138
1139 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, NULL, NULL, &pos2, NULL);
1140
1141 /* handle qterm == qterm2 later */
1142 if( qterm1 != qterm )
1143 continue;
1144
1145 if( quadvar2aggr[i] != -1 || quadvar2aggr[pos2] != -1 )
1146 {
1147 SCIP_CALL( SCIPchgVarUb(subscip, forwardarcs[arcidx], 0.0) );
1148 SCIP_CALL( SCIPchgVarUb(subscip, backwardarcs[arcidx], 0.0) );
1149 }
1150 else
1151 ++*nedges;
1152
1153 ++arcidx;
1154 }
1155 }
1156
1157 return SCIP_OKAY;
1158}
1159
1160/** stores the best edge-concave aggregation found by the MIP model */
1161static
1163 SCIP* subscip, /**< auxiliary SCIP to search aggregations */
1164 SCIP_NLROW* nlrow, /**< nonlinear row */
1165 SCIP_VAR** forwardarcs, /**< forward arc variables */
1166 SCIP_VAR** backwardarcs, /**< backward arc variables */
1167 int* quadvar2aggr, /**< mapping of quadvars to e.c. aggr. index (< 0: in no aggr.) */
1168 int nfoundsofar /**< number of e.c. aggregation found so far */
1169 )
1170{
1171 SCIP_SOL* sol;
1172 SCIP_EXPR* expr;
1173 int nquadexprs;
1174 int arcidx;
1175 int i;
1176
1177 assert(subscip != NULL);
1178 assert(nlrow != NULL);
1179 assert(forwardarcs != NULL);
1180 assert(backwardarcs != NULL);
1181 assert(quadvar2aggr != NULL);
1182 assert(nfoundsofar >= 0);
1183 assert(SCIPgetStatus(subscip) < SCIP_STATUS_INFEASIBLE);
1184 assert(SCIPgetNSols(subscip) > 0);
1185
1186 sol = SCIPgetBestSol(subscip);
1187 assert(sol != NULL);
1188
1189 expr = SCIPnlrowGetExpr(nlrow);
1190 SCIPexprGetQuadraticData(expr, NULL, NULL, NULL, NULL, &nquadexprs, NULL, NULL, NULL);
1191
1192 /* fix each arc to 0 if at least one of its nodes is contained in an e.c. aggregation */
1193 arcidx = 0;
1194 for( i = 0; i < nquadexprs; ++i )
1195 {
1196 SCIP_EXPR* qterm;
1197 SCIP_Real coef;
1198 int nadjbilin;
1199 int* adjbilin;
1200 int j;
1201
1202 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, &coef, &nadjbilin, &adjbilin, NULL);
1203
1204 if( !SCIPisZero(subscip, coef) )
1205 {
1206 if( SCIPisGT(subscip, SCIPgetSolVal(subscip, sol, forwardarcs[arcidx]), 0.5) ||
1207 SCIPisGT(subscip, SCIPgetSolVal(subscip, sol, backwardarcs[arcidx]), 0.5) )
1208 {
1209 assert(quadvar2aggr[i] == -1 || quadvar2aggr[i] == nfoundsofar);
1210 quadvar2aggr[i] = nfoundsofar;
1211 }
1212
1213 ++arcidx;
1214 }
1215
1216 for( j = 0; j < nadjbilin; ++j )
1217 {
1218 SCIP_EXPR* qterm1;
1219 int pos2;
1220
1221 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, NULL, NULL, &pos2, NULL);
1222
1223 /* handle qterm == qterm2 later */
1224 if( qterm1 != qterm )
1225 continue;
1226
1227 if( SCIPisGT(subscip, SCIPgetSolVal(subscip, sol, forwardarcs[arcidx]), 0.5) ||
1228 SCIPisGT(subscip, SCIPgetSolVal(subscip, sol, backwardarcs[arcidx]), 0.5) )
1229 {
1230 assert(quadvar2aggr[i] == -1 || quadvar2aggr[i] == nfoundsofar);
1231 assert(quadvar2aggr[pos2] == -1 || quadvar2aggr[pos2] == nfoundsofar);
1232
1233 quadvar2aggr[i] = nfoundsofar;
1234 quadvar2aggr[pos2] = nfoundsofar;
1235 }
1236
1237 ++arcidx;
1238 }
1239 }
1240
1241 return SCIP_OKAY;
1242}
1243
1244/** searches for edge-concave aggregations with a MIP model based on binary flow variables */
1245static
1247 SCIP* subscip, /**< SCIP data structure */
1248 SCIP_Real timelimit, /**< time limit to solve the MIP */
1249 int nedges, /**< number of nonexcluded undirected edges */
1250 SCIP_Bool* aggrleft, /**< pointer to store if there might be a left aggregation */
1251 SCIP_Bool* found /**< pointer to store if we have found an aggregation */
1252 )
1253{
1254 assert(subscip != NULL);
1255 assert(aggrleft != NULL);
1256 assert(found != NULL);
1257 assert(nedges >= 0);
1258
1259 *aggrleft = TRUE;
1260 *found = FALSE;
1261
1262 if( SCIPisLE(subscip, timelimit, 0.0) )
1263 return SCIP_OKAY;
1264
1265 /* set working limits */
1266 SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
1267 SCIP_CALL( SCIPsetLongintParam(subscip, "limits/totalnodes", SUBSCIP_NODELIMIT) );
1268
1269 /* set heuristics to aggressive */
1271
1272 /* disable output to console in optimized mode, enable in SCIP's debug mode */
1273#ifdef SCIP_DEBUG
1274 SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
1275 SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 1) );
1276#else
1277 SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
1278#endif
1279
1280 SCIP_CALL( SCIPsolve(subscip) );
1281
1282 /* no more aggregation left if the MIP is infeasible */
1283 if( SCIPgetStatus(subscip) >= SCIP_STATUS_INFEASIBLE )
1284 {
1285 *found = FALSE;
1286 *aggrleft = FALSE;
1287 return SCIP_OKAY;
1288 }
1289
1290 if( SCIPgetNSols(subscip) > 0 )
1291 {
1292 *found = TRUE;
1293 *aggrleft = TRUE;
1294
1295#ifdef SCIP_DEBUG
1296 if( SCIPgetNSols(subscip) > 0 )
1297 {
1298 SCIP_CALL( SCIPprintSol(subscip, SCIPgetBestSol(subscip), NULL , FALSE) );
1299 }
1300#endif
1301 }
1302
1303 return SCIP_OKAY;
1304}
1305
1306/** creates a tclique graph from a given nonlinear row
1307 *
1308 * SCIP's clique code can only handle integer node weights; all node weights are scaled by a factor of 100; since the
1309 * clique code ignores nodes with weight of zero, we add an offset of 100 to each weight
1310 */
1311static
1313 SCIP_NLROW* nlrow, /**< nonlinear row */
1314 TCLIQUE_GRAPH** graph, /**< TCLIQUE graph structure */
1315 SCIP_Real* nodeweights /**< weights for each quadratic variable (nodes in the graph) */
1316 )
1317{
1318 SCIP_EXPR* expr;
1319 int nquadexprs;
1320 int i;
1321
1322 assert(graph != NULL);
1323 assert(nlrow != NULL);
1324
1325 /* create the tclique graph */
1326 if( !tcliqueCreate(graph) )
1327 {
1328 SCIPerrorMessage("could not create clique graph\n");
1329 return SCIP_ERROR;
1330 }
1331
1332 expr = SCIPnlrowGetExpr(nlrow);
1333 SCIPexprGetQuadraticData(expr, NULL, NULL, NULL, NULL, &nquadexprs, NULL, NULL, NULL);
1334
1335 /* add all nodes to the tclique graph */
1336 for( i = 0; i < nquadexprs; ++i )
1337 {
1338 int nodeweight;
1339
1340 /* note: clique code can only handle integer weights */
1341 nodeweight = 100 + (int)(100 * nodeweights[i]);
1342 /* SCIPdebugMsg(scip, "%d (%s): nodeweight %d \n", i, SCIPvarGetName(SCIPnlrowGetQuadVars(nlrow)[i]), nodeweight); */
1343
1344 if( !tcliqueAddNode(*graph, i, nodeweight) )
1345 {
1346 SCIPerrorMessage("could not add node to clique graph\n");
1347 return SCIP_ERROR;
1348 }
1349 }
1350
1351 /* add all edges */
1352 for( i = 0; i < nquadexprs; ++i )
1353 {
1354 SCIP_EXPR* qterm;
1355 int nadjbilin;
1356 int* adjbilin;
1357 int j;
1358
1359 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, NULL, &nadjbilin, &adjbilin, NULL);
1360
1361 for( j = 0; j < nadjbilin; ++j )
1362 {
1363 SCIP_EXPR* qterm1;
1364 SCIP_EXPR* qterm2;
1365 int pos2;
1366
1367 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, &qterm2, NULL, &pos2, NULL);
1368
1369 /* handle qterm == qterm2 later */
1370 if( qterm1 != qterm )
1371 continue;
1372
1373#ifdef SCIP_DEBUG_DETAILED
1374 SCIPdebugMessage(" add edge (%d, %d) = (%s,%s) to tclique graph\n",
1377#endif
1378
1379 if( !tcliqueAddEdge(*graph, i, pos2) )
1380 {
1381 SCIPerrorMessage("could not add edge to clique graph\n");
1382 return SCIP_ERROR;
1383 }
1384 }
1385 }
1386
1387 /* flush the clique graph */
1388 if( !tcliqueFlush(*graph) )
1389 {
1390 SCIPerrorMessage("could not flush the clique graph\n");
1391 return SCIP_ERROR;
1392 }
1393
1394 return SCIP_OKAY;
1395}
1396
1397/** searches for edge-concave aggregations by computing cliques in the graph representation of a given nonlinear row
1398 *
1399 * update graph, compute clique, store clique; after computing a clique we heuristically check if the clique contains
1400 * at least one good cycle
1401 */
1402static
1404 SCIP* scip, /**< SCIP data structure */
1405 TCLIQUE_GRAPH* graph, /**< TCLIQUE graph structure */
1406 SCIP_SEPADATA* sepadata, /**< separator data */
1407 SCIP_NLROW* nlrow, /**< nonlinear row */
1408 int* quadvar2aggr, /**< mapping of quadvars to e.c. aggr. index (< 0: in no aggr.) */
1409 int nfoundsofar, /**< number of e.c. aggregation found so far */
1410 SCIP_Bool rhsaggr, /**< consider nonlinear row aggregation for g(x) <= rhs (TRUE) or
1411 * lhs <= g(x) (FALSE) */
1412 SCIP_Bool* foundaggr, /**< pointer to store if we have found an aggregation */
1413 SCIP_Bool* foundclique /**< pointer to store if we have found a clique */
1414 )
1415{
1416 SCIP_HASHMAP* cliquemap;
1417 TCLIQUE_STATUS status;
1418 SCIP_EXPR* expr;
1419 int nquadexprs;
1420 int* maxcliquenodes;
1421 int* degrees;
1422 int nmaxcliquenodes;
1423 int maxcliqueweight;
1424 int noddcycleedges;
1425 int ntwodegrees;
1426 int aggrsize;
1427 int i;
1428
1429 assert(graph != NULL);
1430 assert(nfoundsofar >= 0);
1431 assert(foundaggr != NULL);
1432 assert(foundclique != NULL);
1433
1434 cliquemap = NULL;
1435 *foundaggr = FALSE;
1436 *foundclique = FALSE;
1437
1438 expr = SCIPnlrowGetExpr(nlrow);
1439 SCIPexprGetQuadraticData(expr, NULL, NULL, NULL, NULL, &nquadexprs, NULL, NULL, NULL);
1440 assert(nquadexprs == tcliqueGetNNodes(graph));
1441
1442 /* exclude all nodes which are already in an edge-concave aggregation (no flush is needed) */
1443 for( i = 0; i < nquadexprs; ++i )
1444 {
1445 if( quadvar2aggr[i] != -1 )
1446 {
1447 SCIPdebugMsg(scip, "exclude node %d from clique graph\n", i);
1448 tcliqueChangeWeight(graph, i, 0);
1449 }
1450 }
1451
1452 SCIP_CALL( SCIPallocBufferArray(scip, &maxcliquenodes, nquadexprs) );
1453
1454 /* solve clique problem */
1455 tcliqueMaxClique(tcliqueGetNNodes, tcliqueGetWeights, tcliqueIsEdge, tcliqueSelectAdjnodes, graph, NULL, NULL,
1456 maxcliquenodes, &nmaxcliquenodes, &maxcliqueweight, CLIQUE_MAXFIRSTNODEWEIGHT, CLIQUE_MINWEIGHT,
1458
1459 if( status != TCLIQUE_OPTIMAL || nmaxcliquenodes < sepadata->minaggrsize )
1460 goto TERMINATE;
1461
1462 *foundclique = TRUE;
1463 aggrsize = MIN(sepadata->maxaggrsize, nmaxcliquenodes);
1464 SCIP_CALL( SCIPhashmapCreate(&cliquemap, SCIPblkmem(scip), aggrsize) );
1465
1466 for( i = 0; i < aggrsize; ++i )
1467 {
1468 SCIP_CALL( SCIPhashmapInsertInt(cliquemap, (void*) (size_t) maxcliquenodes[i], 0) ); /*lint !e571*/
1469 }
1470
1471 /* count the degree of good cycle edges for each node in the clique */
1472 SCIP_CALL( SCIPallocBufferArray(scip, &degrees, aggrsize) );
1473 BMSclearMemoryArray(degrees, aggrsize);
1474 ntwodegrees = 0;
1475
1476 /* count the number of positive or negative edges (depending on <= rhs or >= lhs) */
1477 noddcycleedges = 0;
1478 for( i = 0; i < nquadexprs; ++i )
1479 {
1480 SCIP_Bool isoddcycleedge;
1481 SCIP_EXPR* qterm;
1482 SCIP_Real coef;
1483 int nadjbilin;
1484 int* adjbilin;
1485 int j;
1486
