Scippy

SCIP

Solving Constraint Integer Programs

nlhdlr_quotient.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 nlhdlr_quotient.c
26 * @ingroup DEFPLUGINS_NLHDLR
27 * @brief quotient nonlinear handler
28 * @author Benjamin Mueller
29 * @author Fabian Wegscheider
30 *
31 * @todo implement INITSEPA
32 * @todo use the convex envelope for x/y described in Tawarmalani and Sahinidis (2002) if y has a finite upper bound
33 */
34
35#include <string.h>
36
38#include "scip/cons_nonlinear.h"
40#include "scip/nlhdlr.h"
42
43/* fundamental nonlinear handler properties */
44#define NLHDLR_NAME "quotient"
45#define NLHDLR_DESC "nonlinear handler for quotient expressions"
46#define NLHDLR_DETECTPRIORITY 20
47#define NLHDLR_ENFOPRIORITY 20
48
49/** translate from one value of infinity to another
50 *
51 * if val is &ge; infty1, then give infty2, else give val
52 */
53#define infty2infty(infty1, infty2, val) ((val) >= (infty1) ? (infty2) : (val))
54
55/*lint -e666*/
56
57/*
58 * Data structures
59 */
60
61/** nonlinear handler expression data */
62struct SCIP_NlhdlrExprData
63{
64 SCIP_EXPR* numexpr; /**< expression of the numerator */
65 SCIP_Real numcoef; /**< coefficient of the numerator */
66 SCIP_Real numconst; /**< constant of the numerator */
67 SCIP_EXPR* denomexpr; /**< expression of the denominator */
68 SCIP_Real denomcoef; /**< coefficient of the denominator */
69 SCIP_Real denomconst; /**< constant of the denominator */
70 SCIP_Real constant; /**< constant */
71};
72
73/*
74 * Local methods
75 */
76
77/** helper method to create nonlinear handler expression data */
78static
80 SCIP* scip, /**< SCIP data structure */
81 SCIP_NLHDLREXPRDATA** nlhdlrexprdata, /**< nonlinear handler expression data */
82 SCIP_EXPR* numexpr, /**< expression of the numerator */
83 SCIP_Real numcoef, /**< coefficient of the numerator */
84 SCIP_Real numconst, /**< constant of the numerator */
85 SCIP_EXPR* denomexpr, /**< expression of the denominator */
86 SCIP_Real denomcoef, /**< coefficient of the denominator */
87 SCIP_Real denomconst, /**< constant of the denominator */
88 SCIP_Real constant /**< constant */
89 )
90{
91 assert(nlhdlrexprdata != NULL);
92 assert(numexpr != NULL);
93 assert(denomexpr != NULL);
94 assert(!SCIPisZero(scip, numcoef));
95 assert(!SCIPisZero(scip, denomcoef));
96
97 /* allocate memory */
98 SCIP_CALL( SCIPallocBlockMemory(scip, nlhdlrexprdata) );
99
100 /* store values */
101 (*nlhdlrexprdata)->numexpr = numexpr;
102 (*nlhdlrexprdata)->numcoef = numcoef;
103 (*nlhdlrexprdata)->numconst = numconst;
104 (*nlhdlrexprdata)->denomexpr = denomexpr;
105 (*nlhdlrexprdata)->denomcoef = denomcoef;
106 (*nlhdlrexprdata)->denomconst = denomconst;
107 (*nlhdlrexprdata)->constant = constant;
108
109 /* capture expressions */
110 SCIPcaptureExpr(numexpr);
111 SCIPcaptureExpr(denomexpr);
112
113 return SCIP_OKAY;
114}
115
116/** helper method to free nonlinear handler expression data */
117static
119 SCIP* scip, /**< SCIP data structure */
120 SCIP_NLHDLREXPRDATA** nlhdlrexprdata /**< nonlinear handler expression data */
121 )
122{
123 assert(nlhdlrexprdata != NULL);
124 assert(*nlhdlrexprdata != NULL);
125 assert((*nlhdlrexprdata)->numexpr != NULL);
126 assert((*nlhdlrexprdata)->denomexpr != NULL);
127
128 /* release expressions */
129 SCIP_CALL( SCIPreleaseExpr(scip, &(*nlhdlrexprdata)->denomexpr) );
130 SCIP_CALL( SCIPreleaseExpr(scip, &(*nlhdlrexprdata)->numexpr) );
131
132 /* free expression data of nonlinear handler */
133 SCIPfreeBlockMemory(scip, nlhdlrexprdata);
134
135 return SCIP_OKAY;
136}
137
138/** helper method to transform an expression g(x) into a*f(x) + b */
139static
141 SCIP* scip, /**< SCIP data structure */
142 SCIP_EXPR* expr, /**< expression */
143 SCIP_EXPR** target, /**< pointer to store the expression f(x) */
144 SCIP_Real* coef, /**< pointer to store the coefficient */
145 SCIP_Real* constant /**< pointer to store the constant */
146 )
147{
148 assert(expr != NULL);
149 assert(target != NULL);
150 assert(coef != NULL);
151 assert(constant != NULL);
152
153 /* expression is a sum with one child */
154 if( SCIPisExprSum(scip, expr) && SCIPexprGetNChildren(expr) == 1 )
155 {
156 *target = SCIPexprGetChildren(expr)[0];
157 *coef = SCIPgetCoefsExprSum(expr)[0];
158 *constant = SCIPgetConstantExprSum(expr);
159 }
160 else /* otherwise return 1 * f(x) + 0 */
161 {
162 *target = expr;
163 *coef = 1.0;
164 *constant = 0.0;
165 }
166}
167
168/** helper method to detect an expression of the form (a*x + b) / (c*y + d) + e
169 *
170 * Due to the expansion of products, there are two types of expressions that can be detected:
171 *
172 * 1. prod(f(x), pow(g(y),-1))
173 * 2. sum(prod(f(x),pow(g(y),-1)), pow(g(y),-1))
174 *
175 * @todo At the moment quotients like xy / z are not detected, because they are turned into a product expression
176 * with three children, i.e., x * y * (1 / z).
177 */
178static
180 SCIP* scip, /**< SCIP data structure */
181 SCIP_EXPR* expr, /**< expression */
182 SCIP_NLHDLREXPRDATA** nlhdlrexprdata, /**< pointer to store nonlinear handler expression data */
183 SCIP_Bool* success /**< pointer to store whether nonlinear handler should be called for this expression */
184 )
185{
186 SCIP_EXPR** children;
187 SCIP_EXPR* denomexpr = NULL;
188 SCIP_EXPR* numexpr = NULL;
189 SCIP_EXPR* xexpr = NULL;
190 SCIP_EXPR* yexpr = NULL;
191 SCIP_Real a, b, c, d, e;
192 SCIP_Real nomfac = 1.0;
193 SCIP_Real numconst = 0.0;
194
195 assert(scip != NULL);
196 assert(expr != NULL);
197
198 *success = FALSE;
199 a = 0.0;
200 b = 0.0;
201 c = 0.0;
202 d = 0.0;
203 e = 0.0;
204
205 /* possible structures only have two children */
206 if( SCIPexprGetNChildren(expr) != 2 )
207 return SCIP_OKAY;
208
209 /* expression must be either a product or a sum */
210 if( !SCIPisExprProduct(scip, expr) && !SCIPisExprSum(scip, expr) )
211 return SCIP_OKAY;
212
213 children = SCIPexprGetChildren(expr);
214 assert(children != NULL);
215
216 /* case: prod(f(x), pow(g(y),-1)) */
217 if( SCIPisExprProduct(scip, expr) )
218 {
219 if( SCIPisExprPower(scip, children[0]) && SCIPgetExponentExprPow(children[0]) == -1.0 ) /*lint !e777*/
220 {
221 denomexpr = SCIPexprGetChildren(children[0])[0];
222 numexpr = children[1];
223 }
224 else if( SCIPisExprPower(scip, children[1]) && SCIPgetExponentExprPow(children[1]) == -1.0 ) /*lint !e777*/
225 {
226 denomexpr = SCIPexprGetChildren(children[1])[0];
227 numexpr = children[0];
228 }
229
230 /* remember to scale the numerator by the coefficient stored in the product expression */
231 nomfac = SCIPgetCoefExprProduct(expr);
232 }
233 /* case: sum(prod(f(x),pow(g(y),-1)), pow(g(y),-1)) */
234 else
235 {
236 SCIP_Real* sumcoefs;
237
238 assert(SCIPisExprSum(scip, expr));
239 sumcoefs = SCIPgetCoefsExprSum(expr);
240
241 /* children[0] is 1/g(y) and children[1] is a product of f(x) and 1/g(y) */
242 if( SCIPisExprPower(scip, children[0]) && SCIPgetExponentExprPow(children[0]) == -1.0
243 && SCIPisExprProduct(scip, children[1]) && SCIPexprGetNChildren(children[1]) == 2 ) /* lint !e777 */
244 {
245 SCIP_Real prodcoef = SCIPgetCoefExprProduct(children[1]);
246
247 if( children[0] == SCIPexprGetChildren(children[1])[0] )
248 {
249 denomexpr = SCIPexprGetChildren(children[0])[0];
250 numexpr = SCIPexprGetChildren(children[1])[1];
251 }
252 else if( children[0] == SCIPexprGetChildren(children[1])[1] )
253 {
254 denomexpr = SCIPexprGetChildren(children[0])[0];
255 numexpr = SCIPexprGetChildren(children[1])[0];
256 }
257
258 /* remember scalar and constant for numerator */
259 nomfac = sumcoefs[1] * prodcoef;
260 numconst = sumcoefs[0];
261 }
262 /* children[1] is 1/g(y) and children[0] is a product of f(x) and 1/g(y) */
263 else if( SCIPisExprPower(scip, children[1]) && SCIPgetExponentExprPow(children[1]) == -1.0
264 && SCIPisExprProduct(scip, children[0]) && SCIPexprGetNChildren(children[0]) == 2 ) /* lint !e777 */
265 {
266 SCIP_Real prodcoef = SCIPgetCoefExprProduct(children[0]);
267
268 if( children[1] == SCIPexprGetChildren(children[0])[0] )
269 {
270 denomexpr = SCIPexprGetChildren(children[1])[0];
271 numexpr = SCIPexprGetChildren(children[0])[1];
