Scippy

SCIP

Solving Constraint Integer Programs

type_cons.h
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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) 2002-2020 Konrad-Zuse-Zentrum */
7 /* fuer Informationstechnik Berlin */
8 /* */
9 /* SCIP is distributed under the terms of the ZIB Academic License. */
10 /* */
11 /* You should have received a copy of the ZIB Academic License */
12 /* along with SCIP; see the file COPYING. If not visit scipopt.org. */
13 /* */
14 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
15 
16 /**@file type_cons.h
17  * @ingroup TYPEDEFINITIONS
18  * @brief type definitions for constraints and constraint handlers
19  * @author Tobias Achterberg
20  * @author Stefan Heinz
21  *
22  * This file defines the interface for constraint handlers implemented in C.
23  *
24  * - \ref CONS "Instructions for implementing a constraint handler"
25  * - \ref CONSHDLRS "List of available constraint handlers"
26  * - \ref scip::ObjConshdlr "C++ wrapper class"
27  */
28 
29 /** @defgroup DEFPLUGINS_CONS Default constraint handlers
30  * @ingroup DEFPLUGINS
31  * @brief implementation files (.c files) of the default constraint handlers of SCIP
32  */
33 
34 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
35 
36 #ifndef __SCIP_TYPE_CONS_H__
37 #define __SCIP_TYPE_CONS_H__
38 
39 #include "scip/def.h"
40 #include "scip/type_lp.h"
41 #include "scip/type_retcode.h"
42 #include "scip/type_result.h"
43 #include "scip/type_var.h"
44 #include "scip/type_sol.h"
45 #include "scip/type_scip.h"
46 #include "scip/type_timing.h"
47 #include "scip/type_heur.h"
48 
49 #ifdef __cplusplus
50 extern "C" {
51 #endif
52 
53 typedef struct SCIP_Conshdlr SCIP_CONSHDLR; /**< constraint handler for a specific constraint type */
54 typedef struct SCIP_Cons SCIP_CONS; /**< constraint data structure */
55 typedef struct SCIP_ConshdlrData SCIP_CONSHDLRDATA; /**< constraint handler data */
56 typedef struct SCIP_ConsData SCIP_CONSDATA; /**< locally defined constraint type specific data */
57 typedef struct SCIP_ConsSetChg SCIP_CONSSETCHG; /**< tracks additions and removals of the set of active constraints */
58 typedef struct SCIP_LinConsStats SCIP_LINCONSSTATS; /**< linear constraint classification statistics used for MIPLIB */
59 
60 /** linear constraint types recognizable */
62 {
63  SCIP_LINCONSTYPE_EMPTY = 0, /**< linear constraints with no variables */
64  SCIP_LINCONSTYPE_FREE = 1, /**< linear constraints with no finite side */
65  SCIP_LINCONSTYPE_SINGLETON = 2, /**< linear constraints with a single variable */
66  SCIP_LINCONSTYPE_AGGREGATION = 3, /**< linear constraints of the type \f$ ax + by = c\f$ */
67  SCIP_LINCONSTYPE_PRECEDENCE = 4, /**< linear constraints of the type \f$ a x - a y \leq b\f$ where \f$x\f$ and \f$y\f$ must have the same type */
68  SCIP_LINCONSTYPE_VARBOUND = 5, /**< linear constraints of the form \f$ ax + by \leq c \, x \in \{0,1\} \f$ */
69  SCIP_LINCONSTYPE_SETPARTITION = 6, /**< linear constraints of the form \f$ \sum x_i = 1\, x_i \in \{0,1\} \forall i \f$ */
70  SCIP_LINCONSTYPE_SETPACKING = 7, /**< linear constraints of the form \f$ \sum x_i \leq 1\, x_i \in \{0,1\} \forall i \f$ */
71  SCIP_LINCONSTYPE_SETCOVERING = 8, /**< linear constraints of the form \f$ \sum x_i \geq 1\, x_i \in \{0,1\} \forall i \f$ */
72  SCIP_LINCONSTYPE_CARDINALITY = 9, /**< linear constraints of the form \f$ \sum x_i = k\, x_i \in \{0,1\} \forall i, \, k\geq 2 \f$ */
73  SCIP_LINCONSTYPE_INVKNAPSACK = 10, /**< linear constraints of the form \f$ \sum x_i \leq b\, x_i \in \{0,1\} \forall i, \, b\in \mathbb{n} \geq 2 \f$ */
74  SCIP_LINCONSTYPE_EQKNAPSACK = 11, /**< linear constraints of the form \f$ \sum a_i x_i = b\, x_i \in \{0,1\} \forall i, \, b\in \mathbb{n} \geq 2 \f$ */
75  SCIP_LINCONSTYPE_BINPACKING = 12, /**< linear constraints of the form \f$ \sum a_i x_i + a x \leq a\, x, x_i \in \{0,1\} \forall i, \, a\in \mathbb{n} \geq 2 \f$ */
76  SCIP_LINCONSTYPE_KNAPSACK = 13, /**< linear constraints of the form \f$ \sum a_k x_k \leq b\, x_i \in \{0,1\} \forall i, \, b\in \mathbb{n} \geq 2 \f$ */
77  SCIP_LINCONSTYPE_INTKNAPSACK = 14, /**< linear constraints of the form \f$ \sum a_k x_k \leq b\, x_i \in \mathbb{Z} \forall i, \, b\in \mathbb{n} \f$ */
78  SCIP_LINCONSTYPE_MIXEDBINARY = 15, /**< linear constraints of the form \f$ \sum a_k x_k + \sum p_j s_j \leq/= b\, x_i \in \{0,1\} \forall i, s_j \in \text{ cont. } \forall j\f$ */
79  SCIP_LINCONSTYPE_GENERAL = 16 /**< general linear constraints with no special structure */
80 };
82 
83 #define SCIP_NLINCONSTYPES ((int)SCIP_LINCONSTYPE_GENERAL+1)
84 
85 /** copy method for constraint handler plugins (called when SCIP copies plugins)
86  *
87  * If the copy process was one to one, the valid pointer can be set to TRUE. Otherwise, this pointer has to be set to
88  * FALSE. If all problem defining objects (constraint handlers and variable pricers) return valid = TRUE for all
89  * their copying calls, SCIP assumes that it is an overall one to one copy of the original instance. In this case any
90  * reductions made in the copied SCIP instance can be transfered to the original SCIP instance. If the valid pointer is
91  * set to TRUE and it was not a one to one copy, it might happen that optimal solutions are cut off.
92  *
93  * input:
94  * - scip : SCIP main data structure
95  * - conshdlr : the constraint handler itself