1487 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, &coef, &nadjbilin, &adjbilin, NULL);
1488
1489 isoddcycleedge = (rhsaggr && SCIPisPositive(scip, coef)) || (!rhsaggr && SCIPisNegative(scip, coef));
1490
1491 if( isoddcycleedge && SCIPhashmapExists(cliquemap, (void*) (size_t) i) )
1492 {
1493 ++noddcycleedges;
1494 ++degrees[i];
1495 }
1496
1497 for( j = 0; j < nadjbilin; ++j )
1498 {
1499 SCIP_EXPR* qterm1;
1500 SCIP_EXPR* qterm2;
1501 int pos2;
1502
1503 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, &qterm2, &coef, &pos2, NULL);
1504
1505 /* handle qterm == qterm2 later */
1506 if( qterm1 != qterm )
1507 continue;
1508
1509 isoddcycleedge = (rhsaggr && SCIPisPositive(scip, coef)) || (!rhsaggr && SCIPisNegative(scip, coef));
1510
1511 if( isoddcycleedge
1512 && SCIPhashmapExists(cliquemap, (void*) (size_t) i)
1513 && SCIPhashmapExists(cliquemap, (void*) (size_t) pos2) )
1514 {
1515 ++noddcycleedges;
1516 ++degrees[i];
1517 ++degrees[pos2];
1518 }
1519 }
1520 }
1521
1522 /* count the number of nodes with exactly two incident odd cycle edges */
1523 for( i = 0; i < aggrsize; ++i )
1524 if( degrees[i] == 2 )
1525 ++ntwodegrees;
1526
1527 /* check cases for which we are sure that there are no good cycles in the clique */
1528 if( noddcycleedges == 0 || (aggrsize == 3 && noddcycleedges == 2) || (aggrsize == 4 && ntwodegrees == 4) )
1529 *foundaggr = FALSE;
1530 else
1531 *foundaggr = TRUE;
1532
1533 /* add the found clique as an edge-concave aggregation or exclude the nodes from the remaining search */
1534 for( i = 0; i < aggrsize; ++i )
1535 {
1536 quadvar2aggr[ maxcliquenodes[i] ] = *foundaggr ? nfoundsofar : -2;
1537 SCIPdebugMsg(scip, "%s %d\n", *foundaggr ? "aggregate node: " : "exclude node: ", maxcliquenodes[i]);
1538 }
1539
1540 SCIPfreeBufferArray(scip, &degrees);
1541
1542TERMINATE:
1543 if( cliquemap != NULL )
1544 SCIPhashmapFree(&cliquemap);
1545 SCIPfreeBufferArray(scip, &maxcliquenodes);
1546
1547 return SCIP_OKAY;
1548}
1549
1550/** helper function for searchEcAggr() */
1551static
1553 SCIP* scip, /**< SCIP data structure */
1554 SCIP* subscip, /**< sub-SCIP data structure */
1555 SCIP_SEPADATA* sepadata, /**< separator data */
1556 SCIP_NLROW* nlrow, /**< nonlinear row */
1557 SCIP_SOL* sol, /**< current solution (might be NULL) */
1558 SCIP_Bool rhsaggr, /**< consider nonlinear row aggregation for g(x) <= rhs (TRUE) or g(x) >= lhs (FALSE) */
1559 int* quadvar2aggr, /**< array to store for each quadratic variable in which edge-concave
1560 * aggregation it is stored (< 0: in no aggregation); size has to be at
1561 * least SCIPnlrowGetNQuadVars(nlrow) */
1562 int* nfound /**< pointer to store the number of found e.c. aggregations */
1563 )
1564{
1565 TCLIQUE_GRAPH* graph = NULL;
1566 SCIP_EXPR* expr;
1567 SCIP_VAR** forwardarcs;
1568 SCIP_VAR** backwardarcs;
1569 SCIP_Real* nodeweights;
1570 SCIP_Real timelimit;
1571 SCIP_RETCODE retcode;
1572 int nunsucces = 0;
1573 int nedges = 0;
1574 int narcs;
1575 int nquadvars;
1576 int nbilinexprs;
1577 int i;
1578
1579 assert(subscip != NULL);
1580 assert(quadvar2aggr != NULL);
1581 assert(nfound != NULL);
1582
1583 expr = SCIPnlrowGetExpr(nlrow);
1584 SCIPexprGetQuadraticData(expr, NULL, NULL, NULL, NULL, &nquadvars, &nbilinexprs, NULL, NULL);
1585
1586 retcode = SCIP_OKAY;
1587 *nfound = 0;
1588
1589 /* arrays to store all arc variables of the MIP model; note that we introduce variables even for loops in the graph
1590 * to have an easy mapping from the edges of the graph to the quadratic elements
1591 * nquadvars + nbilinexprs is an upper bound on the actual number of square and bilinear terms
1592 */
1593 SCIP_CALL( SCIPallocBufferArray(scip, &nodeweights, nquadvars) );
1594 SCIP_CALL( SCIPallocBufferArray(scip, &forwardarcs, nquadvars + nbilinexprs) );
1595 SCIP_CALL( SCIPallocBufferArray(scip, &backwardarcs, nquadvars + nbilinexprs) );
1596
1597 /* initialize mapping from quadvars to e.c. aggregation index (-1: quadvar is in no aggregation); compute node
1598 * weights
1599 */
1600 for( i = 0; i < nquadvars; ++i )
1601 {
1602 SCIP_EXPR* qterm;
1603 SCIP_VAR* var;
1604
1605 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, NULL, NULL, NULL, NULL);
1606 assert(SCIPisExprVar(scip, qterm));
1607 var = SCIPgetVarExprVar(qterm);
1608
1609 quadvar2aggr[i] = -1;
1610 nodeweights[i] = phi(scip, SCIPgetSolVal(scip, sol, var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var));
1611 SCIPdebugMsg(scip, "%s = %e (%e in [%e, %e])\n", SCIPvarGetName(var), nodeweights[i], SCIPgetSolVal(scip, sol, var),
1613 }
1614
1615 SCIP_CALL( createMIP(scip, subscip, sepadata, nlrow, rhsaggr, forwardarcs, backwardarcs, nodeweights, &nedges, &narcs) );
1616 assert(nedges >= 0);
1617 assert(narcs > 0);
1618 SCIPdebugMsg(scip, "nedges (without loops) = %d\n", nedges);
1619 SCIPdebugMsg(scip, "narcs (number of quadratic terms) = %d\n", narcs);
1620
1621 SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
1622
1623 /* main loop to search for edge-concave aggregations */
1624 while( !SCIPisStopped(scip) )
1625 {
1626 SCIP_Bool aggrleft;
1627 SCIP_Bool found;
1628
1629 SCIPdebugMsg(scip, "#remaining edges = %d\n", nedges);
1630
1631 /* not enough edges left */
1632 if( nedges < sepadata->minaggrsize )
1633 break;
1634
1635 /* check whether there is enough time left; update the remaining time */
1636 if( !SCIPisInfinity(scip, timelimit) )
1637 {
1638 timelimit -= SCIPgetSolvingTime(scip);
1639 if( timelimit <= 0.0 )
1640 {
1641 SCIPdebugMsg(scip, "skip aggregation search since no time left\n");
1642 goto TERMINATE;
1643 }
1644 }
1645
1646 /* 1.a - search for edge-concave aggregation with the help of the MIP model */
1647 SCIP_CALL( searchEcAggrWithMIP(subscip, timelimit, nedges, &aggrleft, &found) );
1648
1649 /* 1.b - there are no more edge-concave aggregations left */
1650 if( !aggrleft )
1651 {
1652 SCIPdebugMsg(scip, "no more aggregation left\n");
1653 break;
1654 }
1655
1656 if( found )
1657 {
1658 SCIP_CALL( storeAggrFromMIP(subscip, nlrow, forwardarcs, backwardarcs, quadvar2aggr, *nfound) );
1659 ++(*nfound);
1660 nunsucces = 0;
1661 }
1662 /* try to find an edge-concave aggregation by computing cliques */
1663 else
1664 {
1665 SCIP_Bool foundaggr;
1666 SCIP_Bool foundclique;
1667
1668 ++nunsucces;
1669
1670 /* create graph if necessary */
1671 if( graph == NULL )
1672 {
1673 SCIP_CALL_TERMINATE( retcode, createTcliqueGraph(nlrow, &graph, nodeweights), TERMINATE );
1674 }
1675
1676 /* 2.a - search and store a single edge-concave aggregation by computing a clique with a good cycle */
1677 SCIP_CALL_FINALLY( searchEcAggrWithCliques(scip, graph, sepadata, nlrow, quadvar2aggr, *nfound, rhsaggr,
1678 &foundaggr, &foundclique), tcliqueFree(&graph) );
1679
1680 if( foundaggr )
1681 {
1682 assert(foundclique);
1683 ++(*nfound);
1684 nunsucces = 0;
1685 }
1686 else
1687 ++nunsucces;
1688
1689 /* 2.b - no clique of at least minaggrsize size found */
1690 if( !foundclique )
1691 {
1692 assert(!foundaggr);
1693 SCIPdebugMsg(scip, "did not find a clique to exclude -> leave aggregation search\n");
1694 break;
1695 }
1696 }
1697
1698 /* leave the algorithm if we did not find something for maxstallrounds many iterations */
1699 if( nunsucces >= sepadata->maxstallrounds && *nfound == 0 )
1700 {
1701 SCIPdebugMsg(scip, "did not find an e.c. aggregation for %d iterations\n", nunsucces);
1702 break;
1703 }
1704
1705 /* exclude all edges used in the last aggregation and nodes found in the clique solution */
1706 SCIP_CALL_FINALLY( updateMIP(subscip, nlrow, forwardarcs, backwardarcs, quadvar2aggr, &nedges), tcliqueFree(&graph) );
1707 }
1708
1709TERMINATE:
1710
1711#ifdef SCIP_DEBUG
1712 SCIPdebugMsg(scip, "aggregations found:\n");
1713 for( i = 0; i < nquadvars; ++i )
1714 {
1715 SCIPdebugMsg(scip, " %d in %d\n", i, quadvar2aggr[i]);
1716 }
1717#endif
1718
1719 /* free clique graph */
1720 if( graph != NULL )
1721 tcliqueFree(&graph);
1722
1723 /* free sub-SCIP */
1724 for( i = 0; i < narcs; ++i )
1725 {
1726 SCIP_CALL( SCIPreleaseVar(subscip, &forwardarcs[i]) );
1727 SCIP_CALL( SCIPreleaseVar(subscip, &backwardarcs[i]) );
1728 }
1729
1730 SCIPfreeBufferArray(scip, &backwardarcs);
1731 SCIPfreeBufferArray(scip, &forwardarcs);
1732 SCIPfreeBufferArray(scip, &nodeweights);
1733
1734 return retcode;
1735}
1736
1737/** computes a partitioning into edge-concave aggregations for a given (quadratic) nonlinear row
1738 *
1739 * Each aggregation has to contain a cycle with an odd number of positive weighted edges (good cycles) in the corresponding graph representation.
1740 * For this we use the following algorithm:
1741 * -# use a MIP model based on binary flow variables to compute good cycles and store the implied subgraphs as an e.c. aggr.
1742 * -# if we find a good cycle, store the implied subgraph, delete it from the graph representation and go to 1)
1743 * -# if the MIP model is infeasible (there are no good cycles), STOP
1744 * -# we compute a large clique C if the MIP model fails (because of working limits, etc)
1745 * -# if we find a good cycle in C, store the implied subgraph of C, delete it from the graph representation and go to 1)
1746 * -# if C is not large enough, STOP
1747 */
1748static
1750 SCIP* scip, /**< SCIP data structure */
1751 SCIP_SEPADATA* sepadata, /**< separator data */
1752 SCIP_NLROW* nlrow, /**< nonlinear row */
1753 SCIP_SOL* sol, /**< current solution (might be NULL) */
1754 SCIP_Bool rhsaggr, /**< consider nonlinear row aggregation for g(x) <= rhs (TRUE) or g(x) >= lhs (FALSE) */
1755 int* quadvar2aggr, /**< array to store for each quadratic variable in which edge-concave
1756 * aggregation it is stored (< 0: in no aggregation); size has to be at
1757 * least SCIPnlrowGetNQuadVars(nlrow) */
1758 int* nfound /**< pointer to store the number of found e.c. aggregations */
1759 )
1760{
1761 SCIP* subscip;
1762 SCIP_RETCODE retcode;
1763
1764 /* create and set up a sub-SCIP */
1765 SCIP_CALL_FINALLY( SCIPcreate(&subscip), (void)SCIPfree(&subscip) );
1766
1767 retcode = doSeachEcAggr(scip, subscip, sepadata, nlrow, sol, rhsaggr, quadvar2aggr, nfound);
1768
1769 SCIP_CALL( SCIPfree(&subscip) );
1770 SCIP_CALL( retcode );
1771
1772 return SCIP_OKAY;
1773}
1774
1775/** returns whether a given nonlinear row can be used to compute edge-concave aggregations for which their convex
1776 * envelope could dominate the termwise bilinear relaxation
1777 *
1778 * This is the case if there exists at least one cycle with
1779 * an odd number of positive edges in the corresponding graph representation of the nonlinear row.