272 }
273 else if( children[1] == SCIPexprGetChildren(children[0])[1] )
274 {
275 denomexpr = SCIPexprGetChildren(children[1])[0];
276 numexpr = SCIPexprGetChildren(children[0])[0];
277 }
278
279 /* remember scalar and constant for numerator */
280 nomfac = sumcoefs[0] * prodcoef;
281 numconst = sumcoefs[1];
282 }
283
284 /* remember the constant of the sum expression */
285 e = SCIPgetConstantExprSum(expr);
286 }
287
288 if( denomexpr != NULL && numexpr != NULL )
289 {
290 /* transform numerator and denominator to detect structures like (a * f(x) + b) / (c * f(x) + d) */
291 transformExpr(scip, numexpr, &xexpr, &a, &b);
292 transformExpr(scip, denomexpr, &yexpr, &c, &d);
293
294 SCIPdebugMsg(scip, "detected numerator (%g * %p + %g) and denominator (%g * %p + %g)\n", a, (void*)xexpr, b,
295 c, (void*)yexpr, d);
296
297 /* detection is only be successful if the expression of the numerator an denominator are the same
298 * (so boundtightening can be stronger than default) or we are going to provide estimators (there will be an auxvar)
299 */
300 *success = (xexpr == yexpr) || (SCIPgetExprNAuxvarUsesNonlinear(expr) > 0);
301
302#ifdef SCIP_DEBUG
303 SCIPinfoMessage(scip, NULL, "Expression for numerator: ");
304 SCIP_CALL( SCIPprintExpr(scip, xexpr, NULL) );
305 SCIPinfoMessage(scip, NULL, "\nExpression for denominator: ");
306 SCIP_CALL( SCIPprintExpr(scip, yexpr, NULL) );
307 SCIPinfoMessage(scip, NULL, "\n");
308#endif
309 }
310
311 /* register usage of xexpr and yexpr
312 * create nonlinear handler expression data
313 */
314 if( *success )
315 {
316 assert(xexpr != NULL);
317 assert(xexpr != NULL);
318 assert(a != 0.0);
319 assert(c != 0.0);
320
321 assert(SCIPgetExprNAuxvarUsesNonlinear(expr) > 0 || xexpr == yexpr);
322
323 /* request auxiliary variables for xexpr and yexpr if we will estimate
324 * mark that the bounds of the expression are important to construct the estimators
325 * (TODO check the curvature of the univariate quotient, as bounds may actually not be used)
326 * if univariate, then we also do inteval and reverseprop, so mark that the activities will be used for inteval
327 */
330 xexpr == yexpr,
333
334 if( xexpr != yexpr && SCIPgetExprNAuxvarUsesNonlinear(expr) > 0 )
335 {
337 }
338
339 a = nomfac * a;
340 b = nomfac * b + numconst;
341
344 SCIPdebugMsg(scip, "detected quotient expression (%g * %p + %g) / (%g * %p + %g) + %g\n", a, (void*)xexpr,
345 b, c, (void*)yexpr, d, e);
346 SCIP_CALL( exprdataCreate(scip, nlhdlrexprdata, xexpr, a, b, yexpr, c, d, e) );
347 }
348
349 return SCIP_OKAY;
350}
351
352/** helper method to compute interval for (a x + b) / (c x + d) + e */
353static
355 SCIP* scip, /**< SCIP data structure */
356 SCIP_INTERVAL bnds, /**< bounds on x */
357 SCIP_Real a, /**< coefficient in numerator */
358 SCIP_Real b, /**< constant in numerator */
359 SCIP_Real c, /**< coefficient in denominator */
360 SCIP_Real d, /**< constant in denominator */
361 SCIP_Real e /**< constant */
362 )
363{
364 SCIP_INTERVAL result;
365 SCIP_INTERVAL denominterval;
366 SCIP_INTERVAL numinterval;
367 int i;
368
369 assert(scip != NULL);
370
371 /* return empty interval if the domain of x is empty */
373 {
374 SCIPintervalSetEmpty(&result);
375 return result;
376 }
377
378 /* compute bounds for denominator */
379 SCIPintervalMulScalar(SCIP_INTERVAL_INFINITY, &denominterval, bnds, c);
380 SCIPintervalAddScalar(SCIP_INTERVAL_INFINITY, &denominterval, denominterval, d);
381
382 /* there is no useful interval if 0 is in the interior of the interval of the denominator */
383 if( SCIPintervalGetInf(denominterval) < 0.0 && SCIPintervalGetSup(denominterval) > 0.0 )
384 {
386 return result;
387 }
388
389 /* a d = b c implies that f(x) = b / d + e, i.e., f is constant */
390 if( a*d - b*c == 0.0 )
391 {
392 SCIPintervalSet(&result, b / d + e);
393 return result;
394 }
395
396 /*
397 * evaluate for [x.inf,x.inf] and [x.sup,x.sup] independently
398 */
399 SCIPintervalSetEmpty(&result);
400
401 for( i = 0; i < 2; ++i )
402 {
403 SCIP_INTERVAL quotinterval;
404 SCIP_Real val = (i == 0) ? bnds.inf : bnds.sup;
405
406 /* set the resulting interval to a / c if the bounds is infinite */
407 if( SCIPisInfinity(scip, REALABS(val)) )
408 {
409 SCIPintervalSet(&quotinterval, a);
410 SCIPintervalDivScalar(SCIP_INTERVAL_INFINITY, &quotinterval, quotinterval, c);
411 }
412 else
413 {
414 /* a x' + b */
415 SCIPintervalSet(&numinterval, val);
416 SCIPintervalMulScalar(SCIP_INTERVAL_INFINITY, &numinterval, numinterval, a);
417 SCIPintervalAddScalar(SCIP_INTERVAL_INFINITY, &numinterval, numinterval, b);
418
419 /* c x' + d */
420 SCIPintervalSet(&denominterval, val);
421 SCIPintervalMulScalar(SCIP_INTERVAL_INFINITY, &denominterval, denominterval, c);
422 SCIPintervalAddScalar(SCIP_INTERVAL_INFINITY, &denominterval, denominterval, d);
423
424 /* (a x' + b) / (c x' + d) + e */
425 SCIPintervalDiv(SCIP_INTERVAL_INFINITY, &quotinterval, numinterval, denominterval);
426 SCIPintervalAddScalar(SCIP_INTERVAL_INFINITY, &quotinterval, quotinterval, e);
427 }
428
429 /* unify with the resulting interval */
430 SCIPintervalUnify(&result, result, quotinterval);
431 }
432
433 return result;
434}
435
436/** helper method to compute reverse propagation for (a x + b) / (c x + d) + e */
437static
439 SCIP_INTERVAL bnds, /**< bounds on (a x + b) / (c x + d) + e */
440 SCIP_Real a, /**< coefficient in numerator */
441 SCIP_Real b, /**< constant in numerator */
442 SCIP_Real c, /**< coefficient in denominator */
443 SCIP_Real d, /**< constant in denominator */
444 SCIP_Real e /**< constant */
445 )
446{
447 SCIP_INTERVAL result;
448 int i;
449
450 SCIPintervalSetEmpty(&result);
451
452 /* return empty interval if the domain of the expression is empty */
454 return result;
455
456 /* substract constant from bounds of the expression */
458
459 /* if the expression is constant or the limit lies inside the domain, nothing can be propagated */
460 if( a*d - b*c == 0.0 || (bnds.inf < a / c && bnds.sup > a / c) )
461 {
463 return result;
464 }
465
466 /* compute bounds for [x.inf,x.inf] and [x.sup,x.sup] independently */
467 for( i = 0; i < 2; ++i )
468 {
469 SCIP_INTERVAL denominator;
470 SCIP_INTERVAL numerator;
471 SCIP_INTERVAL quotient;
472 SCIP_Real val = (i == 0) ? bnds.inf : bnds.sup;
473
474 /* (d * x' - b) */
475 SCIPintervalSet(&numerator, d);
476 SCIPintervalMulScalar(SCIP_INTERVAL_INFINITY, &numerator, numerator, val);
477 SCIPintervalAddScalar(SCIP_INTERVAL_INFINITY, &numerator, numerator, -b);
478
479 /* (a - c * x') */
480 SCIPintervalSet(&denominator, -c);
481 SCIPintervalMulScalar(SCIP_INTERVAL_INFINITY, &denominator, denominator, val);
482 SCIPintervalAddScalar(SCIP_INTERVAL_INFINITY, &denominator, denominator, a);
483
484 /* (d * x' - b) / (a - c * x') */
485 SCIPintervalDiv(SCIP_INTERVAL_INFINITY, &quotient, numerator, denominator);
486
487 /* unify with the resulting interval */
488 SCIPintervalUnify(&result, result, quotient);
489 }
490
491 return result;
492}
493
494/** adds data to given rowprep; the generated estimator is always locally valid
495 *
496 * @note the constant is moved to the left- or right-hand side
497 * @note other than the name of this function may indicate, it does not create a rowprep
498 */
499static
501 SCIP* scip, /**< SCIP data structure */
502 SCIP_ROWPREP* rowprep, /**< a rowprep where to store the estimator */
503 SCIP_VAR** vars, /**< variables */
504 SCIP_Real* coefs, /**< coefficients */
505 SCIP_Real constant, /**< constant */
506 int nlinvars /**< total number of variables */
507 )
508{
509 assert(scip != NULL);
510 assert(rowprep != NULL);
511 assert(coefs != NULL);
512 assert(vars != NULL);
513
514 /* create rowprep */
515 SCIProwprepAddSide(rowprep, -constant);
516 SCIP_CALL( SCIPensureRowprepSize(scip, rowprep, nlinvars + 1) );
517
518 /* add coefficients */
519 SCIP_CALL( SCIPaddRowprepTerms(scip, rowprep, nlinvars, vars, coefs) );
520
521 return SCIP_OKAY;
522}
523
524/** computes an estimator at a given point for the univariate case (ax + b) / (cx + d) + e
525 *
526 * Depending on the reference point, the estimator is a tangent or a secant on the graph.
527 * It depends on whether we are under- or overestimating, whether we are on the left or
528 * on the right side of the singularity at -d/c, and whether it is the monotone increasing
529 * (ad - bc > 0) or decreasing part (ad - bc < 0). Together, there are 8 cases:
530 *
531 * - mon. incr. + overestimate + left hand side --> secant
532 * - mon. incr. + overestimate + right hand side --> tangent
533 * - mon. incr. + understimate + left hand side --> tangent
534 * - mon. incr. + understimate + right hand side --> secant
535 * - mon. decr. + overestimate + left hand side --> tangent
536 * - mon. decr. + overestimate + right hand side --> secant
537 * - mon. decr. + understimate + left hand side --> secant
538 * - mon. decr. + understimate + right hand side --> tangent
539 */
540static
542 SCIP* scip, /**< SCIP data structure */
543 SCIP_Real lbx, /**< local lower bound of x */
544 SCIP_Real ubx, /**< local upper bound of x */
545 SCIP_Real gllbx, /**< global lower bound of x */
546 SCIP_Real glubx, /**< global upper bound of x */
547 SCIP_Real solx, /**< solution value of x */
548 SCIP_Real a, /**< coefficient in numerator */
549 SCIP_Real b, /**< constant in numerator */
550 SCIP_Real c, /**< coefficient in denominator */
551 SCIP_Real d, /**< constant in denominator */
552 SCIP_Real e, /**< constant */
553 SCIP_Real* coef, /**< pointer to store the coefficient */
554 SCIP_Real* constant, /**< pointer to store the constant */
555 SCIP_Bool overestimate, /**< whether the expression should be overestimated */
556 SCIP_Bool* local, /**< pointer to store whether the estimate is locally valid */
557 SCIP_Bool* branchinguseful, /**< pointer to store whether branching on the expression would improve the estimator */
558 SCIP_Bool* success /**< buffer to store whether separation was successful */
559 )
560{
561 SCIP_Real singularity;
562 SCIP_Bool isinleftpart;
563 SCIP_Bool monincreasing;
564
565 assert(lbx <= solx && solx <= ubx);
566 assert(coef != NULL);
567 assert(constant != NULL);
568 assert(local != NULL);
569 assert(branchinguseful != NULL);
570 assert(success != NULL);
571
572 *branchinguseful = TRUE;
573 *success = FALSE;
574 *coef = 0.0;
575 *constant = 0.0;
576 singularity = -d / c;
577
578 /* estimate is globally valid if local and global bounds are equal */
579 *local = gllbx != lbx || glubx != ubx; /*lint !e777*/
580
581 /* if 0 is in the denom interval, estimation is not possible */
582 if( SCIPisLE(scip, lbx, singularity) && SCIPisGE(scip, ubx, singularity) )
583 return SCIP_OKAY;
584
585 isinleftpart = (ubx < singularity);
586 monincreasing = (a * d - b * c > 0.0);
587
588 /* this encodes the 8 cases explained above */
589 if( monincreasing == (overestimate == isinleftpart) )
590 {
591 SCIP_Real lbeval;
592 SCIP_Real ubeval;
593
594 /* if one of the bounds is infinite, secant cannot be computed */
595 if( SCIPisInfinity(scip, -lbx) || SCIPisInfinity(scip, ubx) )
596 return SCIP_OKAY;
597
598 lbeval = (a * lbx + b) / (c * lbx + d) + e;
599 ubeval = (a * ubx + b) / (c * ubx + d) + e;
600
601 /* compute coefficient and constant of linear estimator */
602 *coef = (ubeval - lbeval) / (ubx - lbx);
603 *constant = ubeval - (*coef) * ubx;
604 }
605 else
606 {
607 SCIP_Real soleval;
608
609 soleval = (a * solx + b) / (c * solx + d) + e;
610
611 /* compute coefficient and constant of linear estimator */
612 *coef = (a * d - b * c) / SQR(d + c * solx);
613 *constant = soleval - (*coef) * solx;
614
615 /* gradient cuts are globally valid if the singularity is not in [gllbx,glubx] */
616 *local = SCIPisLE(scip, gllbx, singularity) && SCIPisGE(scip, glubx, singularity);
617
618 /* branching will not improve the convexification via tangent cuts */
619 *branchinguseful = FALSE;
620 }
621
622 /* avoid huge values in the cut */
623 if( SCIPisHugeValue(scip, REALABS(*coef)) || SCIPisHugeValue(scip, REALABS(*constant)) )
624 return SCIP_OKAY;
625
626 *success = TRUE;
627
628 return SCIP_OKAY;
629}
630
631/** helper method to compute estimator for the univariate case; the estimator is stored in a given rowprep */
632static
634 SCIP* scip, /**< SCIP data structure */
635 SCIP_SOL* sol, /**< solution point (or NULL for the LP solution) */
636 SCIP_EXPR* xexpr, /**< argument expression */
637 SCIP_Real a, /**< coefficient in numerator */
638 SCIP_Real b, /**< constant in numerator */
639 SCIP_Real c, /**< coefficient in denominator */
640 SCIP_Real d, /**< constant in denominator */
641 SCIP_Real e, /**< constant */
642 SCIP_Bool overestimate, /**< whether the expression should be overestimated */
643 SCIP_ROWPREP* rowprep, /**< a rowprep where to store the estimator */
644 SCIP_Bool* branchinguseful, /**< pointer to store whether branching on the expression would improve the estimator */
645 SCIP_Bool* success /**< buffer to store whether separation was successful */
646 )
647{
648 SCIP_VAR* x;
649 SCIP_Real constant;
650 SCIP_Real coef;
651 SCIP_Real gllbx;
652 SCIP_Real glubx;
653 SCIP_Real lbx;
654 SCIP_Real ubx;
655 SCIP_Real solx;
656 SCIP_Bool local;
657 SCIP_INTERVAL bnd;
658
659 assert(rowprep != NULL);
660 assert(branchinguseful != NULL);
661 assert(success != NULL);
662
664
665 /* get local bounds on xexpr */
671 lbx = bnd.inf;
672 ubx = bnd.sup;
673
674 /* check whether variable has been fixed or has empty interval */
675 if( SCIPisEQ(scip, lbx, ubx) || ubx < lbx )
676 {
677 *success = FALSE;
678 return SCIP_OKAY;
679 }
680
681 /* get global variable bounds */
682 gllbx = SCIPvarGetLbGlobal(x);
683 glubx = SCIPvarGetUbGlobal(x);
684
685 /* get and adjust solution value */
686 solx = SCIPgetSolVal(scip, sol, x);
687 solx = MIN(MAX(solx, lbx), ubx);
688
689 /* compute an estimator */
690 SCIP_CALL( estimateUnivariate(scip, lbx, ubx, gllbx, glubx, solx, a, b, c, d, e, &coef, &constant, overestimate, &local, branchinguseful, success) );
691
692 /* add estimator to rowprep, if successful */
693 if( *success )
694 {
695 (void) SCIPsnprintf(SCIProwprepGetName(rowprep), SCIP_MAXSTRLEN, "quot_%s_%lld", SCIPvarGetName(x), SCIPgetNLPs(scip));
696 SCIP_CALL( createRowprep(scip, rowprep, &x, &coef, constant, 1) );
697 SCIProwprepSetLocal(rowprep, local);
698 }
699
700 return SCIP_OKAY;
701}
702
703/** helper method to compute a gradient cut for
704 * \f[
705 * h^c(x,y) := \frac{1}{y} \left(\frac{x + \sqrt{\text{lbx}\cdot\text{ubx}}}{\sqrt{\text{lbx}} + \sqrt{\text{ubx}}}\right)^2
706 * \f]
707 * at a given reference point
708 *
709 * See Zamora and Grossmann (1988) for more details.