1780 */
1781static
1783 SCIP* scip, /**< SCIP data structure */
1784 SCIP_SEPADATA* sepadata, /**< separator data */
1785 SCIP_NLROW* nlrow, /**< nonlinear row representation of a nonlinear constraint */
1786 SCIP_Bool* rhscandidate, /**< pointer to store if we should compute edge-concave aggregations for
1787 * the <= rhs case */
1788 SCIP_Bool* lhscandidate /**< pointer to store if we should compute edge-concave aggregations for
1789 * the >= lhs case */
1790 )
1791{
1792 SCIP_EXPR* expr = NULL;
1793 SCIP_Bool takerow = FALSE;
1794 int nquadvars = 0;
1795 int* degrees;
1796 int ninterestingnodes;
1797 int nposedges;
1798 int nnegedges;
1799 int i;
1800
1801 assert(rhscandidate != NULL);
1802 assert(lhscandidate != NULL);
1803
1804 *rhscandidate = TRUE;
1805 *lhscandidate = TRUE;
1806
1807 /* check whether nlrow is in the NLP, is quadratic in variables, and there are enough quadratic variables */
1808 if( SCIPnlrowIsInNLP(nlrow) && SCIPnlrowGetExpr(nlrow) != NULL )
1809 {
1810 expr = SCIPnlrowGetExpr(nlrow);
1811 SCIP_CALL( SCIPcheckExprQuadratic(scip, expr, &takerow) );
1812 }
1813 if( takerow )
1814 takerow = SCIPexprAreQuadraticExprsVariables(expr);
1815 if( takerow )
1816 {
1817 SCIPexprGetQuadraticData(expr, NULL, NULL, NULL, NULL, &nquadvars, NULL, NULL, NULL);
1818 takerow = nquadvars >= sepadata->minaggrsize;
1819 }
1820 if( !takerow )
1821 {
1822 *rhscandidate = FALSE;
1823 *lhscandidate = FALSE;
1824 return SCIP_OKAY;
1825 }
1826
1827 /* check for infinite rhs or lhs */
1829 *rhscandidate = FALSE;
1831 *lhscandidate = FALSE;
1832
1833 SCIP_CALL( SCIPallocClearBufferArray(scip, &degrees, nquadvars) );
1834
1835 ninterestingnodes = 0;
1836 nposedges = 0;
1837 nnegedges = 0;
1838
1839 for( i = 0; i < nquadvars; ++i )
1840 {
1841 SCIP_EXPR* qterm;
1842 SCIP_VAR* var1;
1843 int nadjbilin;
1844 int* adjbilin;
1845 int j;
1846
1847 SCIPexprGetQuadraticQuadTerm(expr, i, &qterm, NULL, NULL, &nadjbilin, &adjbilin, NULL);
1848 assert(SCIPisExprVar(scip, qterm));
1849
1850 var1 = SCIPgetVarExprVar(qterm);
1851
1852 /* do not consider global fixed variables */
1854 continue;
1855
1856 for( j = 0; j < nadjbilin; ++j )
1857 {
1858 SCIP_EXPR* qterm1;
1859 SCIP_EXPR* qterm2;
1860 SCIP_VAR* var2;
1861 SCIP_Real coef;
1862 int pos2;
1863
1864 SCIPexprGetQuadraticBilinTerm(expr, adjbilin[j], &qterm1, &qterm2, &coef, &pos2, NULL);
1865
1866 if( qterm1 != qterm )
1867 continue;
1868
1869 var2 = SCIPgetVarExprVar(qterm2);
1870
1871 /* do not consider loops or global fixed variables */
1873 continue;
1874
1875 ++degrees[i];
1876 ++degrees[pos2];
1877
1878 /* count the number of nodes with a degree of at least 2 */
1879 if( degrees[i] == 2 )
1880 ++ninterestingnodes;
1881 if( degrees[pos2] == 2 )
1882 ++ninterestingnodes;
1883
1884 nposedges += SCIPisPositive(scip, coef) ? 1 : 0;
1885 nnegedges += SCIPisNegative(scip, coef) ? 1 : 0;
1886 }
1887 }
1888
1889 SCIPfreeBufferArray(scip, &degrees);
1890
1891 SCIPdebugMsg(scip, "nlrow contains: %d edges\n", nposedges + nnegedges);
1892
1893 /* too many edges, too few edges, or to few nodes with degree at least 2 in the graph */
1894 if( nposedges + nnegedges > sepadata->maxbilinterms || nposedges + nnegedges < sepadata->minaggrsize
1895 || ninterestingnodes < sepadata->minaggrsize )
1896 {
1897 *rhscandidate = FALSE;
1898 *lhscandidate = FALSE;
1899 return SCIP_OKAY;
1900 }
1901
1902 /* check if there are enough positive/negative edges; for a 3-clique there has to be an odd number of those edges */
1903 if( nposedges == 0 || (nposedges + nnegedges == 3 && (nposedges % 2) == 0) )
1904 *rhscandidate = FALSE;
1905 if( nnegedges == 0 || (nposedges + nnegedges == 3 && (nnegedges % 2) == 0) )
1906 *lhscandidate = FALSE;
1907
1908 return SCIP_OKAY;
1909}
1910
1911/** finds and stores edge-concave aggregations for a given nonlinear row */
1912static
1914 SCIP* scip, /**< SCIP data structure */
1915 SCIP_SEPADATA* sepadata, /**< separator data */
1916 SCIP_NLROW* nlrow, /**< nonlinear row */
1917 SCIP_SOL* sol /**< current solution (might be NULL) */
1918 )
1919{
1920 int nquadvars;
1921 int* quadvar2aggr;
1922 SCIP_Bool rhscandidate;
1923 SCIP_Bool lhscandidate;
1924
1925 assert(scip != NULL);
1926 assert(nlrow != NULL);
1927 assert(sepadata != NULL);
1928
1929#ifdef SCIP_DEBUG
1930 SCIPdebugMsg(scip, "search for edge-concave aggregation for the nonlinear row: \n");
1931 SCIP_CALL( SCIPprintNlRow(scip, nlrow, NULL) );
1932#endif
1933
1934 /* check obvious conditions for existing cycles with an odd number of positive/negative edges */
1935 SCIP_CALL( isCandidate(scip, sepadata, nlrow, &rhscandidate, &lhscandidate) );
1936 SCIPdebugMsg(scip, "rhs candidate = %u lhs candidate = %u\n", rhscandidate, lhscandidate);
1937
1938 if( !rhscandidate && !lhscandidate )
1939 return SCIP_OKAY;
1940
1942 SCIP_CALL( SCIPallocBufferArray(scip, &quadvar2aggr, nquadvars) ); /*lint !e705*/
1943
1944 /* search for edge-concave aggregations (consider <= rhs) */
1945 if( rhscandidate )
1946 {
1947 SCIP_NLROWAGGR* nlrowaggr;
1948 int nfound;
1949
1950 assert(!SCIPisInfinity(scip, REALABS(SCIPnlrowGetRhs(nlrow))));
1951
1952 SCIPdebugMsg(scip, "consider <= rhs\n");
1953 SCIP_CALL( searchEcAggr(scip, sepadata, nlrow, sol, TRUE, quadvar2aggr, &nfound) );
1954
1955 if( nfound > 0 )
1956 {
1957 SCIP_CALL( nlrowaggrCreate(scip, nlrow, &nlrowaggr, quadvar2aggr, nfound, TRUE) );
1958 assert(nlrow != NULL);
1959 SCIPdebug(nlrowaggrPrint(scip, nlrowaggr));
1960 SCIP_CALL( sepadataAddNlrowaggr(scip, sepadata, nlrowaggr) );
1961 }
1962 }
1963
1964 /* search for edge-concave aggregations (consider <= lhs) */
1965 if( lhscandidate )
1966 {
1967 SCIP_NLROWAGGR* nlrowaggr;
1968 int nfound;
1969
1970 assert(!SCIPisInfinity(scip, REALABS(SCIPnlrowGetLhs(nlrow))));
1971
1972 SCIPdebugMsg(scip, "consider >= lhs\n");
1973 SCIP_CALL( searchEcAggr(scip, sepadata, nlrow, sol, FALSE, quadvar2aggr, &nfound) );
1974
1975 if( nfound > 0 )
1976 {
1977 SCIP_CALL( nlrowaggrCreate(scip, nlrow, &nlrowaggr, quadvar2aggr, nfound, FALSE) );
1978 assert(nlrow != NULL);
1979 SCIPdebug(nlrowaggrPrint(scip, nlrowaggr));
1980 SCIP_CALL( sepadataAddNlrowaggr(scip, sepadata, nlrowaggr) );
1981 }
1982 }
1983
1984 SCIPfreeBufferArray(scip, &quadvar2aggr);
1985 return SCIP_OKAY;
1986}
1987
1988/*
1989 * methods to compute edge-concave cuts
1990 */
1991
1992#ifdef SCIP_DEBUG
1993/** prints a given facet (candidate) */
1994static
1995void printFacet(
1996 SCIP* scip, /**< SCIP data structure */
1997 SCIP_VAR** vars, /**< variables contained in the edge-concave aggregation */
1998 int nvars, /**< number of variables contained in the edge-concave aggregation */
1999 SCIP_Real* facet, /**< current facet candidate */
2000 SCIP_Real facetval /**< facet evaluated at the current solution */
2001 )
2002{
2003 int i;
2004
2005 SCIPdebugMsg(scip, "print facet (val=%e): ", facetval);
2006 for( i = 0; i < nvars; ++i )
2007 SCIPdebugMsgPrint(scip, "%e %s + ", facet[i], SCIPvarGetName(vars[i]));
2008 SCIPdebugMsgPrint(scip, "%e\n", facet[nvars]);
2009}
2010#endif
2011
2012/** checks if a facet is really an underestimate for all corners of the domain [l,u]
2013 *
2014 * Because of numerics it can happen that a facet violates a corner of the domain.
2015 * To make the facet valid we subtract the maximum violation from the constant part of the facet.
2016 */
2017static
2019 SCIP* scip, /**< SCIP data structure */
2020 SCIP_ECAGGR* ecaggr, /**< edge-concave aggregation data */
2021 SCIP_Real* fvals, /**< array containing all corner values of the aggregation */
2022 SCIP_Real* facet /**< current facet candidate (of dimension ecaggr->nvars + 1) */
2023 )
2024{
2025 SCIP_Real maxviolation;
2026 SCIP_Real val;
2027 unsigned int i;
2028 unsigned int ncorner;
2029 unsigned int prev;
2030
2031 assert(scip != NULL);
2032 assert(ecaggr != NULL);
2033 assert(fvals != NULL);
2034 assert(facet != NULL);
2035
2036 ncorner = (unsigned int) poweroftwo[ecaggr->nvars];
2037 maxviolation = 0.0;
2038
2039 /* check for the origin */
2040 val = facet[ecaggr->nvars];
2041 for( i = 0; i < (unsigned int) ecaggr->nvars; ++i )
2042 val += facet[i] * SCIPvarGetLbLocal(ecaggr->vars[i]);
2043
2044 /* update maximum violation */
2045 maxviolation = MAX(val - fvals[0], maxviolation);
2046 assert(SCIPisFeasEQ(scip, maxviolation, 0.0));
2047
2048 prev = 0;
2049 for( i = 1; i < ncorner; ++i )
2050 {
2051 unsigned int gray;
2052 unsigned int diff;
2053 unsigned int pos;
2054
2055 gray = i ^ (i >> 1);
2056 diff = gray ^ prev;
2057
2058 /* compute position of unique 1 of diff */
2059 pos = 0;
2060 while( (diff >>= 1) != 0 )
2061 ++pos;
2062
2063 if( gray > prev )
2064 val += facet[pos] * (SCIPvarGetUbLocal(ecaggr->vars[pos]) - SCIPvarGetLbLocal(ecaggr->vars[pos]));
2065 else
2066 val -= facet[pos] * (SCIPvarGetUbLocal(ecaggr->vars[pos]) - SCIPvarGetLbLocal(ecaggr->vars[pos]));
2067
2068 /* update maximum violation */
2069 maxviolation = MAX(val - fvals[gray], maxviolation);
2070 assert(SCIPisFeasEQ(scip, maxviolation, 0.0));
2071
2072 prev = gray;
2073 }
2074
2075 SCIPdebugMsg(scip, "maximum violation of facet: %2.8e\n", maxviolation);
2076
2077 /* there seem to be numerical problems if the violation is too large; in this case we reject the facet */
2078 if( maxviolation > ADJUSTFACETTOL )
2079 return FALSE;
2080
2081 /* adjust constant part of the facet */
2082 facet[ecaggr->nvars] -= maxviolation;
2083
2084 return TRUE;
2085}
2086
2087/** set up LP interface to solve LPs to compute the facet of the convex envelope */
2088static
2090 SCIP* scip, /**< SCIP data structure */
2091 SCIP_SEPADATA* sepadata /**< separation data */
2092 )
2093{
2094 SCIP_Real* obj;
2095 SCIP_Real* lb;
2096 SCIP_Real* ub;
2097 SCIP_Real* val;
2098 int* beg;
2099 int* ind;
2100 int nnonz;
2101 int ncols;
2102 int nrows;
2103 int i;
2104 int k;
2105
2106 assert(scip != NULL);
2107 assert(sepadata != NULL);
2108 assert(sepadata->nnlrowaggrs > 0);
2109
2110 /* LP interface has been already created with enough rows/columns*/
2111 if( sepadata->lpi != NULL && sepadata->lpisize >= sepadata->maxecsize )
2112 return SCIP_OKAY;
2113
2114 /* size of lpi is too small; reconstruct lpi */
2115 if( sepadata->lpi != NULL )
2116 {
2117 SCIP_CALL( SCIPlpiFree(&sepadata->lpi) );
2118 sepadata->lpi = NULL;
2119 }
2120
2121 assert(sepadata->lpi == NULL);
2122 SCIP_CALL( SCIPlpiCreate(&(sepadata->lpi), SCIPgetMessagehdlr(scip), "e.c. LP", SCIP_OBJSEN_MINIMIZE) );
2123 sepadata->lpisize = sepadata->maxecsize;
2124
2125 nrows = sepadata->maxecsize + 1;
2126 ncols = poweroftwo[nrows - 1];
2127 nnonz = (ncols * (nrows + 1)) / 2;
2128 k = 0;
2129
2130 /* allocate necessary memory */
2131 SCIP_CALL( SCIPallocBufferArray(scip, &obj, ncols) );
2132 SCIP_CALL( SCIPallocBufferArray(scip, &lb, ncols) );
2133 SCIP_CALL( SCIPallocBufferArray(scip, &ub, ncols) );
2134 SCIP_CALL( SCIPallocBufferArray(scip, &beg, ncols) );
2135 SCIP_CALL( SCIPallocBufferArray(scip, &val, nnonz) );
2136 SCIP_CALL( SCIPallocBufferArray(scip, &ind, nnonz) );
2137
2138 /* calculate nonzero entries in the LP; set obj, lb, and ub to zero */
2139 for( i = 0; i < ncols; ++i )
2140 {
2141 int row;
2142 int a;
2143
2144 obj[i] = 0.0;
2145 lb[i] = 0.0;
2146 ub[i] = 0.0;
2147
2148 SCIPdebugMsg(scip, "col %i starts at position %d\n", i, k);
2149 beg[i] = k;
2150 row = 0;
2151 a = 1;
2152
2153 /* iterate through the bit representation of i */
2154 while( a <= i )
2155 {
2156 if( (a & i) != 0 )
2157 {
2158 val[k] = 1.0;
2159 ind[k] = row;
2160
2161 SCIPdebugMsg(scip, " val[%d][%d] = 1 (position %d)\n", row, i, k);
2162
2163 ++k;
2164 }
2165
2166 a <<= 1; /*lint !e701*/
2167 ++row;
2168 assert(poweroftwo[row] == a);
2169 }
2170
2171 /* put 1 as a coefficient for sum_{i} \lambda_i = 1 row (last row) */
2172 val[k] = 1.0;
2173 ind[k] = nrows - 1;
2174 ++k;
2175 SCIPdebugMsg(scip, " val[%d][%d] = 1 (position %d)\n", nrows - 1, i, k);
2176 }
2177 assert(k == nnonz);
2178
2179 /*
2180 * add all columns to the LP interface
2181 * CPLEX needs the row to exist before adding columns, so we create the rows with dummy sides
2182 * note that the assert is not needed once somebody fixes the LPI
2183 */
2184 assert(nrows <= ncols);
2185 SCIP_CALL( SCIPlpiAddRows(sepadata->lpi, nrows, obj, obj, NULL, 0, NULL, NULL, NULL) );
2186 SCIP_CALL( SCIPlpiAddCols(sepadata->lpi, ncols, obj, lb, ub, NULL, nnonz, beg, ind, val) );
2187
2188 /* free allocated memory */
2195
2196 return SCIP_OKAY;
2197}
2198
2199/** evaluates an edge-concave aggregation at a corner of the domain [l,u] */
2200static
2202 SCIP_ECAGGR* ecaggr, /**< edge-concave aggregation data */
2203 int k /**< k-th corner */
2204 )
2205{
2206 SCIP_Real val;
2207 int i;
2208
2209 assert(ecaggr != NULL);
2210 assert(k >= 0 && k < poweroftwo[ecaggr->nvars]);
2211
2212 val = 0.0;
2213
2214 for( i = 0; i < ecaggr->nterms; ++i )
2215 {
2216 SCIP_Real coef;
2217 SCIP_Real bound1;
2218 SCIP_Real bound2;
2219 int idx1;
2220 int idx2;
2221
2222 idx1 = ecaggr->termvars1[i];
2223 idx2 = ecaggr->termvars2[i];
2224 coef = ecaggr->termcoefs[i];
2225 assert(idx1 >= 0 && idx1 < ecaggr->nvars);
2226 assert(idx2 >= 0 && idx2 < ecaggr->nvars);
2227
2228 bound1 = ((poweroftwo[idx1]) & k) == 0 ? SCIPvarGetLbLocal(ecaggr->vars[idx1]) : SCIPvarGetUbLocal(ecaggr->vars[idx1]); /*lint !e661*/
2229 bound2 = ((poweroftwo[idx2]) & k) == 0 ? SCIPvarGetLbLocal(ecaggr->vars[idx2]) : SCIPvarGetUbLocal(ecaggr->vars[idx2]); /*lint !e661*/
2230
2231 val += coef * bound1 * bound2;
2232 }
2233
2234 return val;
2235}
2236
2237/** returns (val - lb) / (ub - lb) for a in [lb, ub] */
2238static
2240 SCIP* scip, /**< SCIP data structure */
2241 SCIP_Real lb, /**< lower bound */
2242 SCIP_Real ub, /**< upper bound */
2243 SCIP_Real val /**< value in [lb,ub] */
2244 )
2245{
2246 assert(scip != NULL);
2247 assert(!SCIPisInfinity(scip, -lb));
2248 assert(!SCIPisInfinity(scip, ub));
2249 assert(!SCIPisInfinity(scip, REALABS(val)));
2250 assert(!SCIPisFeasEQ(scip, ub - lb, 0.0)); /* this would mean that a variable has been fixed */
2251
2252 /* adjust val */
2253 val = MIN(val, ub);
2254 val = MAX(val, lb);
2255
2256 val = (val - lb) / (ub - lb);
2257 assert(val >= 0.0 && val <= 1.0);
2258
2259 return val;
2260}
2261
2262/** computes a facet of the convex envelope of an edge concave aggregation
2263 *
2264 * The algorithm solves the following LP:
2265 * \f{align}{
2266 * \min & \sum_i \lambda_i f(v_i)\\
2267 * s.t. & \sum_i \lambda_i v_i = x\\
2268 * & \sum_i \lambda_i = 1\\
2269 * & \lambda \geq 0
2270 * \f}
2271 * where \f$f\f$ is an edge concave function, \f$x\in [l,u]\f$ is a solution of the current relaxation, and \f$v_i\f$ are the vertices of \f$[l,u]\f$.
2272 * The method transforms the problem to the domain \f$[0,1]^n\f$, computes a facet, and transforms this facet to the
2273 * original space. The dual solution of the LP above are the coefficients of the facet.
2274 *
2275 * The complete algorithm works as follows:
2276 * -# compute \f$f(v_i)\f$ for each corner \f$v_i\f$ of \f$[l,u]\f$
2277 * -# set up the described LP for the transformed space
2278 * -# solve the LP and store the resulting facet for the transformed space
2279 * -# transform the facet to original space
2280 * -# adjust and check facet with the algorithm of Rikun et al.
2281 */
2282static
2284 SCIP* scip, /**< SCIP data structure */
2285 SCIP_SEPADATA* sepadata, /**< separation data */
2286 SCIP_SOL* sol, /**< solution (might be NULL) */
2287 SCIP_ECAGGR* ecaggr, /**< edge-concave aggregation data */
2288 SCIP_Real* facet, /**< array to store the coefficients of the resulting facet; size has to be at least (ecaggr->nvars + 1) */
2289 SCIP_Real* facetval, /**< pointer to store the value of the facet evaluated at the current solution */
2290 SCIP_Bool* success /**< pointer to store if we have found a facet */
2291 )
2292{
2293 SCIP_Real* fvals;
2294 SCIP_Real* side;
2295 SCIP_Real* lb;
2296 SCIP_Real* ub;
2297 SCIP_Real perturbation;
2298 int* inds;
2299 int ncorner;
2300 int ncols;
2301 int nrows;
2302 int i;
2303
2304 assert(scip != NULL);
2305 assert(sepadata != NULL);
2306 assert(ecaggr != NULL);
2307 assert(facet != NULL);
2308 assert(facetval != NULL);
2309 assert(success != NULL);
2310 assert(ecaggr->nvars <= sepadata->maxecsize);
2311
2312 *facetval = -SCIPinfinity(scip);
2313 *success = FALSE;
2314
2315 /* create LP if this has not been done yet */
2316 SCIP_CALL( createLP(scip, sepadata) );
2317
2318 assert(sepadata->lpi != NULL);
2319 assert(sepadata->lpisize >= ecaggr->nvars);
2320
2321 SCIP_CALL( SCIPlpiGetNCols(sepadata->lpi, &ncols) );
2322 SCIP_CALL( SCIPlpiGetNRows(sepadata->lpi, &nrows) );
2323 ncorner = poweroftwo[ecaggr->nvars];
2324
2325 assert(ncorner <= ncols);
2326 assert(ecaggr->nvars + 1 <= nrows);
2327 assert(nrows <= ncols);
2328
2329 /* allocate necessary memory */
2330 SCIP_CALL( SCIPallocBufferArray(scip, &fvals, ncols) );
2331 SCIP_CALL( SCIPallocBufferArray(scip, &inds, ncols) );
2332 SCIP_CALL( SCIPallocBufferArray(scip, &lb, ncols) );
2333 SCIP_CALL( SCIPallocBufferArray(scip, &ub, ncols) );
2334 SCIP_CALL( SCIPallocBufferArray(scip, &side, ncols) );
2335
2336 /*
2337 * 1. compute f(v_i) for each corner v_i of [l,u]
2338 * 2. set up the described LP for the transformed space
2339 */
2340 for( i = 0; i < ncols; ++i )
2341 {
2342 fvals[i] = i < ncorner ? evalCorner(ecaggr, i) : 0.0;
2343 inds[i] = i;
2344
2345 /* update bounds; fix variables to zero which are currently not in the LP */
2346 lb[i] = 0.0;
2347 ub[i] = i < ncorner ? 1.0 : 0.0;
2348 SCIPdebugMsg(scip, "bounds of LP col %d = [%e, %e]; obj = %e\n", i, lb[i], ub[i], fvals[i]);
2349 }
2350
2351 /* update lhs and rhs */
2352 perturbation = 0.001;
2353 for( i = 0; i < nrows; ++i )
2354 {
2355 /* note that the last row corresponds to sum_{j} \lambda_j = 1 */
2356 if( i < ecaggr->nvars )
2357 {
2358 SCIP_VAR* x;
2359
2360 x = ecaggr->vars[i];
2361 assert(x != NULL);
2362
2364
2365 /* perturb point to enforce an LP solution with ecaggr->nvars + 1 nonzero */
2366 side[i] += side[i] > perturbation ? -perturbation : perturbation;
2367 perturbation /= 1.2;
2368 }
2369 else
2370 {
2371 side[i] = (i == nrows - 1) ? 1.0 : 0.0;
2372 }
2373
2374 SCIPdebugMsg(scip, "LP row %d in [%e, %e]\n", i, side[i], side[i]);
2375 }
2376
2377 /* update LP */
2378 SCIP_CALL( SCIPlpiChgObj(sepadata->lpi, ncols, inds, fvals) );
2379 SCIP_CALL( SCIPlpiChgBounds(sepadata->lpi, ncols, inds, lb, ub) );
2380 SCIP_CALL( SCIPlpiChgSides(sepadata->lpi, nrows, inds, side, side) );
2381
2382 /* free memory used to build the LP */
2383 SCIPfreeBufferArray(scip, &side);
2386 SCIPfreeBufferArray(scip, &inds);
2387
2388 /*
2389 * 3. solve the LP and store the resulting facet for the transformed space
2390 */
2391 if( USEDUALSIMPLEX ) /*lint !e774 !e506*/
2392 {
2393 SCIP_CALL( SCIPlpiSolveDual(sepadata->lpi) );
2394 }
2395 else
2396 {
2397 SCIP_CALL( SCIPlpiSolvePrimal(sepadata->lpi) );
2398 }
2399
2400 /* the dual solution corresponds to the coefficients of the facet in the transformed problem; note that it might be
2401 * the case that the dual solution has more components than the facet array
2402 */
2403 if( ecaggr->nvars + 1 == ncols )
2404 {
2405 SCIP_CALL( SCIPlpiGetSol(sepadata->lpi, NULL, NULL, facet, NULL, NULL) );
2406 }
2407 else
2408 {
2409 SCIP_Real* dualsol;
2410
2411 SCIP_CALL( SCIPallocBufferArray(scip, &dualsol, nrows) );
2412
2413 /* get the dual solution */
2414 SCIP_CALL( SCIPlpiGetSol(sepadata->lpi, NULL, NULL, dualsol, NULL, NULL) );
2415
2416 for( i = 0; i < ecaggr->nvars; ++i )
2417 facet[i] = dualsol[i];
2418
2419 /* constant part of the facet is the last component of the dual solution */
2420 facet[ecaggr->nvars] = dualsol[nrows - 1];
2421
2422 SCIPfreeBufferArray(scip, &dualsol);
2423 }
2424
2425#ifdef SCIP_DEBUG
2426 SCIPdebugMsg(scip, "facet for the transformed problem: ");
2427 for( i = 0; i < ecaggr->nvars; ++i )
2428 {
2429 SCIPdebugMsgPrint(scip, "%3.4e * %s + ", facet[i], SCIPvarGetName(ecaggr->vars[i]));
2430 }
2431 SCIPdebugMsgPrint(scip, "%3.4e\n", facet[ecaggr->nvars]);
2432#endif
2433
2434 /*
2435 * 4. transform the facet to original space
2436 * we now have the linear underestimator L(x) = beta^T x + beta_0, which needs to be transform to the original space
2437 * the underestimator in the original space, G(x) = alpha^T x + alpha_0, is given by G(x) = L(T(x)), where T(.) is
2438 * the transformation applied in step 2; therefore,
2439 * alpha_i = beta_i/(ub_i - lb_i)
2440 * alpha_0 = beta_0 - sum_i lb_i * beta_i/(ub_i - lb_i)
2441 */
2442
2443 SCIPdebugMsg(scip, "facet in orig. space: ");
2444 *facetval = 0.0;
2445
2446 for( i = 0; i < ecaggr->nvars; ++i )
2447 {
2448 SCIP_Real varlb;
2449 SCIP_Real varub;
2450
2451 varlb = SCIPvarGetLbLocal(ecaggr->vars[i]);
2452 varub = SCIPvarGetUbLocal(ecaggr->vars[i]);
2453 assert(!SCIPisEQ(scip, varlb, varub));
2454
2455 /* substract (\beta_i * lb_i) / (ub_i - lb_i) from current alpha_0 */
2456 facet[ecaggr->nvars] -= (facet[i] * varlb) / (varub - varlb);
2457
2458 /* set \alpha_i := \beta_i / (ub_i - lb_i) */
2459 facet[i] = facet[i] / (varub - varlb);
2460 *facetval += facet[i] * SCIPgetSolVal(scip, sol, ecaggr->vars[i]);
2461
2462 SCIPdebugMsgPrint(scip, "%3.4e * %s + ", facet[i], SCIPvarGetName(ecaggr->vars[i]));
2463 }
2464
2465 /* add constant part to the facet value */
2466 *facetval += facet[ecaggr->nvars];
2467 SCIPdebugMsgPrint(scip, "%3.4e\n", facet[ecaggr->nvars]);
2468
2469 /*
2470 * 5. adjust and check facet with the algorithm of Rikun et al.
2471 */
2472
2473 if( checkRikun(scip, ecaggr, fvals, facet) )
2474 {
2475 SCIPdebugMsg(scip, "facet pass the check of Rikun et al.\n");
2476 *success = TRUE;
2477 }
2478
2479 /* free allocated memory */
2480 SCIPfreeBufferArray(scip, &fvals);
2481
2482 return SCIP_OKAY;
2483}
2484
2485/*
2486 * miscellaneous methods
2487 */
2488
2489/** method to add a facet of the convex envelope of an edge-concave aggregation to a given cut */
2490static
2492 SCIP* scip, /**< SCIP data structure */
2493 SCIP_SOL* sol, /**< current solution (might be NULL) */
2494 SCIP_ROW* cut, /**< current cut (modifiable) */
2495 SCIP_Real* facet, /**< coefficient of the facet (dimension nvars + 1) */
2496 SCIP_VAR** vars, /**< variables of the facet */
2497 int nvars, /**< number of variables in the facet */
2498 SCIP_Real* cutconstant, /**< pointer to update the constant part of the facet */
2499 SCIP_Real* cutactivity, /**< pointer to update the activity of the cut */
2500 SCIP_Bool* success /**< pointer to store if everything went fine */
2501 )
2502{
2503 int i;
2504
2505 assert(cut != NULL);
2506 assert(facet != NULL);
2507 assert(vars != NULL);
2508 assert(nvars > 0);
2509 assert(cutconstant != NULL);
2510 assert(cutactivity != NULL);
2511 assert(success != NULL);
2512
2513 *success = TRUE;
2514
2515 for( i = 0; i < nvars; ++i )
2516 {
2517 if( SCIPisInfinity(scip, REALABS(facet[i])) )
2518 {
2519 *success = FALSE;
2520 return SCIP_OKAY;
2521 }
2522
2523 if( !SCIPisZero(scip, facet[i]) )
2524 {
2525 /* add only a constant if the variable has been fixed */
2526 if( SCIPvarGetLbLocal(vars[i]) == SCIPvarGetUbLocal(vars[i]) ) /*lint !e777*/
2527 {
2528 assert(SCIPisFeasEQ(scip, SCIPvarGetLbLocal(vars[i]), SCIPgetSolVal(scip, sol, vars[i])));
2529 *cutconstant += facet[i] * SCIPgetSolVal(scip, sol, vars[i]);
2530 *cutactivity += facet[i] * SCIPgetSolVal(scip, sol, vars[i]);
2531 }
2532 else
2533 {
2534 *cutactivity += facet[i] * SCIPgetSolVal(scip, sol, vars[i]);
2535 SCIP_CALL( SCIPaddVarToRow(scip, cut, vars[i], facet[i]) );
2536 }
2537 }
2538 }
2539
2540 /* add constant part of the facet */
2541 *cutconstant += facet[nvars];
2542 *cutactivity += facet[nvars];
2543
2544 return SCIP_OKAY;
2545}
2546
2547/** method to add a linear term to a given cut */
2548static
2550 SCIP* scip, /**< SCIP data structure */
2551 SCIP_SOL* sol, /**< current solution (might be NULL) */
2552 SCIP_ROW* cut, /**< current cut (modifiable) */
2553 SCIP_VAR* x, /**< linear variable */
2554 SCIP_Real coeff, /**< coefficient */
2555 SCIP_Real* cutconstant, /**< pointer to update the constant part of the facet */
2556 SCIP_Real* cutactivity, /**< pointer to update the activity of the cut */
2557 SCIP_Bool* success /**< pointer to store if everything went fine */
2558 )
2559{
2560 SCIP_Real activity;
2561
2562 assert(cut != NULL);
2563 assert(x != NULL);
2564 assert(!SCIPisZero(scip, coeff));
2565 assert(!SCIPisInfinity(scip, coeff));
2566 assert(cutconstant != NULL);
2567 assert(cutactivity != NULL);
2568 assert(success != NULL);
2569
2570 *success = TRUE;
2571 activity = SCIPgetSolVal(scip, sol, x) * coeff;
2572
2573 /* do not add a term if the activity is -infinity */
2574 if( SCIPisInfinity(scip, -1.0 * REALABS(activity)) )
2575 {
2576 *success = FALSE;
2577 return SCIP_OKAY;
2578 }
2579
2580 /* add activity to the constant part if the variable has been fixed */
2581 if( SCIPvarGetLbLocal(x) == SCIPvarGetUbLocal(x) ) /*lint !e777*/
2582 {
2584 *cutconstant += activity;
2585 SCIPdebugMsg(scip, "add to cut: %e\n", activity);
2586 }
2587 else
2588 {
2589 SCIP_CALL( SCIPaddVarToRow(scip, cut, x, coeff) );