710 */
711static
713 SCIP_Real lbx, /**< lower bound of x */
714 SCIP_Real ubx, /**< upper bound of x */
715 SCIP_Real solx, /**< solution value of x */
716 SCIP_Real soly, /**< solution value of y */
717 SCIP_Real* coefx, /**< pointer to store the coefficient of x */
718 SCIP_Real* coefy, /**< pointer to store the coefficient of y */
719 SCIP_Real* constant /**< pointer to store the constant */
720 )
721{
722 SCIP_Real tmp1;
723 SCIP_Real tmp2;
724
725 assert(lbx >= 0.0);
726 assert(lbx <= ubx);
727 assert(soly > 0.0);
728 assert(coefx != NULL);
729 assert(coefy != NULL);
730 assert(constant != NULL);
731
732 tmp1 = sqrt(lbx * ubx) + solx;
733 tmp2 = SQR(sqrt(lbx) + sqrt(ubx)) * soly; /*lint !e666*/
734 assert(tmp2 > 0.0);
735
736 *coefx = 2.0 * tmp1 / tmp2;
737 *coefy = -SQR(tmp1) / (tmp2 * soly);
738 *constant = 2.0 * sqrt(lbx * ubx) * tmp1 / tmp2;
739}
740
741/** computes an over- or underestimator at a given point for the bivariate case x/y &le;/&ge; z
742 *
743 * There are the following cases for y > 0:
744 *
745 * 1. lbx < 0 < ubx:
746 * Rewrite x / y = z as x = y * z and use McCormick to compute a valid inequality of the form
747 * x = y * z &le; a * y + b * z + c. Note that b > 0 because of y > 0. The inequality is then transformed
748 * to x / b - a/b * y - c/b &le; z, which results in a valid underestimator for x / y over the set
749 * {(x,y) | lbz &le; x / y &le; ubz}. Note that overestimating/underestimating the bilinear term with McCormick
750 * results in an underestimator/overestimator for x / y.
751 *
752 * 2. lbx &ge; 0 or ubx &le; 0:
753 * - overestimation: use \f$z \leq \frac{1}{\text{lby}\cdot\text{uby}} \min(\text{uby}\cdot x - \text{lbx}\cdot y + \text{lbx}\cdot\text{lby}, \text{lby}\cdot x - \text{ubx}\cdot y + \text{ubx}\cdot\text{uby})\f$
754 * - underestimation: use \f$z \geq x/y \geq \frac{1}{y} \frac{x + \sqrt{\text{lbx}\cdot\text{ubx}}}{\sqrt{\text{lbx} + \sqrt{\text{ubx}}}}\f$ and build gradient cut
755 *
756 * If y < 0, swap and negate its bounds and compute the respective opposite estimator (and negate it).
757 *
758 * If 0 is in the interval of y, nothing is possible.
759 */
760static
762 SCIP* scip, /**< SCIP data structure */
763 SCIP_Real lbx, /**< lower bound of x */
764 SCIP_Real ubx, /**< upper bound of x */
765 SCIP_Real lby, /**< lower bound of y */
766 SCIP_Real uby, /**< upper bound of y */
767 SCIP_Real lbz, /**< lower bound of z */
768 SCIP_Real ubz, /**< lower bound of z */
769 SCIP_Real solx, /**< reference point for x */
770 SCIP_Real soly, /**< reference point for y */
771 SCIP_Real solz, /**< reference point for z */
772 SCIP_Bool overestimate, /**< whether the expression should be overestimated */
773 SCIP_Real* coefx, /**< pointer to store the x coefficient */
774 SCIP_Real* coefy, /**< pointer to store the y coefficient */
775 SCIP_Real* constant, /**< pointer to store the constant */
776 SCIP_Bool* branchingusefulx, /**< pointer to store whether branching on x would improve the estimator */
777 SCIP_Bool* branchingusefuly, /**< pointer to store whether branching on y would improve the estimator */
778 SCIP_Bool* success /**< buffer to store whether computing the estimator was successful */
779 )
780{
781 SCIP_Bool negatedx = FALSE;
782 SCIP_Bool negatedy = FALSE;
783
784 assert(lbx <= solx && solx <= ubx);
785 assert(lby <= soly && soly <= uby);
786 assert(lbz <= solz && solz <= ubz);
787 assert(coefx != NULL);
788 assert(coefy != NULL);
789 assert(constant != NULL);
790 assert(branchingusefulx != NULL);
791 assert(branchingusefuly != NULL);
792 assert(success != NULL);
793
794 *branchingusefulx = TRUE;
795 *branchingusefuly = TRUE;
796 *success = TRUE;
797 *coefx = 0.0;
798 *coefy = 0.0;
799 *constant = 0.0;
800
801 /* if 0 is in [lby,uby], then it is not possible to compute an estimator */
802 if( SCIPisLE(scip, lby, 0.0) && SCIPisGE(scip, uby, 0.0) )
803 {
804 *success = FALSE;
805 return SCIP_OKAY;
806 }
807
808 /* negate bounds of y if it is not positive */
809 if( uby < 0.0 )
810 {
811 SCIP_Real tmp = uby;
812
813 uby = -lby;
814 lby = -tmp;
815 soly = -soly;
816 negatedy = TRUE;
817 overestimate = !overestimate;
818 }
819
820 /* case 1: 0 is in the interior of [lbx,ubx] */
821 if( lbx < 0.0 && 0.0 < ubx )
822 {
823 SCIP_Real mccoefy = 0.0;
824 SCIP_Real mccoefaux = 0.0;
825 SCIP_Real mcconst = 0.0;
826
827 /* as explained in the description of this method, overestimating/underestimating the bilinear term results in an
828 * underestimator/overestimator for x / y
829 */
830 SCIPaddBilinMcCormick(scip, 1.0, lbz, ubz, solz, lby, uby, soly, !overestimate, &mccoefaux, &mccoefy, &mcconst,
831 success);
832 assert(mccoefaux >= 0.0);
833
834 if( !(*success) )
835 return SCIP_OKAY;
836
837 /* resulting estimator is x/b - a/b * y - c/b, where a*y + b*z + c is the estimator for y*z */
838 *coefx = 1.0 / mccoefaux;
839 *coefy = -mccoefy / mccoefaux;
840 *constant = -mcconst / mccoefaux;
841 }
842 /* case 2: 0 is not in the interior of [lbx,ubx] */
843 else
844 {
845 /* negate bounds of x if it is negative */
846 if( ubx <= 0.0 )
847 {
848 SCIP_Real tmp = ubx;
849
850 ubx = -lbx;
851 lbx = -tmp;
852 solx = -solx;
853 negatedx = TRUE;
854 overestimate = !overestimate;
855 }
856
857 /* case 2a */
858 if( overestimate )
859 {
860 /* check where the minimum is attained */
861 if( uby * solx - lbx * soly + lbx * lby <= lby * solx - ubx * soly + ubx * uby )
862 {
863 *coefx = 1.0 / lby;
864 *coefy = -lbx / (lby * uby);
865 *constant = lbx / uby;
866 }
867 else
868 {
869 *coefx = 1.0 / uby;
870 *coefy = -ubx / (lby * uby);
871 *constant = ubx / lby;
872 }
873 }
874 /* case 2b */
875 else
876 {
877 /* compute gradient cut for h^c(x,y) at (solx,soly) */
878 hcGradCut(lbx, ubx, solx, soly, coefx, coefy, constant);
879
880 /* estimator is independent of the bounds of y */
881 *branchingusefuly = FALSE;
882 }
883 }
884
885 /* reverse negations of x and y in the resulting estimator */
886 if( negatedx )
887 *coefx = -(*coefx);
888 if( negatedy )
889 *coefy = -(*coefy);
890
891 /* if exactly one variable has been negated, then we have computed an underestimate/overestimate for the negated
892 * expression, which results in an overestimate/underestimate for the original expression
893 */
894 if( negatedx != negatedy )
895 {
896 *coefx = -(*coefx);
897 *coefy = -(*coefy);
898 *constant = -(*constant);
899 }
900
901 /* avoid huge values in the estimator */
902 if( SCIPisHugeValue(scip, REALABS(*coefx)) || SCIPisHugeValue(scip, REALABS(*coefy))
903 || SCIPisHugeValue(scip, REALABS(*constant)) )
904 {
905 *success = FALSE;
906 return SCIP_OKAY;
907 }
908
909 return SCIP_OKAY;
910}
911
912/** construct an estimator for a quotient expression of the form (ax + b) / (cy + d) + e
913 *
914 * The resulting estimator is stored in a rowprep.
915 *
916 * The method first computes an estimator for x' / y' with x := ax + b and y := cy + d
917 * and then transforms this estimator to one for the quotient (ax + b) / (cy + d) + e.