2590 SCIPdebugMsg(scip, "add to cut: %e * %s\n", coeff, SCIPvarGetName(x));
2591 }
2592
2593 *cutactivity += activity;
2594
2595 return SCIP_OKAY;
2596}
2597
2598/** method to add an underestimate of a bilinear term to a given cut */
2599static
2601 SCIP* scip, /**< SCIP data structure */
2602 SCIP_SOL* sol, /**< current solution (might be NULL) */
2603 SCIP_ROW* cut, /**< current cut (modifiable) */
2604 SCIP_VAR* x, /**< first bilinear variable */
2605 SCIP_VAR* y, /**< seconds bilinear variable */
2606 SCIP_Real coeff, /**< coefficient */
2607 SCIP_Real* cutconstant, /**< pointer to update the constant part of the facet */
2608 SCIP_Real* cutactivity, /**< pointer to update the activity of the cut */
2609 SCIP_Bool* success /**< pointer to store if everything went fine */
2610 )
2611{
2612 SCIP_Real activity;
2613
2614 assert(cut != NULL);
2615 assert(x != NULL);
2616 assert(y != NULL);
2617 assert(!SCIPisZero(scip, coeff));
2618 assert(cutconstant != NULL);
2619 assert(cutactivity != NULL);
2620 assert(success != NULL);
2621
2622 *success = TRUE;
2623 activity = coeff * SCIPgetSolVal(scip, sol, x) * SCIPgetSolVal(scip, sol, y);
2624
2625 if( SCIPisInfinity(scip, REALABS(coeff)) )
2626 {
2627 *success = FALSE;
2628 return SCIP_OKAY;
2629 }
2630
2631 /* do not add a term if the activity is -infinity */
2632 if( SCIPisInfinity(scip, -1.0 * REALABS(activity)) )
2633 {
2634 *success = FALSE;
2635 return SCIP_OKAY;
2636 }
2637
2638 /* quadratic case */
2639 if( x == y )
2640 {
2641 SCIP_Real refpoint;
2642 SCIP_Real lincoef;
2643 SCIP_Real linconst;
2644
2645 lincoef = 0.0;
2646 linconst = 0.0;
2647 refpoint = SCIPgetSolVal(scip, sol, x);
2648
2649 /* adjust the reference point */
2650 refpoint = SCIPisLT(scip, refpoint, SCIPvarGetLbLocal(x)) ? SCIPvarGetLbLocal(x) : refpoint;
2651 refpoint = SCIPisGT(scip, refpoint, SCIPvarGetUbLocal(x)) ? SCIPvarGetUbLocal(x) : refpoint;
2652 assert(SCIPisLE(scip, refpoint, SCIPvarGetUbLocal(x)) && SCIPisGE(scip, refpoint, SCIPvarGetLbLocal(x)));
2653
2654 if( SCIPisPositive(scip, coeff) )
2655 SCIPaddSquareLinearization(scip, coeff, refpoint, SCIPvarIsIntegral(x), &lincoef, &linconst, success);
2656 else
2657 SCIPaddSquareSecant(scip, coeff, SCIPvarGetLbLocal(x), SCIPvarGetUbLocal(x), &lincoef, &linconst, success);
2658
2659 *cutactivity += lincoef * refpoint + linconst;
2660 *cutconstant += linconst;
2661
2662 /* add underestimate to cut */
2663 SCIP_CALL( SCIPaddVarToRow(scip, cut, x, lincoef) );
2664
2665 SCIPdebugMsg(scip, "add to cut: %e * %s + %e\n", lincoef, SCIPvarGetName(x), linconst);
2666 }
2667 /* bilinear case */
2668 else
2669 {
2670 SCIP_Real refpointx;
2671 SCIP_Real refpointy;
2672 SCIP_Real lincoefx;
2673 SCIP_Real lincoefy;
2674 SCIP_Real linconst;
2675
2676 lincoefx = 0.0;
2677 lincoefy = 0.0;
2678 linconst = 0.0;
2679 refpointx = SCIPgetSolVal(scip, sol, x);
2680 refpointy = SCIPgetSolVal(scip, sol, y);
2681
2682 /* adjust the reference points */
2683 refpointx = SCIPisLT(scip, refpointx, SCIPvarGetLbLocal(x)) ? SCIPvarGetLbLocal(x) : refpointx;
2684 refpointx = SCIPisGT(scip, refpointx, SCIPvarGetUbLocal(x)) ? SCIPvarGetUbLocal(x) : refpointx;
2685 refpointy = SCIPisLT(scip, refpointy, SCIPvarGetLbLocal(y)) ? SCIPvarGetLbLocal(y) : refpointy;
2686 refpointy = SCIPisGT(scip, refpointy, SCIPvarGetUbLocal(y)) ? SCIPvarGetUbLocal(y) : refpointy;
2687 assert(SCIPisLE(scip, refpointx, SCIPvarGetUbLocal(x)) && SCIPisGE(scip, refpointx, SCIPvarGetLbLocal(x)));
2688 assert(SCIPisLE(scip, refpointy, SCIPvarGetUbLocal(y)) && SCIPisGE(scip, refpointy, SCIPvarGetLbLocal(y)));
2689
2691 SCIPvarGetUbLocal(y), refpointy, FALSE, &lincoefx, &lincoefy, &linconst, success);
2692
2693 *cutactivity += lincoefx * refpointx + lincoefy * refpointy + linconst;
2694 *cutconstant += linconst;
2695
2696 /* add underestimate to cut */
2697 SCIP_CALL( SCIPaddVarToRow(scip, cut, x, lincoefx) );
2698 SCIP_CALL( SCIPaddVarToRow(scip, cut, y, lincoefy) );
2699
2700 SCIPdebugMsg(scip, "add to cut: %e * %s + %e * %s + %e\n", lincoefx, SCIPvarGetName(x), lincoefy,
2701 SCIPvarGetName(y), linconst);
2702 }
2703
2704 return SCIP_OKAY;
2705}
2706
2707/** method to compute and add a cut for a nonlinear row aggregation and a given solution
2708 *
2709 * we compute for each edge concave aggregation one facet;
2710 * the remaining bilinear terms will be underestimated with McCormick, secants or linearizations;
2711 * constant and linear terms will be added to the cut directly
2712 */
2713static
2715 SCIP* scip, /**< SCIP data structure */
2716 SCIP_SEPA* sepa, /**< separator */
2717 SCIP_SEPADATA* sepadata, /**< separator data */
2718 SCIP_NLROWAGGR* nlrowaggr, /**< nonlinear row aggregation */
2719 SCIP_SOL* sol, /**< current solution (might be NULL) */
2720 SCIP_Bool* separated, /**< pointer to store if we could separate the current solution */
2721 SCIP_Bool* cutoff /**< pointer to store if the current node gets cut off */
2722 )
2723{
2724 SCIP_ROW* cut;
2725 SCIP_Real* bestfacet;
2726 SCIP_Real bestfacetval;
2727 SCIP_Real cutconstant;
2728 SCIP_Real cutactivity;
2729 int bestfacetsize;
2730 char cutname[SCIP_MAXSTRLEN];
2731 SCIP_Bool found;
2732 SCIP_Bool islocalcut;
2733 int i;
2734
2735 assert(separated != NULL);
2736 assert(cutoff != NULL);
2737 assert(nlrowaggr->necaggr > 0);
2738 assert(nlrowaggr->nlrow != NULL);
2739 assert(SCIPnlrowIsInNLP(nlrowaggr->nlrow));
2740
2741 *separated = FALSE;
2742 *cutoff = FALSE;
2743 /* we use SCIPgetDepth because we add the cut to the global cut pool if cut is globally valid */
2744 islocalcut = SCIPgetDepth(scip) != 0;
2745
2746 /* create the cut */
2747 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "ec");
2748 SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), SCIPinfinity(scip), islocalcut, FALSE,
2749 sepadata->dynamiccuts) );
2751
2752 /* track rhs and activity of the cut */
2753 cutconstant = nlrowaggr->constant;
2754 cutactivity = 0.0;
2755
2756 /* allocate necessary memory */
2757 bestfacetsize = sepadata->maxaggrsize + 1;
2758 SCIP_CALL( SCIPallocBufferArray(scip, &bestfacet, bestfacetsize) );
2759
2760#ifdef SCIP_DEBUG
2761 SCIP_CALL( SCIPprintNlRow(scip, nlrowaggr->nlrow, NULL) );
2762
2763 SCIPdebugMsg(scip, "current solution:\n");
2764 for( i = 0; i < SCIPgetNVars(scip); ++i )
2765 {
2766 SCIP_VAR* var = SCIPgetVars(scip)[i];
2767 SCIPdebugMsg(scip, " %s = [%e, %e] solval = %e\n", SCIPvarGetName(var), SCIPvarGetLbLocal(var),
2768 SCIPvarGetUbLocal(var), SCIPgetSolVal(scip, sol, var));
2769 }
2770#endif
2771
2772 /* compute a facet for each edge-concave aggregation */
2773 for( i = 0; i < nlrowaggr->necaggr; ++i )
2774 {
2775 SCIP_ECAGGR* ecaggr;
2776 SCIP_Bool success;
2777
2778 ecaggr = nlrowaggr->ecaggr[i];
2779 assert(ecaggr != NULL);
2780
2781 /* compute a facet of the convex envelope */
2782 SCIP_CALL( computeConvexEnvelopeFacet(scip, sepadata, sol, ecaggr, bestfacet, &bestfacetval, &found) );
2783
2784 SCIPdebugMsg(scip, "found facet for edge-concave aggregation %d/%d ? %s\n", i, nlrowaggr->necaggr,
2785 found ? "yes" : "no");
2786
2787#ifdef SCIP_DEBUG
2788 if( found )
2789 printFacet(scip, ecaggr->vars, ecaggr->nvars, bestfacet, bestfacetval);
2790#endif
2791
2792 /* do not add any cut because we did not found a facet for at least one edge-concave aggregation */
2793 if( !found ) /*lint !e774*/
2794 goto TERMINATE;
2795
2796 /* add facet to the cut and update the rhs and activity of the cut */
2797 SCIP_CALL( addFacetToCut(scip, sol, cut, bestfacet, ecaggr->vars, ecaggr->nvars, &cutconstant, &cutactivity,
2798 &success) );
2799
2800 if( !success )
2801 goto TERMINATE;
2802 }
2803
2804 /* compute an underestimate for each bilinear term which is not in any edge-concave aggregation */
2805 for( i = 0; i < nlrowaggr->nremterms; ++i )
2806 {
2807 SCIP_VAR* x;
2808 SCIP_VAR* y;
2809 SCIP_Bool success;
2810
2811 x = nlrowaggr->remtermvars1[i];
2812 y = nlrowaggr->remtermvars2[i];
2813 assert(x != NULL);
2814 assert(y != NULL);
2815
2816 SCIP_CALL( addBilinearTermToCut(scip, sol, cut, x, y, nlrowaggr->remtermcoefs[i], &cutconstant, &cutactivity,
2817 &success) );
2818
2819 if( !success )
2820 goto TERMINATE;
2821 }
2822
2823 /* add all linear terms to the cut */
2824 for( i = 0; i < nlrowaggr->nlinvars; ++i )
2825 {
2826 SCIP_VAR* x;
2827 SCIP_Real coef;
2828 SCIP_Bool success;
2829
2830 x = nlrowaggr->linvars[i];
2831 assert(x != NULL);
2832
2833 coef = nlrowaggr->lincoefs[i];
2834
2835 SCIP_CALL( addLinearTermToCut(scip, sol, cut, x, coef, &cutconstant, &cutactivity, &success) );
2836
2837 if( !success )
2838 goto TERMINATE;
2839 }
2840
2841 SCIPdebugMsg(scip, "cut activity = %e rhs(nlrow) = %e\n", cutactivity, nlrowaggr->rhs);
2842
2843 /* set rhs of the cut (substract the constant part of the cut) */
2844 SCIP_CALL( SCIPchgRowRhs(scip, cut, nlrowaggr->rhs - cutconstant) );
2846
2847 /* check activity of the row; this assert can fail because of numerics */
2848 /* assert(SCIPisFeasEQ(scip, cutactivity - cutconstant, SCIPgetRowSolActivity(scip, cut, sol)) ); */
2849
2850#ifdef SCIP_DEBUG
2851 SCIP_CALL( SCIPprintRow(scip, cut, NULL) );
2852#endif
2853
2854 SCIPdebugMsg(scip, "EC cut <%s>: act=%f eff=%f rank=%d range=%e\n",
2857
2858 /* try to add the cut has a finite rhs, is efficacious, and does not exceed the maximum cut range */
2859 if( !SCIPisInfinity(scip, nlrowaggr->rhs - cutconstant) && SCIPisCutEfficacious(scip, sol, cut)
2860 && SCIPgetRowMaxCoef(scip, cut) / SCIPgetRowMinCoef(scip, cut) < sepadata->cutmaxrange )
2861 {
2862 /* add the cut if it is separating the given solution by at least minviolation */
2863 if( SCIPisGE(scip, cutactivity - nlrowaggr->rhs, sepadata->minviolation) )
2864 {
2865 SCIP_CALL( SCIPaddRow(scip, cut, FALSE, cutoff) );
2866 *separated = TRUE;
2867 SCIPdebugMsg(scip, "added separating cut\n");
2868 }
2869
2870 if( !(*cutoff) && !islocalcut )
2871 {
2872 SCIP_CALL( SCIPaddPoolCut(scip, cut) );
2873 SCIPdebugMsg(scip, "added cut to cut pool\n");
2874 }
2875 }
2876
2877TERMINATE:
2878 /* free allocated memory */
2879 SCIPfreeBufferArray(scip, &bestfacet);
2880
2881 /* release the row */
2882 SCIP_CALL( SCIPreleaseRow(scip, &cut) );
2883
2884 return SCIP_OKAY;
2885}
2886
2887/** returns whether it is possible to compute a cut for a given nonlinear row aggregation */
2888static
2890 SCIP* scip, /**< SCIP data structure */
2891 SCIP_SOL* sol, /**< current solution (might be NULL) */
2892 SCIP_NLROWAGGR* nlrowaggr /**< nonlinear row aggregation */
2893 )
2894{
2895 int i;
2896