918 */
919static
921 SCIP* scip, /**< SCIP data structure */
922 SCIP_EXPR* xexpr, /**< numerator expression */
923 SCIP_EXPR* yexpr, /**< denominator expression */
924 SCIP_VAR* auxvar, /**< auxiliary variable */
925 SCIP_SOL* sol, /**< solution point (or NULL for the LP solution) */
926 SCIP_Real a, /**< coefficient of numerator */
927 SCIP_Real b, /**< constant of numerator */
928 SCIP_Real c, /**< coefficient of denominator */
929 SCIP_Real d, /**< constant of denominator */
930 SCIP_Real e, /**< constant term */
931 SCIP_Bool overestimate, /**< whether the expression should be overestimated */
932 SCIP_ROWPREP* rowprep, /**< a rowprep where to store the estimator */
933 SCIP_Bool* branchingusefulx, /**< pointer to store whether branching on x would improve the estimator */
934 SCIP_Bool* branchingusefuly, /**< pointer to store whether branching on y would improve the estimator */
935 SCIP_Bool* success /**< buffer to store whether separation was successful */
936 )
937{
938 SCIP_VAR* vars[2];
939 SCIP_Real coefs[2] = {0.0, 0.0};
940 SCIP_Real constant = 0.0;
941 SCIP_Real solx;
942 SCIP_Real soly;
943 SCIP_Real solz;
944 SCIP_Real lbx;
945 SCIP_Real ubx;
946 SCIP_Real lby;
947 SCIP_Real uby;
948 SCIP_Real lbz;
949 SCIP_Real ubz;
950 SCIP_INTERVAL bnd;
951
952 assert(xexpr != NULL);
953 assert(yexpr != NULL);
954 assert(xexpr != yexpr);
955 assert(auxvar != NULL);
956 assert(rowprep != NULL);
957 assert(branchingusefulx != NULL);
958 assert(branchingusefuly != NULL);
959 assert(success != NULL);
960
961 vars[0] = SCIPgetExprAuxVarNonlinear(xexpr);
962 vars[1] = SCIPgetExprAuxVarNonlinear(yexpr);
963
964 /* get bounds for x, y, and z */
970 lbx = bnd.inf;
971 ubx = bnd.sup;
972
978 lby = bnd.inf;
979 uby = bnd.sup;
980
981 lbz = SCIPvarGetLbLocal(auxvar);
982 ubz = SCIPvarGetUbLocal(auxvar);
983
984 /* check whether one of the variables has been fixed or has empty domain */
985 if( SCIPisEQ(scip, lbx, ubx) || SCIPisEQ(scip, lby, uby) || ubx < lbx || uby < lby )
986 {
987 *success = FALSE;
988 return SCIP_OKAY;
989 }
990
991 /* get and adjust solution values */
992 solx = SCIPgetSolVal(scip, sol, vars[0]);
993 soly = SCIPgetSolVal(scip, sol, vars[1]);
994 solz = SCIPgetSolVal(scip, sol, auxvar);
995 solx = MIN(MAX(solx, lbx), ubx);
996 soly = MIN(MAX(soly, lby), uby);
997 solz = MIN(MAX(solz, lbz), ubz);
998
999 /* compute an estimator */
1001 MIN(a * lbx, a * ubx) + b, MAX(a * lbx, a * ubx) + b, /* bounds of x' */
1002 MIN(c * lby, c * uby) + d, MAX(c * lby, c * uby) + d, /* bounds of y' */
1003 lbz, ubz, a * solx + b, c * soly + d, solz, overestimate, &coefs[0], &coefs[1], &constant,
1004 branchingusefulx, branchingusefuly, success) );
1005
1006 /* add estimator to rowprep, if successful */
1007 if( *success )
1008 {
1009 /* transform estimator Ax' + By'+ C = A(ax + b) + B (cy + d) + C = (Aa) x + (Bc) y + (C + Ab + Bd);
1010 * add the constant e separately
1011 */
1012 constant += coefs[0] * b + coefs[1] * d + e;
1013 coefs[0] *= a;
1014 coefs[1] *= c;
1015
1016 /* prepare rowprep */
1017 (void) SCIPsnprintf(SCIProwprepGetName(rowprep), SCIP_MAXSTRLEN, "quot_%s_%s_%lld", SCIPvarGetName(vars[0]), SCIPvarGetName(vars[1]),
1018 SCIPgetNLPs(scip));
1019 SCIP_CALL( createRowprep(scip, rowprep, vars, coefs, constant, 2) );
1020 }
1021
1022 return SCIP_OKAY;
1023}
1024
1025/*
1026 * Callback methods of nonlinear handler
1027 */
1028
1029/** nonlinear handler copy callback */
1030static
1031SCIP_DECL_NLHDLRCOPYHDLR(nlhdlrCopyhdlrQuotient)
1032{ /*lint --e{715}*/
1033 assert(targetscip != NULL);
1034 assert(sourcenlhdlr != NULL);
1035 assert(strcmp(SCIPnlhdlrGetName(sourcenlhdlr), NLHDLR_NAME) == 0);
1036
1037 SCIP_CALL( SCIPincludeNlhdlrQuotient(targetscip) );
1038
1039 return SCIP_OKAY;
1040}
1041
1042
1043/** callback to free expression specific data */
1044static
1045SCIP_DECL_NLHDLRFREEEXPRDATA(nlhdlrFreeExprDataQuotient)
1046{ /*lint --e{715}*/
1047 assert(nlhdlrexprdata != NULL);
1048 assert(*nlhdlrexprdata != NULL);
1049
1050 /* free expression data of nonlinear handler */
1051 SCIP_CALL( exprdataFree(scip, nlhdlrexprdata) );
1052
1053 return SCIP_OKAY;
1054}
1055
1056
1057/** callback to detect structure in expression tree */
1058static
1059SCIP_DECL_NLHDLRDETECT(nlhdlrDetectQuotient)
1060{ /*lint --e{715}*/
1061 SCIP_Bool success;
1062
1063 assert(nlhdlrexprdata != NULL);
1064
1065 /* call detection routine */
1066 SCIP_CALL( detectExpr(scip, expr, nlhdlrexprdata, &success) );
1067
1068 if( success )
1069 {
1070 if( SCIPgetExprNAuxvarUsesNonlinear(expr) > 0 )
1071 *participating = SCIP_NLHDLR_METHOD_SEPABOTH;
1072
1073 if( (*nlhdlrexprdata)->numexpr == (*nlhdlrexprdata)->denomexpr )
1074 {
1075 /* if univariate, then we also do inteval and reverseprop */
1076 *participating |= SCIP_NLHDLR_METHOD_ACTIVITY;
1077
1078 /* if univariate, then all our methods are enforcing */
1079 *enforcing |= *participating;
1080 }
1081 }
1082
1083 return SCIP_OKAY;
1084}
1085
1086
1087/** auxiliary evaluation callback of nonlinear handler */
1088static
1089SCIP_DECL_NLHDLREVALAUX(nlhdlrEvalauxQuotient)
1090{ /*lint --e{715}*/
1091 SCIP_VAR* auxvarx;
1092 SCIP_VAR* auxvary;
1093 SCIP_Real solvalx;
1094 SCIP_Real solvaly;
1095 SCIP_Real nomval;
1096 SCIP_Real denomval;
1097
1098 assert(expr != NULL);
1099 assert(auxvalue != NULL);
1100
1101 /**! [SnippetNlhdlrEvalauxQuotient] */
1102 /* get auxiliary variables */
1103 auxvarx = SCIPgetExprAuxVarNonlinear(nlhdlrexprdata->numexpr);
1104 auxvary = SCIPgetExprAuxVarNonlinear(nlhdlrexprdata->denomexpr);
1105 assert(auxvarx != NULL);
1106 assert(auxvary != NULL);
1107
1108 /* get solution values of the auxiliary variables */
1109 solvalx = SCIPgetSolVal(scip, sol, auxvarx);
1110 solvaly = SCIPgetSolVal(scip, sol, auxvary);
1111
1112 /* evaluate expression w.r.t. the values of the auxiliary variables */
1113 nomval = nlhdlrexprdata->numcoef * solvalx + nlhdlrexprdata->numconst;
1114 denomval = nlhdlrexprdata->denomcoef * solvaly + nlhdlrexprdata->denomconst;
1115
1116 /* return SCIP_INVALID if the denominator evaluates to zero */
1117 *auxvalue = (denomval != 0.0) ? nlhdlrexprdata->constant + nomval / denomval : SCIP_INVALID;
1118 /**! [SnippetNlhdlrEvalauxQuotient] */
1119
1120 return SCIP_OKAY;
1121}
1122
1123
1124/** nonlinear handler under/overestimation callback
1125 *
1126 * @todo which of the paramters did I not use, but have to be taken into consideration?