2897 assert(scip != NULL);
2898 assert(nlrowaggr != NULL);
2899
2900 if( !SCIPnlrowIsInNLP(nlrowaggr->nlrow) )
2901 {
2902 SCIPdebugMsg(scip, "nlrow is not in NLP anymore\n");
2903 return FALSE;
2904 }
2905
2906 for( i = 0; i < nlrowaggr->nquadvars; ++i )
2907 {
2908 SCIP_VAR* var = nlrowaggr->quadvars[i];
2909 assert(var != NULL);
2910
2911 /* check whether the variable has infinite bounds */
2913 || SCIPisInfinity(scip, REALABS(SCIPgetSolVal(scip, sol, var))) )
2914 {
2915 SCIPdebugMsg(scip, "nlrow aggregation contains unbounded variables\n");
2916 return FALSE;
2917 }
2918
2919 /* check whether the variable has been fixed and is in one edge-concave aggregation */
2920 if( nlrowaggr->quadvar2aggr[i] >= 0 && SCIPisFeasEQ(scip, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var)) )
2921 {
2922 SCIPdebugMsg(scip, "nlrow aggregation contains fixed variables in an e.c. aggregation\n");
2923 return FALSE;
2924 }
2925 }
2926
2927 return TRUE;
2928}
2929
2930/** searches and tries to add edge-concave cuts */
2931static
2933 SCIP* scip, /**< SCIP data structure */
2934 SCIP_SEPA* sepa, /**< separator */
2935 SCIP_SEPADATA* sepadata, /**< separator data */
2936 int depth, /**< current depth */
2937 SCIP_SOL* sol, /**< current solution */
2938 SCIP_RESULT* result /**< pointer to store the result of the separation call */
2939 )
2940{
2941 int nmaxcuts;
2942 int ncuts;
2943 int i;
2944
2945 assert(*result == SCIP_DIDNOTRUN);
2946
2947 SCIPdebugMsg(scip, "separate cuts...\n");
2948
2949 /* skip if there are no nonlinear row aggregations */
2950 if( sepadata->nnlrowaggrs == 0 )
2951 {
2952 SCIPdebugMsg(scip, "no aggregations exists -> skip call\n");
2953 return SCIP_OKAY;
2954 }
2955
2956 /* get the maximal number of cuts allowed in a separation round */
2957 nmaxcuts = depth == 0 ? sepadata->maxsepacutsroot : sepadata->maxsepacuts;
2958 ncuts = 0;
2959
2960 /* try to compute cuts for each nonlinear row independently */
2961 for( i = 0; i < sepadata->nnlrowaggrs && ncuts < nmaxcuts && !SCIPisStopped(scip); ++i )
2962 {
2963 SCIP_NLROWAGGR* nlrowaggr;
2964 SCIP_Bool separated;
2965 SCIP_Bool cutoff;
2966
2967 nlrowaggr = sepadata->nlrowaggrs[i];
2968 assert(nlrowaggr != NULL);
2969
2970 /* skip nonlinear aggregations for which it is obviously not possible to compute a cut */
2971 if( !isPossibleToComputeCut(scip, sol, nlrowaggr) )
2972 return SCIP_OKAY;
2973
2974 *result = (*result == SCIP_DIDNOTRUN) ? SCIP_DIDNOTFIND : *result;
2975
2976 SCIPdebugMsg(scip, "try to compute a cut for nonlinear row aggregation %d\n", i);
2977
2978 /* compute and add cut */
2979 SCIP_CALL( computeCut(scip, sepa, sepadata, nlrowaggr, sol, &separated, &cutoff) );
2980 SCIPdebugMsg(scip, "found a cut: %s cutoff: %s\n", separated ? "yes" : "no", cutoff ? "yes" : "no");
2981
2982 /* stop if the current node gets cut off */
2983 if( cutoff )
2984 {
2985 assert(separated);
2986 *result = SCIP_CUTOFF;
2987 return SCIP_OKAY;
2988 }
2989
2990 /* do not compute more cuts if we already separated the given solution */
2991 if( separated )
2992 {
2993 assert(!cutoff);
2994 *result = SCIP_SEPARATED;
2995 ++ncuts;
2996 }
2997 }
2998
2999 return SCIP_OKAY;
3000}
3001
3002/*
3003 * Callback methods of separator
3004 */
3005
3006/** copy method for separator plugins (called when SCIP copies plugins) */
3007static
3008SCIP_DECL_SEPACOPY(sepaCopyEccuts)
3009{ /*lint --e{715}*/
3010 assert(scip != NULL);
3011 assert(sepa != NULL);
3012 assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
3013
3014 /* call inclusion method of constraint handler */
3016
3017 return SCIP_OKAY;
3018}
3019
3020/** destructor of separator to free user data (called when SCIP is exiting) */
3021static
3022SCIP_DECL_SEPAFREE(sepaFreeEccuts)
3023{ /*lint --e{715}*/
3024 SCIP_SEPADATA* sepadata;
3025
3026 sepadata = SCIPsepaGetData(sepa);
3027 assert(sepadata != NULL);
3028
3029 SCIP_CALL( sepadataFree(scip, &sepadata) );
3030 SCIPsepaSetData(sepa, NULL);
3031
3032 return SCIP_OKAY;
3033}
3034
3035/** solving process deinitialization method of separator (called before branch and bound process data is freed) */
3036static
3037SCIP_DECL_SEPAEXITSOL(sepaExitsolEccuts)
3038{ /*lint --e{715}*/
3039 SCIP_SEPADATA* sepadata;
3040
3041 sepadata = SCIPsepaGetData(sepa);
3042 assert(sepadata != NULL);
3043
3044 /* print statistics */
3045#ifdef SCIP_STATISTIC
3046 SCIPstatisticMessage("rhs-AGGR %d\n", sepadata->nrhsnlrowaggrs);
3047 SCIPstatisticMessage("lhs-AGGR %d\n", sepadata->nlhsnlrowaggrs);
3048 SCIPstatisticMessage("aggr. search time = %f\n", sepadata->aggrsearchtime);
3049#endif
3050
3051 /* free nonlinear row aggregations */
3052 SCIP_CALL( sepadataFreeNlrows(scip, sepadata) );
3053
3054 /* mark that we should search again for nonlinear row aggregations */
3055 sepadata->searchedforaggr = FALSE;
3056
3057 SCIPdebugMsg(scip, "exitsol\n");
3058
3059 return SCIP_OKAY;
3060}
3061
3062/** LP solution separation method of separator */
3063static
3064SCIP_DECL_SEPAEXECLP(sepaExeclpEccuts)
3065{ /*lint --e{715}*/
3066 SCIP_SEPADATA* sepadata;
3067 int ncalls;
3068
3069 sepadata = SCIPsepaGetData(sepa);
3070 assert(sepadata != NULL);
3071
3072 *result = SCIP_DIDNOTRUN;
3073
3074 if( !allowlocal )
3075 return SCIP_OKAY;
3076
3077 /* check min- and maximal aggregation size */
3078 if( sepadata->maxaggrsize < sepadata->minaggrsize )
3080
3081 /* only call separator, if we are not close to terminating */
3082 if( SCIPisStopped(scip) )
3083 return SCIP_OKAY;
3084
3085 /* skip if the LP is not constructed yet */
3087 {
3088 SCIPdebugMsg(scip, "Skip since NLP is not constructed yet.\n");
3089 return SCIP_OKAY;
3090 }
3091
3092 /* only call separator up to a maximum depth */
3093 if ( sepadata->maxdepth >= 0 && depth > sepadata->maxdepth )
3094 return SCIP_OKAY;
3095
3096 /* only call separator a given number of times at each node */
3097 ncalls = SCIPsepaGetNCallsAtNode(sepa);
3098 if ( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
3099 || (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
3100 return SCIP_OKAY;
3101
3102 /* search for nonlinear row aggregations */
3103 if( !sepadata->searchedforaggr )
3104 {
3105 int i;
3106
3107 SCIPstatistic( sepadata->aggrsearchtime -= SCIPgetTotalTime(scip) );
3108
3109 SCIPdebugMsg(scip, "search for nonlinear row aggregations\n");
3110 for( i = 0; i < SCIPgetNNLPNlRows(scip) && !SCIPisStopped(scip); ++i )
3111 {
3112 SCIP_NLROW* nlrow = SCIPgetNLPNlRows(scip)[i];
3113 SCIP_CALL( findAndStoreEcAggregations(scip, sepadata, nlrow, NULL) );
3114 }
3115 sepadata->searchedforaggr = TRUE;
3116
3117 SCIPstatistic( sepadata->aggrsearchtime += SCIPgetTotalTime(scip) );
3118 }
3119
3120 /* search for edge-concave cuts */
3121 SCIP_CALL( separateCuts(scip, sepa, sepadata, depth, NULL, result) );
3122
3123 return SCIP_OKAY;
3124}
3125
3126/*
3127 * separator specific interface methods
3128 */
3129
3130/** creates the edge-concave separator and includes it in SCIP
3131 *
3132 * @ingroup SeparatorIncludes
3133 */
3135 SCIP* scip /**< SCIP data structure */
3136 )
3137{
3138 SCIP_SEPADATA* sepadata;
3139 SCIP_SEPA* sepa;
3140
3141 /* create eccuts separator data */
3142 SCIP_CALL( sepadataCreate(scip, &sepadata) );
3143
3144 /* include separator */
3146 SEPA_USESSUBSCIP, SEPA_DELAY, sepaExeclpEccuts, NULL, sepadata) );
3147
3148 assert(sepa != NULL);
3149
3150 /* set non fundamental callbacks via setter functions */
3151 SCIP_CALL( SCIPsetSepaCopy(scip, sepa, sepaCopyEccuts) );
3152 SCIP_CALL( SCIPsetSepaFree(scip, sepa, sepaFreeEccuts) );
3153 SCIP_CALL( SCIPsetSepaExitsol(scip, sepa, sepaExitsolEccuts) );
3154
3155 /* add eccuts separator parameters */
3157 "separating/" SEPA_NAME "/dynamiccuts",
3158 "should generated cuts be removed from the LP if they are no longer tight?",
3159 &sepadata->dynamiccuts, FALSE, DEFAULT_DYNAMICCUTS, NULL, NULL) );
3160
3162 "separating/" SEPA_NAME "/maxrounds",
3163 "maximal number of eccuts separation rounds per node (-1: unlimited)",
3164 &sepadata->maxrounds, FALSE, DEFAULT_MAXROUNDS, -1, INT_MAX, NULL, NULL) );
3165
3167 "separating/" SEPA_NAME "/maxroundsroot",
3168 "maximal number of eccuts separation rounds in the root node (-1: unlimited)",
3169 &sepadata->maxroundsroot, FALSE, DEFAULT_MAXROUNDSROOT, -1, INT_MAX, NULL, NULL) );
3170
3172 "separating/" SEPA_NAME "/maxdepth",
3173 "maximal depth at which the separator is applied (-1: unlimited)",
3174 &sepadata->maxdepth, FALSE, DEFAULT_MAXDEPTH, -1, INT_MAX, NULL, NULL) );
3175
3177 "separating/" SEPA_NAME "/maxsepacuts",
3178 "maximal number of edge-concave cuts separated per separation round",
3179 &sepadata->maxsepacuts, FALSE, DEFAULT_MAXSEPACUTS, 0, INT_MAX, NULL, NULL) );
3180
3182 "separating/" SEPA_NAME "/maxsepacutsroot",
3183 "maximal number of edge-concave cuts separated per separation round in the root node",
3184 &sepadata->maxsepacutsroot, FALSE, DEFAULT_MAXSEPACUTSROOT, 0, INT_MAX, NULL, NULL) );
3185
3186 SCIP_CALL( SCIPaddRealParam(scip, "separating/" SEPA_NAME "/cutmaxrange",
3187 "maximal coef. range of a cut (max coef. divided by min coef.) in order to be added to LP relaxation",
3188 &sepadata->cutmaxrange, FALSE, DEFAULT_CUTMAXRANGE, 0.0, SCIPinfinity(scip), NULL, NULL) );
3189
3190 SCIP_CALL( SCIPaddRealParam(scip, "separating/" SEPA_NAME "/minviolation",
3191 "minimal violation of an edge-concave cut to be separated",
3192 &sepadata->minviolation, FALSE, DEFAULT_MINVIOLATION, 0.0, 0.5, NULL, NULL) );
3193
3195 "separating/" SEPA_NAME "/minaggrsize",
3196 "search for edge-concave aggregations of at least this size",
3197 &sepadata->minaggrsize, TRUE, DEFAULT_MINAGGRSIZE, 3, 5, NULL, NULL) );
3198
3200 "separating/" SEPA_NAME "/maxaggrsize",
3201 "search for edge-concave aggregations of at most this size",
3202 &sepadata->maxaggrsize, TRUE, DEFAULT_MAXAGGRSIZE, 3, 5, NULL, NULL) );
3203
3205 "separating/" SEPA_NAME "/maxbilinterms",
3206 "maximum number of bilinear terms allowed to be in a quadratic constraint",
3207 &sepadata->maxbilinterms, TRUE, DEFAULT_MAXBILINTERMS, 0, INT_MAX, NULL, NULL) );
3208
3210 "separating/" SEPA_NAME "/maxstallrounds",
3211 "maximum number of unsuccessful rounds in the edge-concave aggregation search",
3212 &sepadata->maxstallrounds, TRUE, DEFAULT_MAXSTALLROUNDS, 0, INT_MAX, NULL, NULL) );
3213
3214 return SCIP_OKAY;
3215}
SCIP_VAR * a
Definition: circlepacking.c:66
SCIP_VAR ** y
Definition: circlepacking.c:64
SCIP_VAR ** x
Definition: circlepacking.c:63
Constraint handler for XOR constraints, .