1127*/
1128static
1129SCIP_DECL_NLHDLRESTIMATE(nlhdlrEstimateQuotient)
1130{ /*lint --e{715}*/
1131 SCIP_Bool branchingusefulx = FALSE;
1132 SCIP_Bool branchingusefuly = FALSE;
1133 SCIP_ROWPREP* rowprep;
1134
1135 assert(nlhdlr != NULL);
1136 assert(expr != NULL);
1137 assert(nlhdlrexprdata != NULL);
1138 assert(rowpreps != NULL);
1139
1140 /** ![SnippetNlhdlrEstimateQuotient] */
1141 *addedbranchscores = FALSE;
1142 *success = FALSE;
1143
1145
1146 if( nlhdlrexprdata->numexpr == nlhdlrexprdata->denomexpr )
1147 {
1148 /* univariate case */
1149 SCIP_CALL( estimateUnivariateQuotient(scip, sol, nlhdlrexprdata->numexpr, nlhdlrexprdata->numcoef, nlhdlrexprdata->numconst,
1150 nlhdlrexprdata->denomcoef, nlhdlrexprdata->denomconst, nlhdlrexprdata->constant, overestimate, rowprep,
1151 &branchingusefulx, success) );
1152 }
1153 else
1154 {
1155 /* bivariate case */
1156 SCIP_CALL( estimateBivariateQuotient(scip, nlhdlrexprdata->numexpr, nlhdlrexprdata->denomexpr, SCIPgetExprAuxVarNonlinear(expr), sol,
1157 nlhdlrexprdata->numcoef, nlhdlrexprdata->numconst, nlhdlrexprdata->denomcoef, nlhdlrexprdata->denomconst,
1158 nlhdlrexprdata->constant, overestimate, rowprep,
1159 &branchingusefulx, &branchingusefuly, success) );
1160 }
1161
1162 if( *success )
1163 {
1164 SCIP_CALL( SCIPsetPtrarrayVal(scip, rowpreps, 0, rowprep) );
1165 }
1166 else
1167 {
1168 SCIPfreeRowprep(scip, &rowprep);
1169 }
1170
1171 /* add branching scores if requested */
1172 if( addbranchscores )
1173 {
1174 SCIP_EXPR* exprs[2];
1175 SCIP_Real violation;
1176 int nexprs = 0;
1177
1178 if( branchingusefulx )
1179 exprs[nexprs++] = nlhdlrexprdata->numexpr;
1180 if( branchingusefuly )
1181 exprs[nexprs++] = nlhdlrexprdata->denomexpr;
1182
1183 /* compute violation w.r.t. the auxiliary variable(s) */
1184#ifndef BRSCORE_ABSVIOL
1185 SCIP_CALL( SCIPgetExprRelAuxViolationNonlinear(scip, expr, auxvalue, sol, &violation, NULL, NULL) );
1186#else
1187 SCIP_CALL( SCIPgetExprAbsAuxViolationNonlinear(scip, expr, auxvalue, sol, &violation, NULL, NULL) );
1188#endif
1189 assert(violation > 0.0); /* there should be a violation if we were called to enforce */
1190
1191 SCIP_CALL( SCIPaddExprsViolScoreNonlinear(scip, exprs, nexprs, violation, sol, addedbranchscores) );
1192 }
1193 /** ![SnippetNlhdlrEstimateQuotient] */
1194
1195 return SCIP_OKAY;
1196}
1197
1198/** nonlinear handler solution linearization callback */
1199static
1200SCIP_DECL_NLHDLRSOLLINEARIZE(nlhdlrSollinearizeQuotient)
1201{ /*lint --e{715}*/
1202 SCIP_VAR* x;
1203 SCIP_Real lbx;
1204 SCIP_Real ubx;
1205 SCIP_Real solx;
1206 int c;
1207
1208 assert(nlhdlr != NULL);
1209 assert(expr != NULL);
1210 assert(nlhdlrexprdata != NULL);
1211
1212 /* in the bivariate case, we do not get globally valid estimators */
1213 if( nlhdlrexprdata->numexpr != nlhdlrexprdata->denomexpr )
1214 return SCIP_OKAY;
1215
1216 x = SCIPgetExprAuxVarNonlinear(nlhdlrexprdata->numexpr);
1217 lbx = SCIPvarGetLbGlobal(x);
1218 ubx = SCIPvarGetUbGlobal(x);
1219 solx = SCIPgetSolVal(scip, sol, x);
1220 solx = MAX(MIN(solx, ubx), lbx);
1221
1222 for( c = (overestimate ? 0 : 1); c < (underestimate ? 2 : 1); ++c ) /* c == 0: overestimate, c == 1: underestimate */
1223 {
1224 SCIP_ROWPREP* rowprep;
1225 SCIP_Bool success = FALSE;
1226 SCIP_Bool local = TRUE;
1227 SCIP_Bool branchinguseful;
1228 SCIP_Real coef;
1229 SCIP_Real constant;
1230
1231 /* compute estimator, will be secant or gradient */
1232 SCIP_CALL( estimateUnivariate(scip, lbx, ubx, lbx, ubx, solx,
1233 nlhdlrexprdata->numcoef, nlhdlrexprdata->numconst, nlhdlrexprdata->denomcoef, nlhdlrexprdata->denomconst, nlhdlrexprdata->constant,
1234 &coef, &constant, c == 0, &local, &branchinguseful, &success) );
1235
1236 /* skip if not successful, only locally valid, or just a secant (branchinguseful is TRUE) */
1237 if( !success || local || branchinguseful )
1238 continue;
1239
1241 SCIP_CALL( SCIPaddRowprepTerm(scip, rowprep, x, coef) );
1243 SCIProwprepAddConstant(rowprep, constant);
1244 (void) SCIPsnprintf(SCIProwprepGetName(rowprep), SCIP_MAXSTRLEN, "quot_%s_sol%d", SCIPvarGetName(x), SCIPsolGetIndex(sol));
1245
1246 SCIP_CALL( SCIPcleanupRowprep2(scip, rowprep, sol, SCIPgetHugeValue(scip), &success) );
1247
1248 /* if cleanup succeeded and rowprep is still global, add to cutpool */
1249 if( success && !SCIProwprepIsLocal(rowprep) )
1250 {
1251 SCIP_ROW* row;
1252
1253 SCIP_CALL( SCIPgetRowprepRowCons(scip, &row, rowprep, cons) );
1254 SCIP_CALL( SCIPaddPoolCut(scip, row) );
1255 SCIP_CALL( SCIPreleaseRow(scip, &row) );
1256 }
1257
1258 SCIPfreeRowprep(scip, &rowprep);
1259 }
1260
1261 return SCIP_OKAY;
1262}
1263
1264/** nonlinear handler interval evaluation callback */
1265static
1266SCIP_DECL_NLHDLRINTEVAL(nlhdlrIntevalQuotient)
1267{ /*lint --e{715}*/
1268 SCIP_INTERVAL bnds;
1269
1270 assert(nlhdlrexprdata != NULL);
1271 assert(nlhdlrexprdata->numexpr != NULL);
1272 assert(nlhdlrexprdata->denomexpr != NULL);
1273
1274 /* it is not possible to compute tighter intervals if both expressions are different
1275 * we should not be called in this case, as we haven't said we would participate in this activity in detect
1276 */
1277 assert(nlhdlrexprdata->numexpr == nlhdlrexprdata->denomexpr);
1278
1279 /**! [SnippetNlhdlrIntevalQuotient] */
1280 /* get activity of the numerator (= denominator) expression */
1281 bnds = SCIPexprGetActivity(nlhdlrexprdata->numexpr);
1282
1283 /* call interval evaluation for the univariate quotient expression */
1284 *interval = intEvalQuotient(scip, bnds, nlhdlrexprdata->numcoef, nlhdlrexprdata->numconst,
1285 nlhdlrexprdata->denomcoef, nlhdlrexprdata->denomconst, nlhdlrexprdata->constant);
1286 /**! [SnippetNlhdlrIntevalQuotient] */
1287
1288 return SCIP_OKAY;
1289}
1290
1291
1292/** nonlinear handler callback for reverse propagation */
1293static
1294SCIP_DECL_NLHDLRREVERSEPROP(nlhdlrReversepropQuotient)
1295{ /*lint --e{715}*/
1296 SCIP_INTERVAL result;
1297
1298 assert(nlhdlrexprdata != NULL);
1299 assert(nlhdlrexprdata->numexpr != NULL);
1300 assert(nlhdlrexprdata->denomexpr != NULL);
1301
1302 /* it is not possible to compute tighter intervals if both expressions are different
1303 * we should not be called in this case, as we haven't said we would participate in this activity in detect
1304 */
1305 assert(nlhdlrexprdata->numexpr == nlhdlrexprdata->denomexpr);
1306
1307 SCIPdebugMsg(scip, "call reverse propagation for expression (%g %p + %g) / (%g %p + %g) + %g bounds [%g,%g]\n",
1308 nlhdlrexprdata->numcoef, (void*)nlhdlrexprdata->numexpr, nlhdlrexprdata->numconst,
1309 nlhdlrexprdata->denomcoef, (void*)nlhdlrexprdata->denomexpr, nlhdlrexprdata->denomconst,