#define NULL
Definition: def.h:266
#define SCIP_MAXSTRLEN
Definition: def.h:287
#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_TERMINATE(retcode, x, TERM)
Definition: def.h:394
#define REALABS(x)
Definition: def.h:196
#define SCIP_CALL(x)
Definition: def.h:373
#define SCIP_CALL_FINALLY(x, y)
Definition: def.h:415
void SCIPaddSquareLinearization(SCIP *scip, SCIP_Real sqrcoef, SCIP_Real refpoint, SCIP_Bool isint, SCIP_Real *lincoef, SCIP_Real *linconstant, SCIP_Bool *success)
Definition: expr_pow.c:3253
void SCIPaddSquareSecant(SCIP *scip, SCIP_Real sqrcoef, SCIP_Real lb, SCIP_Real ub, SCIP_Real *lincoef, SCIP_Real *linconstant, SCIP_Bool *success)
Definition: expr_pow.c:3321
#define nnodes
Definition: gastrans.c:74
#define narcs
Definition: gastrans.c:77
SCIP_RETCODE SCIPaddCoefLinear(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real val)
SCIP_RETCODE SCIPcreateConsBasicXor(SCIP *scip, SCIP_CONS **cons, const char *name, SCIP_Bool rhs, int nvars, SCIP_VAR **vars)
Definition: cons_xor.c:6003
SCIP_RETCODE SCIPcreateConsBasicLinear(SCIP *scip, SCIP_CONS **cons, const char *name, int nvars, SCIP_VAR **vars, SCIP_Real *vals, SCIP_Real lhs, SCIP_Real rhs)
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_STATUS SCIPgetStatus(SCIP *scip)
Definition: scip_general.c:508
SCIP_RETCODE SCIPaddVar(SCIP *scip, SCIP_VAR *var)
Definition: scip_prob.c:1668
int SCIPgetNVars(SCIP *scip)
Definition: scip_prob.c:1992
SCIP_RETCODE SCIPaddCons(SCIP *scip, SCIP_CONS *cons)
Definition: scip_prob.c:2770
SCIP_VAR ** SCIPgetVars(SCIP *scip)
Definition: scip_prob.c:1947
SCIP_RETCODE SCIPsetObjsense(SCIP *scip, SCIP_OBJSENSE objsense)
Definition: scip_prob.c:1242
SCIP_RETCODE SCIPcreateProbBasic(SCIP *scip, const char *name)
Definition: scip_prob.c:180
void SCIPhashmapFree(SCIP_HASHMAP **hashmap)
Definition: misc.c:3111
SCIP_RETCODE SCIPhashmapCreate(SCIP_HASHMAP **hashmap, BMS_BLKMEM *blkmem, int mapsize)
Definition: misc.c:3077
SCIP_Bool SCIPhashmapExists(SCIP_HASHMAP *hashmap, void *origin)
Definition: misc.c:3426
SCIP_RETCODE SCIPhashmapInsertInt(SCIP_HASHMAP *hashmap, void *origin, int image)
Definition: misc.c:3195
SCIP_RETCODE SCIPlpiChgSides(SCIP_LPI *lpi, int nrows, const int *ind, const SCIP_Real *lhs, const SCIP_Real *rhs)
Definition: lpi_clp.cpp:1167
SCIP_RETCODE SCIPlpiAddRows(SCIP_LPI *lpi, int nrows, const SCIP_Real *lhs, const SCIP_Real *rhs, char **rownames, int nnonz, const int *beg, const int *ind, const SCIP_Real *val)
Definition: lpi_clp.cpp:914
SCIP_RETCODE SCIPlpiChgBounds(SCIP_LPI *lpi, int ncols, const int *ind, const SCIP_Real *lb, const SCIP_Real *ub)
Definition: lpi_clp.cpp:1084
SCIP_RETCODE SCIPlpiFree(SCIP_LPI **lpi)
Definition: lpi_clp.cpp:643
SCIP_RETCODE SCIPlpiGetSol(SCIP_LPI *lpi, SCIP_Real *objval, SCIP_Real *primsol, SCIP_Real *dualsol, SCIP_Real *activity, SCIP_Real *redcost)
Definition: lpi_clp.cpp:2788
SCIP_RETCODE SCIPlpiSolveDual(SCIP_LPI *lpi)
Definition: lpi_clp.cpp:1880
SCIP_RETCODE SCIPlpiAddCols(SCIP_LPI *lpi, int ncols, const SCIP_Real *obj, const SCIP_Real *lb, const SCIP_Real *ub, char **colnames, int nnonz, const int *beg, const int *ind, const SCIP_Real *val)
Definition: lpi_clp.cpp:758
SCIP_RETCODE SCIPlpiSolvePrimal(SCIP_LPI *lpi)
Definition: lpi_clp.cpp:1805
SCIP_RETCODE SCIPlpiCreate(SCIP_LPI **lpi, SCIP_MESSAGEHDLR *messagehdlr, const char *name, SCIP_OBJSEN objsen)
Definition: lpi_clp.cpp:531
SCIP_RETCODE SCIPlpiChgObj(SCIP_LPI *lpi, int ncols, const int *ind, const SCIP_Real *obj)
Definition: lpi_clp.cpp:1240
SCIP_RETCODE SCIPlpiGetNCols(SCIP_LPI *lpi, int *ncols)
Definition: lpi_clp.cpp:1435
SCIP_RETCODE SCIPlpiGetNRows(SCIP_LPI *lpi, int *nrows)
Definition: lpi_clp.cpp:1417
#define SCIPdebugMsgPrint
Definition: scip_message.h:79
SCIP_MESSAGEHDLR * SCIPgetMessagehdlr(SCIP *scip)
Definition: scip_message.c:88
#define SCIPdebugMsg
Definition: scip_message.h:78
void SCIPaddBilinMcCormick(SCIP *scip, SCIP_Real bilincoef, SCIP_Real lbx, SCIP_Real ubx, SCIP_Real refpointx, SCIP_Real lby, SCIP_Real uby, SCIP_Real refpointy, SCIP_Bool overestimate, SCIP_Real *lincoefx, SCIP_Real *lincoefy, SCIP_Real *linconstant, SCIP_Bool *success)
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 SCIPsetHeuristics(SCIP *scip, SCIP_PARAMSETTING paramsetting, SCIP_Bool quiet)
Definition: scip_param.c:927
SCIP_RETCODE SCIPsetIntParam(SCIP *scip, const char *name, int value)
Definition: scip_param.c:487
SCIP_RETCODE SCIPgetRealParam(SCIP *scip, const char *name, SCIP_Real *value)
Definition: scip_param.c:307
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 SCIPsetRealParam(SCIP *scip, const char *name, SCIP_Real value)
Definition: scip_param.c:603
SCIP_RETCODE SCIPreleaseCons(SCIP *scip, SCIP_CONS **cons)
Definition: scip_cons.c:1174
SCIP_RETCODE SCIPaddPoolCut(SCIP *scip, SCIP_ROW *row)
Definition: scip_cut.c:361
SCIP_Real SCIPgetCutEfficacy(SCIP *scip, SCIP_SOL *sol, SCIP_ROW *cut)
Definition: scip_cut.c:94
SCIP_Bool SCIPisCutEfficacious(SCIP *scip, SCIP_SOL *sol, SCIP_ROW *cut)
Definition: scip_cut.c:117
SCIP_RETCODE SCIPaddRow(SCIP *scip, SCIP_ROW *row, SCIP_Bool forcecut, SCIP_Bool *infeasible)
Definition: scip_cut.c:250
void SCIPexprGetQuadraticBilinTerm(SCIP_EXPR *expr, int termidx, SCIP_EXPR **expr1, SCIP_EXPR **expr2, SCIP_Real *coef, int *pos2, SCIP_EXPR **prodexpr)
Definition: expr.c:4204
SCIP_Bool SCIPexprAreQuadraticExprsVariables(SCIP_EXPR *expr)
Definition: expr.c:4240
void SCIPexprGetQuadraticData(SCIP_EXPR *expr, SCIP_Real *constant, int *nlinexprs, SCIP_EXPR ***linexprs, SCIP_Real **lincoefs, int *nquadexprs, int *nbilinexprs, SCIP_Real **eigenvalues, SCIP_Real **eigenvectors)
Definition: expr.c:4119
SCIP_Bool SCIPisExprVar(SCIP *scip, SCIP_EXPR *expr)
Definition: scip_expr.c:1431
SCIP_RETCODE SCIPcheckExprQuadratic(SCIP *scip, SCIP_EXPR *expr, SCIP_Bool *isquadratic)
Definition: scip_expr.c:2377
SCIP_VAR * SCIPgetVarExprVar(SCIP_EXPR *expr)
Definition: expr_var.c:416
void SCIPexprGetQuadraticQuadTerm(SCIP_EXPR *quadexpr, int termidx, SCIP_EXPR **expr, SCIP_Real *lincoef, SCIP_Real *sqrcoef, int *nadjbilin, int **adjbilin, SCIP_EXPR **sqrexpr)
Definition: expr.c:4164
#define SCIPfreeBlockMemoryArray(scip, ptr, num)
Definition: scip_mem.h:110
#define SCIPensureBlockMemoryArray(scip, ptr, arraysizeptr, minsize)
Definition: scip_mem.h:107
#define SCIPallocClearBufferArray(scip, ptr, num)
Definition: scip_mem.h:126
int SCIPcalcMemGrowSize(SCIP *scip, int num)
Definition: scip_mem.c:139
#define SCIPallocBufferArray(scip, ptr, num)
Definition: scip_mem.h:124
#define SCIPfreeBufferArray(scip, ptr)
Definition: scip_mem.h:136
#define SCIPallocBlockMemoryArray(scip, ptr, num)
Definition: scip_mem.h:93
#define SCIPreallocBlockMemoryArray(scip, ptr, oldnum, newnum)
Definition: scip_mem.h:99
#define SCIPfreeBlockMemory(scip, ptr)
Definition: scip_mem.h:108
#define SCIPfreeBlockMemoryArrayNull(scip, ptr, num)
Definition: scip_mem.h:111
#define SCIPallocBlockMemory(scip, ptr)
Definition: scip_mem.h:89
#define SCIPduplicateBlockMemoryArray(scip, ptr, source, num)
Definition: scip_mem.h:105
SCIP_Bool SCIPisNLPConstructed(SCIP *scip)
Definition: scip_nlp.c:110
int SCIPgetNNLPNlRows(SCIP *scip)
Definition: scip_nlp.c:341
SCIP_NLROW ** SCIPgetNLPNlRows(SCIP *scip)
Definition: scip_nlp.c:319
SCIP_Real SCIPnlrowGetRhs(SCIP_NLROW *nlrow)
Definition: nlp.c:1917
SCIP_Real SCIPnlrowGetLhs(SCIP_NLROW *nlrow)
Definition: nlp.c:1907
int SCIPnlrowGetNLinearVars(SCIP_NLROW *nlrow)
Definition: nlp.c:1867
SCIP_VAR ** SCIPnlrowGetLinearVars(SCIP_NLROW *nlrow)
Definition: nlp.c:1877
SCIP_Real SCIPnlrowGetConstant(SCIP_NLROW *nlrow)
Definition: nlp.c:1857
SCIP_EXPR * SCIPnlrowGetExpr(SCIP_NLROW *nlrow)
Definition: nlp.c:1897
SCIP_Bool SCIPnlrowIsInNLP(SCIP_NLROW *nlrow)
Definition: nlp.c:1956
SCIP_Real * SCIPnlrowGetLinearCoefs(SCIP_NLROW *nlrow)
Definition: nlp.c:1887
SCIP_RETCODE SCIPprintNlRow(SCIP *scip, SCIP_NLROW *nlrow, FILE *file)
Definition: scip_nlp.c:1601
SCIP_Real SCIPgetRowMaxCoef(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1922
SCIP_Real SCIPgetRowMinCoef(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1904
SCIP_RETCODE SCIPcacheRowExtensions(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1635
SCIP_RETCODE SCIPflushRowExtensions(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1658
SCIP_RETCODE SCIPaddVarToRow(SCIP *scip, SCIP_ROW *row, SCIP_VAR *var, SCIP_Real val)
Definition: scip_lp.c:1701
SCIP_RETCODE SCIPprintRow(SCIP *scip, SCIP_ROW *row, FILE *file)
Definition: scip_lp.c:2212
const char * SCIProwGetName(SCIP_ROW *row)
Definition: lp.c:17351
SCIP_RETCODE SCIPreleaseRow(SCIP *scip, SCIP_ROW **row)
Definition: scip_lp.c:1562
SCIP_RETCODE SCIPcreateEmptyRowSepa(SCIP *scip, SCIP_ROW **row, SCIP_SEPA *sepa, const char *name, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool removable)
Definition: scip_lp.c:1453
int SCIProwGetRank(SCIP_ROW *row)
Definition: lp.c:17381
SCIP_RETCODE SCIPchgRowRhs(SCIP *scip, SCIP_ROW *row, SCIP_Real rhs)
Definition: scip_lp.c:1607
SCIP_Real SCIPgetRowSolActivity(SCIP *scip, SCIP_ROW *row, SCIP_SOL *sol)
Definition: scip_lp.c:2144
SCIP_RETCODE SCIPincludeSepaBasic(SCIP *scip, SCIP_SEPA **sepa, const char *name, const char *desc, int priority, int freq, SCIP_Real maxbounddist, SCIP_Bool usessubscip, SCIP_Bool delay, SCIP_DECL_SEPAEXECLP((*sepaexeclp)), SCIP_DECL_SEPAEXECSOL((*sepaexecsol)), SCIP_SEPADATA *sepadata)
Definition: scip_sepa.c:109
const char * SCIPsepaGetName(SCIP_SEPA *sepa)
Definition: sepa.c:743
int SCIPsepaGetNCallsAtNode(SCIP_SEPA *sepa)
Definition: sepa.c:880
SCIP_RETCODE SCIPsetSepaFree(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAFREE((*sepafree)))
Definition: scip_sepa.c:167
SCIP_RETCODE SCIPsetSepaExitsol(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAEXITSOL((*sepaexitsol)))
Definition: scip_sepa.c:231
SCIP_SEPADATA * SCIPsepaGetData(SCIP_SEPA *sepa)
Definition: sepa.c:633
void SCIPsepaSetData(SCIP_SEPA *sepa, SCIP_SEPADATA *sepadata)
Definition: sepa.c:643
SCIP_RETCODE SCIPsetSepaCopy(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPACOPY((*sepacopy)))
Definition: scip_sepa.c:151
SCIP_SOL * SCIPgetBestSol(SCIP *scip)
Definition: scip_sol.c:2165
SCIP_RETCODE SCIPprintSol(SCIP *scip, SCIP_SOL *sol, FILE *file, SCIP_Bool printzeros)
Definition: scip_sol.c:1627
int SCIPgetNSols(SCIP *scip)
Definition: scip_sol.c:2066
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1213
SCIP_RETCODE SCIPfreeTransform(SCIP *scip)
Definition: scip_solve.c:3350
SCIP_RETCODE SCIPsolve(SCIP *scip)
Definition: scip_solve.c:2502
SCIP_Real SCIPgetSolvingTime(SCIP *scip)
Definition: scip_timing.c:378
SCIP_Real SCIPgetTotalTime(SCIP *scip)
Definition: scip_timing.c:351
SCIP_Real SCIPinfinity(SCIP *scip)
SCIP_Bool SCIPisGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisPositive(SCIP *scip, SCIP_Real val)
SCIP_Bool SCIPisLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisInfinity(SCIP *scip, SCIP_Real val)
SCIP_Bool SCIPisGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisNegative(SCIP *scip, SCIP_Real val)
SCIP_Bool SCIPisEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisZero(SCIP *scip, SCIP_Real val)
SCIP_Bool SCIPisLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
int SCIPgetDepth(SCIP *scip)
Definition: scip_tree.c:672
SCIP_Real SCIPvarGetUbLocal(SCIP_VAR *var)
Definition: var.c:18143
SCIP_RETCODE SCIPchgVarUb(SCIP *scip, SCIP_VAR *var, SCIP_Real newbound)
Definition: scip_var.c:4889
SCIP_Real SCIPvarGetUbGlobal(SCIP_VAR *var)
Definition: var.c:18087
int SCIPvarGetIndex(SCIP_VAR *var)
Definition: var.c:17757
const char * SCIPvarGetName(SCIP_VAR *var)
Definition: var.c:17418
SCIP_RETCODE SCIPreleaseVar(SCIP *scip, SCIP_VAR **var)
Definition: scip_var.c:1248
SCIP_Bool SCIPvarIsIntegral(SCIP_VAR *var)
Definition: var.c:17609
SCIP_Real SCIPvarGetLbLocal(SCIP_VAR *var)
Definition: var.c:18133
SCIP_Real SCIPvarGetLbGlobal(SCIP_VAR *var)
Definition: var.c:18077
SCIP_RETCODE SCIPcreateVarBasic(SCIP *scip, SCIP_VAR **var, const char *name, SCIP_Real lb, SCIP_Real ub, SCIP_Real obj, SCIP_VARTYPE vartype)
Definition: scip_var.c:194
SCIP_RETCODE SCIPincludeSepaEccuts(SCIP *scip)
Definition: sepa_eccuts.c:3134
int SCIPsnprintf(char *t, int len, const char *s,...)
Definition: misc.c:10880
#define BMSclearMemory(ptr)
Definition: memory.h:129
#define BMSclearMemoryArray(ptr, num)
Definition: memory.h:130
BMS_BLKMEM * SCIPblkmem(SCIP *scip)
Definition: scip_mem.c:57
internal methods for NLP management
#define SCIPerrorMessage
Definition: pub_message.h:64
#define SCIPstatisticMessage
Definition: pub_message.h:123
#define SCIPdebug(x)
Definition: pub_message.h:93
#define SCIPdebugMessage
Definition: pub_message.h:96
#define SCIPstatistic(x)
Definition: pub_message.h:120
SCIP_RETCODE SCIPincludeDefaultPlugins(SCIP *scip)
default SCIP plugins
#define SEPA_PRIORITY
Definition: sepa_eccuts.c:47
#define CLIQUE_MINWEIGHT
Definition: sepa_eccuts.c:55
static SCIP_RETCODE doSeachEcAggr(SCIP *scip, SCIP *subscip, SCIP_SEPADATA *sepadata, SCIP_NLROW *nlrow, SCIP_SOL *sol, SCIP_Bool rhsaggr, int *quadvar2aggr, int *nfound)
Definition: sepa_eccuts.c:1552
static SCIP_RETCODE ecaggrAddBilinTerm(SCIP *scip, SCIP_ECAGGR *ecaggr, SCIP_VAR *x, SCIP_VAR *y, SCIP_Real coef)
Definition: sepa_eccuts.c:237
static SCIP_RETCODE sepadataCreate(SCIP *scip, SCIP_SEPADATA **sepadata)
Definition: sepa_eccuts.c:728
static SCIP_RETCODE searchEcAggrWithMIP(SCIP *subscip, SCIP_Real timelimit, int nedges, SCIP_Bool *aggrleft, SCIP_Bool *found)
Definition: sepa_eccuts.c:1246
#define SEPA_DELAY
Definition: sepa_eccuts.c:51
static SCIP_RETCODE nlrowaggrCreate(SCIP *scip, SCIP_NLROW *nlrow, SCIP_NLROWAGGR **nlrowaggr, int *quadvar2aggr, int nfound, SCIP_Bool rhsaggr)
Definition: sepa_eccuts.c:430
static SCIP_DECL_SEPAFREE(sepaFreeEccuts)
Definition: sepa_eccuts.c:3022
static SCIP_RETCODE ecaggrAddQuadvar(SCIP_ECAGGR *ecaggr, SCIP_VAR *x)
Definition: sepa_eccuts.c:226
#define USEDUALSIMPLEX
Definition: sepa_eccuts.c:76
#define ADJUSTFACETTOL
Definition: sepa_eccuts.c:75
static SCIP_Real transformValue(SCIP *scip, SCIP_Real lb, SCIP_Real ub, SCIP_Real val)
Definition: sepa_eccuts.c:2239
#define CLIQUE_MAXFIRSTNODEWEIGHT
Definition: sepa_eccuts.c:53
static SCIP_RETCODE separateCuts(SCIP *scip, SCIP_SEPA *sepa, SCIP_SEPADATA *sepadata, int depth, SCIP_SOL *sol, SCIP_RESULT *result)
Definition: sepa_eccuts.c:2932
#define DEFAULT_DYNAMICCUTS
Definition: sepa_eccuts.c:59
static SCIP_RETCODE addFacetToCut(SCIP *scip, SCIP_SOL *sol, SCIP_ROW *cut, SCIP_Real *facet, SCIP_VAR **vars, int nvars, SCIP_Real *cutconstant, SCIP_Real *cutactivity, SCIP_Bool *success)
Definition: sepa_eccuts.c:2491
static SCIP_RETCODE sepadataAddNlrowaggr(SCIP *scip, SCIP_SEPADATA *sepadata, SCIP_NLROWAGGR *nlrowaggr)
Definition: sepa_eccuts.c:800
static SCIP_RETCODE findAndStoreEcAggregations(SCIP *scip, SCIP_SEPADATA *sepadata, SCIP_NLROW *nlrow, SCIP_SOL *sol)
Definition: sepa_eccuts.c:1913
#define SEPA_DESC
Definition: sepa_eccuts.c:46
static SCIP_RETCODE nlrowaggrAddLinearTerm(SCIP *scip, SCIP_NLROWAGGR *nlrowaggr, SCIP_VAR *linvar, SCIP_Real lincoef)
Definition: sepa_eccuts.c:352
#define DEFAULT_MAXROUNDSROOT
Definition: sepa_eccuts.c:61
static SCIP_RETCODE updateMIP(SCIP *subscip, SCIP_NLROW *nlrow, SCIP_VAR **forwardarcs, SCIP_VAR **backwardarcs, int *quadvar2aggr, int *nedges)
Definition: sepa_eccuts.c:1083
#define SEPA_USESSUBSCIP
Definition: sepa_eccuts.c:50
static SCIP_RETCODE searchEcAggr(SCIP *scip, SCIP_SEPADATA *sepadata, SCIP_NLROW *nlrow, SCIP_SOL *sol, SCIP_Bool rhsaggr, int *quadvar2aggr, int *nfound)
Definition: sepa_eccuts.c:1749
static SCIP_RETCODE nlrowaggrAddQuadraticVar(SCIP *scip, SCIP_NLROWAGGR *nlrowaggr, SCIP_VAR *quadvar)
Definition: sepa_eccuts.c:385
static SCIP_RETCODE addBilinearTermToCut(SCIP *scip, SCIP_SOL *sol, SCIP_ROW *cut, SCIP_VAR *x, SCIP_VAR *y, SCIP_Real coeff, SCIP_Real *cutconstant, SCIP_Real *cutactivity, SCIP_Bool *success)
Definition: sepa_eccuts.c:2600
#define DEFAULT_MAXDEPTH
Definition: sepa_eccuts.c:62
static SCIP_Bool isPossibleToComputeCut(SCIP *scip, SCIP_SOL *sol, SCIP_NLROWAGGR *nlrowaggr)
Definition: sepa_eccuts.c:2889
static SCIP_Real phi(SCIP *scip, SCIP_Real val, SCIP_Real lb, SCIP_Real ub)
Definition: sepa_eccuts.c:844
#define DEFAULT_MINVIOLATION
Definition: sepa_eccuts.c:67
static SCIP_RETCODE sepadataFreeNlrows(SCIP *scip, SCIP_SEPADATA *sepadata)
Definition: sepa_eccuts.c:744
#define CLIQUE_BACKTRACKFREQ
Definition: sepa_eccuts.c:57
#define CLIQUE_MAXNTREENODES
Definition: sepa_eccuts.c:56
static SCIP_RETCODE nlrowaggrFree(SCIP *scip, SCIP_NLROWAGGR **nlrowaggr)
Definition: sepa_eccuts.c:652
static SCIP_RETCODE nlrowaggrAddRemBilinTerm(SCIP_NLROWAGGR *nlrowaggr, SCIP_VAR *x, SCIP_VAR *y, SCIP_Real coef)
Definition: sepa_eccuts.c:405
static SCIP_RETCODE addLinearTermToCut(SCIP *scip, SCIP_SOL *sol, SCIP_ROW *cut, SCIP_VAR *x, SCIP_Real coeff, SCIP_Real *cutconstant, SCIP_Real *cutactivity, SCIP_Bool *success)
Definition: sepa_eccuts.c:2549
static SCIP_RETCODE storeAggrFromMIP(SCIP *subscip, SCIP_NLROW *nlrow, SCIP_VAR **forwardarcs, SCIP_VAR **backwardarcs, int *quadvar2aggr, int nfoundsofar)
Definition: sepa_eccuts.c:1162
static SCIP_DECL_SEPAEXITSOL(sepaExitsolEccuts)
Definition: sepa_eccuts.c:3037
#define DEFAULT_MAXSEPACUTSROOT
Definition: sepa_eccuts.c:64
static SCIP_DECL_SEPACOPY(sepaCopyEccuts)
Definition: sepa_eccuts.c:3008
static SCIP_DECL_SEPAEXECLP(sepaExeclpEccuts)
Definition: sepa_eccuts.c:3064
static SCIP_RETCODE computeCut(SCIP *scip, SCIP_SEPA *sepa, SCIP_SEPADATA *sepadata, SCIP_NLROWAGGR *nlrowaggr, SCIP_SOL *sol, SCIP_Bool *separated, SCIP_Bool *cutoff)
Definition: sepa_eccuts.c:2714
static SCIP_RETCODE sepadataFree(SCIP *scip, SCIP_SEPADATA **sepadata)
Definition: sepa_eccuts.c:774
#define DEFAULT_MAXAGGRSIZE
Definition: sepa_eccuts.c:69
static SCIP_RETCODE createTcliqueGraph(SCIP_NLROW *nlrow, TCLIQUE_GRAPH **graph, SCIP_Real *nodeweights)
Definition: sepa_eccuts.c:1312
static SCIP_RETCODE ecaggrFree(SCIP *scip, SCIP_ECAGGR **ecaggr)
Definition: sepa_eccuts.c:205
#define SEPA_MAXBOUNDDIST
Definition: sepa_eccuts.c:49
static SCIP_RETCODE createLP(SCIP *scip, SCIP_SEPADATA *sepadata)
Definition: sepa_eccuts.c:2089
#define DEFAULT_MINAGGRSIZE
Definition: sepa_eccuts.c:68
static SCIP_RETCODE computeConvexEnvelopeFacet(SCIP *scip, SCIP_SEPADATA *sepadata, SCIP_SOL *sol, SCIP_ECAGGR *ecaggr, SCIP_Real *facet, SCIP_Real *facetval, SCIP_Bool *success)
Definition: sepa_eccuts.c:2283
#define SEPA_FREQ
Definition: sepa_eccuts.c:48
static SCIP_RETCODE createMIP(SCIP *scip, SCIP *subscip, SCIP_SEPADATA *sepadata, SCIP_NLROW *nlrow, SCIP_Bool rhsaggr, SCIP_VAR **forwardarcs, SCIP_VAR **backwardarcs, SCIP_Real *nodeweights, int *nedges, int *narcs)
Definition: sepa_eccuts.c:869
static SCIP_Bool checkRikun(SCIP *scip, SCIP_ECAGGR *ecaggr, SCIP_Real *fvals, SCIP_Real *facet)
Definition: sepa_eccuts.c:2018
#define DEFAULT_MAXSEPACUTS
Definition: sepa_eccuts.c:63
#define SEPA_NAME
Definition: sepa_eccuts.c:45
#define DEFAULT_MAXSTALLROUNDS
Definition: sepa_eccuts.c:71
#define SUBSCIP_NODELIMIT
Definition: sepa_eccuts.c:73
#define DEFAULT_MAXBILINTERMS
Definition: sepa_eccuts.c:70
#define DEFAULT_MAXROUNDS
Definition: sepa_eccuts.c:60
static SCIP_RETCODE searchEcAggrWithCliques(SCIP *scip, TCLIQUE_GRAPH *graph, SCIP_SEPADATA *sepadata, SCIP_NLROW *nlrow, int *quadvar2aggr, int nfoundsofar, SCIP_Bool rhsaggr, SCIP_Bool *foundaggr, SCIP_Bool *foundclique)
Definition: sepa_eccuts.c:1403
static SCIP_RETCODE ecaggrCreateEmpty(SCIP *scip, SCIP_ECAGGR **ecaggr, int nquadvars, int nquadterms)
Definition: sepa_eccuts.c:175
static SCIP_Real evalCorner(SCIP_ECAGGR *ecaggr, int k)
Definition: sepa_eccuts.c:2201
#define DEFAULT_CUTMAXRANGE
Definition: sepa_eccuts.c:65
static SCIP_RETCODE isCandidate(SCIP *scip, SCIP_SEPADATA *sepadata, SCIP_NLROW *nlrow, SCIP_Bool *rhscandidate, SCIP_Bool *lhscandidate)
Definition: sepa_eccuts.c:1782
static const int poweroftwo[]
Definition: sepa_eccuts.c:79
static SCIP_RETCODE nlrowaggrStoreLinearTerms(SCIP *scip, SCIP_NLROWAGGR *nlrowaggr, SCIP_VAR **linvars, SCIP_Real *lincoefs, int nlinvars)
Definition: sepa_eccuts.c:311
edge concave cut separator
int * termvars1
Definition: sepa_eccuts.c:95
int termsize
Definition: sepa_eccuts.c:98
SCIP_Real * termcoefs
Definition: sepa_eccuts.c:94
int * termvars2
Definition: sepa_eccuts.c:96
int nterms
Definition: sepa_eccuts.c:97
SCIP_VAR ** vars
Definition: sepa_eccuts.c:90
int varsize
Definition: sepa_eccuts.c:92
int nvars
Definition: sepa_eccuts.c:91
SCIP_VAR ** linvars
Definition: sepa_eccuts.c:112
int linvarssize
Definition: sepa_eccuts.c:115
int remtermsize
Definition: sepa_eccuts.c:127
SCIP_VAR ** remtermvars2
Definition: sepa_eccuts.c:124
SCIP_Real * lincoefs
Definition: sepa_eccuts.c:113
SCIP_Bool rhsaggr
Definition: sepa_eccuts.c:106
SCIP_Real * remtermcoefs
Definition: sepa_eccuts.c:125
int quadvarssize
Definition: sepa_eccuts.c:121
int * quadvar2aggr
Definition: sepa_eccuts.c:118
SCIP_Real constant
Definition: sepa_eccuts.c:130
SCIP_VAR ** quadvars
Definition: sepa_eccuts.c:117
SCIP_Real rhs
Definition: sepa_eccuts.c:129
int nquadvars
Definition: sepa_eccuts.c:120
int nlinvars
Definition: sepa_eccuts.c:114
SCIP_NLROW * nlrow
Definition: sepa_eccuts.c:105
SCIP_ECAGGR ** ecaggr
Definition: sepa_eccuts.c:109
int nremterms
Definition: sepa_eccuts.c:126
SCIP_VAR ** remtermvars1
Definition: sepa_eccuts.c:123
SCIP_Real rhs
Definition: struct_nlp.h:68
tclique user interface
@ TCLIQUE_OPTIMAL
Definition: tclique.h:66
void tcliqueChangeWeight(TCLIQUE_GRAPH *tcliquegraph, int node, TCLIQUE_WEIGHT weight)
void tcliqueFree(TCLIQUE_GRAPH **tcliquegraph)
enum TCLIQUE_Status TCLIQUE_STATUS
Definition: tclique.h:68
void tcliqueMaxClique(TCLIQUE_GETNNODES((*getnnodes)), TCLIQUE_GETWEIGHTS((*getweights)), TCLIQUE_ISEDGE((*isedge)), TCLIQUE_SELECTADJNODES((*selectadjnodes)), TCLIQUE_GRAPH *tcliquegraph, TCLIQUE_NEWSOL((*newsol)), TCLIQUE_DATA *tcliquedata, int *maxcliquenodes, int *nmaxcliquenodes, TCLIQUE_WEIGHT *maxcliqueweight, TCLIQUE_WEIGHT maxfirstnodeweight, TCLIQUE_WEIGHT minweight, int maxntreenodes, int backtrackfreq, int maxnzeroextensions, int fixednode, int *ntreenodes, TCLIQUE_STATUS *status)
TCLIQUE_Bool tcliqueFlush(TCLIQUE_GRAPH *tcliquegraph)
struct TCLIQUE_Graph TCLIQUE_GRAPH
Definition: tclique.h:49
TCLIQUE_Bool tcliqueCreate(TCLIQUE_GRAPH **tcliquegraph)
TCLIQUE_Bool tcliqueAddNode(TCLIQUE_GRAPH *tcliquegraph, int node, TCLIQUE_WEIGHT weight)
TCLIQUE_Bool tcliqueAddEdge(TCLIQUE_GRAPH *tcliquegraph, int node1, int node2)
@ SCIP_OBJSEN_MINIMIZE
Definition: type_lpi.h:43
@ SCIP_PARAMSETTING_AGGRESSIVE
Definition: type_paramset.h:61
@ SCIP_OBJSENSE_MAXIMIZE
Definition: type_prob.h:47
@ SCIP_DIDNOTRUN
Definition: type_result.h:42
@ SCIP_CUTOFF
Definition: type_result.h:48
@ SCIP_DIDNOTFIND
Definition: type_result.h:44
@ SCIP_SEPARATED
Definition: type_result.h:49
enum SCIP_Result SCIP_RESULT
Definition: type_result.h:61
@ SCIP_PARAMETERWRONGVAL
Definition: type_retcode.h:57
@ SCIP_OKAY
Definition: type_retcode.h:42
@ SCIP_ERROR
Definition: type_retcode.h:43
enum SCIP_Retcode SCIP_RETCODE
Definition: type_retcode.h:63
struct SCIP_SepaData SCIP_SEPADATA
Definition: type_sepa.h:52
@ SCIP_STATUS_INFEASIBLE
Definition: type_stat.h:62
@ SCIP_VARTYPE_BINARY
Definition: type_var.h:62