1310 nlhdlrexprdata->constant, bounds.inf, bounds.sup);
1311
1312 /* call reverse propagation */
1313 /**! [SnippetNlhdlrReversepropQuotient] */
1314 result = reversepropQuotient(bounds, nlhdlrexprdata->numcoef, nlhdlrexprdata->numconst,
1315 nlhdlrexprdata->denomcoef, nlhdlrexprdata->denomconst, nlhdlrexprdata->constant);
1316
1317 SCIPdebugMsg(scip, "try to tighten bounds of %p: [%g,%g] -> [%g,%g]\n",
1318 (void*)nlhdlrexprdata->numexpr, SCIPgetExprBoundsNonlinear(scip, nlhdlrexprdata->numexpr).inf,
1319 SCIPgetExprBoundsNonlinear(scip, nlhdlrexprdata->numexpr).sup, result.inf, result.sup);
1320
1321 /* tighten bounds of the expression */
1322 SCIP_CALL( SCIPtightenExprIntervalNonlinear(scip, nlhdlrexprdata->numexpr, result, infeasible, nreductions) );
1323 /**! [SnippetNlhdlrReversepropQuotient] */
1324
1325 return SCIP_OKAY;
1326}
1327
1328
1329/*
1330 * nonlinear handler specific interface methods
1331 */
1332
1333/** includes quotient nonlinear handler in nonlinear constraint handler */
1335 SCIP* scip /**< SCIP data structure */
1336 )
1337{
1338 SCIP_NLHDLRDATA* nlhdlrdata;
1339 SCIP_NLHDLR* nlhdlr;
1340
1341 assert(scip != NULL);
1342
1343 /* create nonlinear handler data */
1344 nlhdlrdata = NULL;
1345
1347 NLHDLR_ENFOPRIORITY, nlhdlrDetectQuotient, nlhdlrEvalauxQuotient, nlhdlrdata) );
1348 assert(nlhdlr != NULL);
1349
1350 SCIPnlhdlrSetCopyHdlr(nlhdlr, nlhdlrCopyhdlrQuotient);
1351 SCIPnlhdlrSetFreeExprData(nlhdlr, nlhdlrFreeExprDataQuotient);
1352 SCIPnlhdlrSetSepa(nlhdlr, NULL, NULL, nlhdlrEstimateQuotient, NULL);
1353 SCIPnlhdlrSetSollinearize(nlhdlr, nlhdlrSollinearizeQuotient);
1354 SCIPnlhdlrSetProp(nlhdlr, nlhdlrIntevalQuotient, nlhdlrReversepropQuotient);
1355
1356 return SCIP_OKAY;
1357}
SCIP_VAR * a
Definition: circlepacking.c:66
SCIP_VAR ** b
Definition: circlepacking.c:65
SCIP_VAR ** x
Definition: circlepacking.c:63
constraint handler for nonlinear constraints specified by algebraic expressions
#define NULL
Definition: def.h:266
#define SCIP_MAXSTRLEN
Definition: def.h:287
#define SCIP_INVALID
Definition: def.h:192
#define SCIP_INTERVAL_INFINITY
Definition: def.h:194
#define SCIP_Bool
Definition: def.h:91
#define MIN(x, y)
Definition: def.h:242
#define SCIP_Real
Definition: def.h:172
#define SQR(x)
Definition: def.h:213
#define TRUE
Definition: def.h:93
#define FALSE
Definition: def.h:94
#define MAX(x, y)
Definition: def.h:238
#define REALABS(x)
Definition: def.h:196
#define SCIP_CALL(x)
Definition: def.h:373
unsigned int SCIPgetExprNAuxvarUsesNonlinear(SCIP_EXPR *expr)
SCIP_RETCODE SCIPgetExprRelAuxViolationNonlinear(SCIP *scip, SCIP_EXPR *expr, SCIP_Real auxvalue, SCIP_SOL *sol, SCIP_Real *viol, SCIP_Bool *violunder, SCIP_Bool *violover)
SCIP_VAR * SCIPgetExprAuxVarNonlinear(SCIP_EXPR *expr)
SCIP_RETCODE SCIPtightenExprIntervalNonlinear(SCIP *scip, SCIP_EXPR *expr, SCIP_INTERVAL newbounds, SCIP_Bool *cutoff, int *ntightenings)
SCIP_RETCODE SCIPaddExprsViolScoreNonlinear(SCIP *scip, SCIP_EXPR **exprs, int nexprs, SCIP_Real violscore, SCIP_SOL *sol, SCIP_Bool *success)
SCIP_RETCODE SCIPregisterExprUsageNonlinear(SCIP *scip, SCIP_EXPR *expr, SCIP_Bool useauxvar, SCIP_Bool useactivityforprop, SCIP_Bool useactivityforsepabelow, SCIP_Bool useactivityforsepaabove)
SCIP_INTERVAL SCIPgetExprBoundsNonlinear(SCIP *scip, SCIP_EXPR *expr)
SCIP_RETCODE SCIPgetExprAbsAuxViolationNonlinear(SCIP *scip, SCIP_EXPR *expr, SCIP_Real auxvalue, SCIP_SOL *sol, SCIP_Real *viol, SCIP_Bool *violunder, SCIP_Bool *violover)
void SCIPinfoMessage(SCIP *scip, FILE *file, const char *formatstr,...)
Definition: scip_message.c:208
#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 SCIPincludeNlhdlrQuotient(SCIP *scip)
SCIP_RETCODE SCIPaddPoolCut(SCIP *scip, SCIP_ROW *row)
Definition: scip_cut.c:361
SCIP_RETCODE SCIPsetPtrarrayVal(SCIP *scip, SCIP_PTRARRAY *ptrarray, int idx, void *val)
int SCIPexprGetNChildren(SCIP_EXPR *expr)
Definition: expr.c:3860
SCIP_Real SCIPgetExponentExprPow(SCIP_EXPR *expr)
Definition: expr_pow.c:3456
SCIP_Bool SCIPisExprProduct(SCIP *scip, SCIP_EXPR *expr)
Definition: scip_expr.c:1464
SCIP_Bool SCIPisExprSum(SCIP *scip, SCIP_EXPR *expr)
Definition: scip_expr.c:1453
SCIP_Real * SCIPgetCoefsExprSum(SCIP_EXPR *expr)
Definition: expr_sum.c:1552
SCIP_Real SCIPgetCoefExprProduct(SCIP_EXPR *expr)
SCIP_RETCODE SCIPreleaseExpr(SCIP *scip, SCIP_EXPR **expr)
Definition: scip_expr.c:1417
SCIP_RETCODE SCIPprintExpr(SCIP *scip, SCIP_EXPR *expr, FILE *file)
Definition: scip_expr.c:1486
SCIP_Bool SCIPisExprPower(SCIP *scip, SCIP_EXPR *expr)
Definition: scip_expr.c:1475
SCIP_EXPR ** SCIPexprGetChildren(SCIP_EXPR *expr)
Definition: expr.c:3870
SCIP_Real SCIPgetConstantExprSum(SCIP_EXPR *expr)
Definition: expr_sum.c:1567
SCIP_INTERVAL SCIPexprGetActivity(SCIP_EXPR *expr)
Definition: expr.c:4016
void SCIPcaptureExpr(SCIP_EXPR *expr)
Definition: scip_expr.c:1409
SCIP_RETCODE SCIPevalExprActivity(SCIP *scip, SCIP_EXPR *expr)
Definition: scip_expr.c:1717
void SCIPintervalIntersectEps(SCIP_INTERVAL *resultant, SCIP_Real eps, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
SCIP_Real SCIPintervalGetInf(SCIP_INTERVAL interval)
void SCIPintervalSetEntire(SCIP_Real infinity, SCIP_INTERVAL *resultant)
void SCIPintervalUnify(SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
void SCIPintervalSubScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_Real operand2)
void SCIPintervalSet(SCIP_INTERVAL *resultant, SCIP_Real value)
SCIP_Bool SCIPintervalIsEmpty(SCIP_Real infinity, SCIP_INTERVAL operand)
void SCIPintervalSetBounds(SCIP_INTERVAL *resultant, SCIP_Real inf, SCIP_Real sup)
void SCIPintervalMulScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_Real operand2)
void SCIPintervalDiv(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
void SCIPintervalAddScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_Real operand2)
void SCIPintervalDivScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_Real operand2)
SCIP_Real SCIPintervalGetSup(SCIP_INTERVAL interval)
void SCIPintervalSetEmpty(SCIP_INTERVAL *resultant)
#define SCIPfreeBlockMemory(scip, ptr)
Definition: scip_mem.h:108
#define SCIPallocBlockMemory(scip, ptr)
Definition: scip_mem.h:89
void SCIPnlhdlrSetCopyHdlr(SCIP_NLHDLR *nlhdlr, SCIP_DECL_NLHDLRCOPYHDLR((*copy)))
Definition: nlhdlr.c:76
void SCIPnlhdlrSetFreeExprData(SCIP_NLHDLR *nlhdlr, SCIP_DECL_NLHDLRFREEEXPRDATA((*freeexprdata)))
Definition: nlhdlr.c:98
void SCIPnlhdlrSetProp(SCIP_NLHDLR *nlhdlr, SCIP_DECL_NLHDLRINTEVAL((*inteval)), SCIP_DECL_NLHDLRREVERSEPROP((*reverseprop)))
Definition: nlhdlr.c:123
void SCIPnlhdlrSetSollinearize(SCIP_NLHDLR *nlhdlr, SCIP_DECL_NLHDLRSOLLINEARIZE((*sollinearize)))
Definition: nlhdlr.c:154
void SCIPnlhdlrSetSepa(SCIP_NLHDLR *nlhdlr, SCIP_DECL_NLHDLRINITSEPA((*initsepa)), SCIP_DECL_NLHDLRENFO((*enfo)), SCIP_DECL_NLHDLRESTIMATE((*estimate)), SCIP_DECL_NLHDLREXITSEPA((*exitsepa)))
Definition: nlhdlr.c:136
const char * SCIPnlhdlrGetName(SCIP_NLHDLR *nlhdlr)
Definition: nlhdlr.c:166
SCIP_RETCODE SCIPincludeNlhdlrNonlinear(SCIP *scip, SCIP_NLHDLR **nlhdlr, const char *name, const char *desc, int detectpriority, int enfopriority, SCIP_DECL_NLHDLRDETECT((*detect)), SCIP_DECL_NLHDLREVALAUX((*evalaux)), SCIP_NLHDLRDATA *nlhdlrdata)
SCIP_RETCODE SCIPreleaseRow(SCIP *scip, SCIP_ROW **row)
Definition: scip_lp.c:1562
int SCIPsolGetIndex(SCIP_SOL *sol)
Definition: sol.c:2835
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1213
SCIP_Longint SCIPgetNLPs(SCIP *scip)
SCIP_Real SCIPinfinity(SCIP *scip)
SCIP_Bool SCIPisGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisHugeValue(SCIP *scip, SCIP_Real val)
SCIP_Bool SCIPisInfinity(SCIP *scip, SCIP_Real val)
SCIP_Real SCIPgetHugeValue(SCIP *scip)
SCIP_Bool SCIPisEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_Bool SCIPisZero(SCIP *scip, SCIP_Real val)
SCIP_Real SCIPepsilon(SCIP *scip)
SCIP_Real SCIPvarGetUbLocal(SCIP_VAR *var)
Definition: var.c:18143
SCIP_Real SCIPvarGetUbGlobal(SCIP_VAR *var)
Definition: var.c:18087
const char * SCIPvarGetName(SCIP_VAR *var)
Definition: var.c:17418
SCIP_Real SCIPvarGetLbLocal(SCIP_VAR *var)
Definition: var.c:18133
SCIP_Real SCIPvarGetLbGlobal(SCIP_VAR *var)
Definition: var.c:18077
SCIP_RETCODE SCIPcleanupRowprep2(SCIP *scip, SCIP_ROWPREP *rowprep, SCIP_SOL *sol, SCIP_Real maxcoefbound, SCIP_Bool *success)
SCIP_RETCODE SCIPensureRowprepSize(SCIP *scip, SCIP_ROWPREP *rowprep, int size)
Definition: misc_rowprep.c:887
char * SCIProwprepGetName(SCIP_ROWPREP *rowprep)
Definition: misc_rowprep.c:689
SCIP_Bool SCIProwprepIsLocal(SCIP_ROWPREP *rowprep)
Definition: misc_rowprep.c:679
void SCIProwprepAddConstant(SCIP_ROWPREP *rowprep, SCIP_Real constant)
Definition: misc_rowprep.c:760
SCIP_RETCODE SCIPaddRowprepTerm(SCIP *scip, SCIP_ROWPREP *rowprep, SCIP_VAR *var, SCIP_Real coef)
Definition: misc_rowprep.c:913
SCIP_RETCODE SCIPgetRowprepRowCons(SCIP *scip, SCIP_ROW **row, SCIP_ROWPREP *rowprep, SCIP_CONS *cons)
SCIP_RETCODE SCIPcreateRowprep(SCIP *scip, SCIP_ROWPREP **rowprep, SCIP_SIDETYPE sidetype, SCIP_Bool local)
Definition: misc_rowprep.c:563
SCIP_RETCODE SCIPaddRowprepTerms(SCIP *scip, SCIP_ROWPREP *rowprep, int nvars, SCIP_VAR **vars, SCIP_Real *coefs)
Definition: misc_rowprep.c:938
void SCIProwprepSetLocal(SCIP_ROWPREP *rowprep, SCIP_Bool islocal)
Definition: misc_rowprep.c:780
void SCIProwprepAddSide(SCIP_ROWPREP *rowprep, SCIP_Real side)
Definition: misc_rowprep.c:746
void SCIPfreeRowprep(SCIP *scip, SCIP_ROWPREP **rowprep)
Definition: misc_rowprep.c:583
int SCIPsnprintf(char *t, int len, const char *s,...)
Definition: misc.c:10880
private functions of nonlinear handlers of nonlinear constraints
bilinear nonlinear handler
static void hcGradCut(SCIP_Real lbx, SCIP_Real ubx, SCIP_Real solx, SCIP_Real soly, SCIP_Real *coefx, SCIP_Real *coefy, SCIP_Real *constant)
#define NLHDLR_DETECTPRIORITY
static void transformExpr(SCIP *scip, SCIP_EXPR *expr, SCIP_EXPR **target, SCIP_Real *coef, SCIP_Real *constant)
static SCIP_RETCODE exprdataCreate(SCIP *scip, SCIP_NLHDLREXPRDATA **nlhdlrexprdata, SCIP_EXPR *numexpr, SCIP_Real numcoef, SCIP_Real numconst, SCIP_EXPR *denomexpr, SCIP_Real denomcoef, SCIP_Real denomconst, SCIP_Real constant)
#define NLHDLR_ENFOPRIORITY
static SCIP_RETCODE exprdataFree(SCIP *scip, SCIP_NLHDLREXPRDATA **nlhdlrexprdata)
static SCIP_DECL_NLHDLRREVERSEPROP(nlhdlrReversepropQuotient)
static SCIP_RETCODE estimateUnivariate(SCIP *scip, SCIP_Real lbx, SCIP_Real ubx, SCIP_Real gllbx, SCIP_Real glubx, SCIP_Real solx, SCIP_Real a, SCIP_Real b, SCIP_Real c, SCIP_Real d, SCIP_Real e, SCIP_Real *coef, SCIP_Real *constant, SCIP_Bool overestimate, SCIP_Bool *local, SCIP_Bool *branchinguseful, SCIP_Bool *success)
static SCIP_INTERVAL reversepropQuotient(SCIP_INTERVAL bnds, SCIP_Real a, SCIP_Real b, SCIP_Real c, SCIP_Real d, SCIP_Real e)
static SCIP_RETCODE estimateBivariateQuotient(SCIP *scip, SCIP_EXPR *xexpr, SCIP_EXPR *yexpr, SCIP_VAR *auxvar, SCIP_SOL *sol, SCIP_Real a, SCIP_Real b, SCIP_Real c, SCIP_Real d, SCIP_Real e, SCIP_Bool overestimate, SCIP_ROWPREP *rowprep, SCIP_Bool *branchingusefulx, SCIP_Bool *branchingusefuly, SCIP_Bool *success)
static SCIP_DECL_NLHDLRFREEEXPRDATA(nlhdlrFreeExprDataQuotient)
static SCIP_DECL_NLHDLRCOPYHDLR(nlhdlrCopyhdlrQuotient)
static SCIP_DECL_NLHDLRSOLLINEARIZE(nlhdlrSollinearizeQuotient)
static SCIP_INTERVAL intEvalQuotient(SCIP *scip, SCIP_INTERVAL bnds, SCIP_Real a, SCIP_Real b, SCIP_Real c, SCIP_Real d, SCIP_Real e)
#define infty2infty(infty1, infty2, val)
#define NLHDLR_DESC
#define NLHDLR_NAME
static SCIP_DECL_NLHDLREVALAUX(nlhdlrEvalauxQuotient)
static SCIP_DECL_NLHDLRINTEVAL(nlhdlrIntevalQuotient)
static SCIP_RETCODE estimateBivariate(SCIP *scip, SCIP_Real lbx, SCIP_Real ubx, SCIP_Real lby, SCIP_Real uby, SCIP_Real lbz, SCIP_Real ubz, SCIP_Real solx, SCIP_Real soly, SCIP_Real solz, SCIP_Bool overestimate, SCIP_Real *coefx, SCIP_Real *coefy, SCIP_Real *constant, SCIP_Bool *branchingusefulx, SCIP_Bool *branchingusefuly, SCIP_Bool *success)
static SCIP_RETCODE createRowprep(SCIP *scip, SCIP_ROWPREP *rowprep, SCIP_VAR **vars, SCIP_Real *coefs, SCIP_Real constant, int nlinvars)
static SCIP_RETCODE estimateUnivariateQuotient(SCIP *scip, SCIP_SOL *sol, SCIP_EXPR *xexpr, SCIP_Real a, SCIP_Real b, SCIP_Real c, SCIP_Real d, SCIP_Real e, SCIP_Bool overestimate, SCIP_ROWPREP *rowprep, SCIP_Bool *branchinguseful, SCIP_Bool *success)
static SCIP_RETCODE detectExpr(SCIP *scip, SCIP_EXPR *expr, SCIP_NLHDLREXPRDATA **nlhdlrexprdata, SCIP_Bool *success)
static SCIP_DECL_NLHDLRESTIMATE(nlhdlrEstimateQuotient)
static SCIP_DECL_NLHDLRDETECT(nlhdlrDetectQuotient)
quotient nonlinear handler
#define SCIPdebug(x)
Definition: pub_message.h:93
preparation of a linear inequality to become a SCIP_ROW
SCIP_Real sup
Definition: intervalarith.h:56
SCIP_Real inf
Definition: intervalarith.h:55
@ SCIP_SIDETYPE_RIGHT
Definition: type_lp.h:65
@ SCIP_SIDETYPE_LEFT
Definition: type_lp.h:64
struct SCIP_NlhdlrData SCIP_NLHDLRDATA
Definition: type_nlhdlr.h:452
#define SCIP_NLHDLR_METHOD_SEPABOTH
Definition: type_nlhdlr.h:53
#define SCIP_NLHDLR_METHOD_ACTIVITY
Definition: type_nlhdlr.h:54
struct SCIP_NlhdlrExprData SCIP_NLHDLREXPRDATA
Definition: type_nlhdlr.h:453
@ SCIP_OKAY
Definition: type_retcode.h:42
enum SCIP_Retcode SCIP_RETCODE
Definition: type_retcode.h:63