96  * - valid : was the copying process valid?
97  */
98 #define SCIP_DECL_CONSHDLRCOPY(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_Bool* valid)
99 
100 /** destructor of constraint handler to free constraint handler data (called when SCIP is exiting)
101  *
102  * input:
103  * - scip : SCIP main data structure
104  * - conshdlr : the constraint handler itself
105  */
106 #define SCIP_DECL_CONSFREE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr)
107 
108 /** initialization method of constraint handler (called after problem was transformed)
109  *
110  * input:
111  * - scip : SCIP main data structure
112  * - conshdlr : the constraint handler itself
113  * - conss : array of constraints in transformed problem
114  * - nconss : number of constraints in transformed problem
115  */
116 #define SCIP_DECL_CONSINIT(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss)
117 
118 /** deinitialization method of constraint handler (called before transformed problem is freed)
119  *
120  * input:
121  * - scip : SCIP main data structure
122  * - conshdlr : the constraint handler itself
123  * - conss : array of constraints in transformed problem
124  * - nconss : number of constraints in transformed problem
125  */
126 #define SCIP_DECL_CONSEXIT(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss)
127 
128 /** presolving initialization method of constraint handler (called when presolving is about to begin)
129  *
130  * This method is called when the presolving process is about to begin, even if presolving is turned off.
131  * The constraint handler may use this call to initialize its data structures.
132  *
133  * Necessary modifications that have to be performed even if presolving is turned off should be done here or in the
134  * presolving deinitialization call (SCIP_DECL_CONSEXITPRE()).
135  *
136  * @note Note that the constraint array might contain constraints that were created but not added to the problem.
137  * Constraints that are not added, i.e., for which SCIPconsIsAdded() returns FALSE, cannot be used for problem
138  * reductions.
139  *
140  * input:
141  * - scip : SCIP main data structure
142  * - conshdlr : the constraint handler itself
143  * - conss : array of constraints in transformed problem
144  * - nconss : number of constraints in transformed problem
145  */
146 #define SCIP_DECL_CONSINITPRE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss)
147 
148 /** presolving deinitialization method of constraint handler (called after presolving has been finished)
149  *
150  * This method is called after the presolving has been finished, even if presolving is turned off.
151  * The constraint handler may use this call e.g. to clean up or modify its data structures.
152  *
153  * Necessary modifications that have to be performed even if presolving is turned off should be done here or in the
154  * presolving initialization call (SCIP_DECL_CONSINITPRE()).
155  *
156  * Besides necessary modifications and clean up, no time consuming operations should be performed, especially if the
157  * problem has already been solved. Use the method SCIPgetStatus(), which in this case returns SCIP_STATUS_OPTIMAL,
158  * SCIP_STATUS_INFEASIBLE, SCIP_STATUS_UNBOUNDED, or SCIP_STATUS_INFORUNBD.
159  *
160  * @note Note that the constraint array might contain constraints that were created but not added to the problem.
161  * Constraints that are not added, i.e., for which SCIPconsIsAdded() returns FALSE, cannot be used for problem
162  * reductions.
163  *
164  * input:
165  * - scip : SCIP main data structure
166  * - conshdlr : the constraint handler itself
167  * - conss : final array of constraints in transformed problem
168  * - nconss : final number of constraints in transformed problem
169  */
170 #define SCIP_DECL_CONSEXITPRE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss)
171 
172 /** solving process initialization method of constraint handler (called when branch and bound process is about to begin)
173  *
174  * This method is called when the presolving was finished and the branch and bound process is about to begin.
175  * The constraint handler may use this call to initialize its branch and bound specific data.
176  *
177  * Besides necessary modifications and clean up, no time consuming operations should be performed, especially if the
178  * problem has already been solved. Use the method SCIPgetStatus(), which in this case returns SCIP_STATUS_OPTIMAL,
179  * SCIP_STATUS_INFEASIBLE, SCIP_STATUS_UNBOUNDED, or SCIP_STATUS_INFORUNBD.
180  *
181  * @note Note that the constraint array might contain constraints that were created but not added to the problem.
182  * Constraints that are not added, i.e., for which SCIPconsIsAdded() returns FALSE, cannot be used for problem
183  * reductions.
184  *
185  * input:
186  * - scip : SCIP main data structure
187  * - conshdlr : the constraint handler itself
188  * - conss : array of constraints of the constraint handler
189  * - nconss : number of constraints of the constraint handler
190  */
191 #define SCIP_DECL_CONSINITSOL(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss)
192 
193 /** solving process deinitialization method of constraint handler (called before branch and bound process data is freed)
194  *
195  * This method is called before the branch and bound process is freed.
196  * The constraint handler should use this call to clean up its branch and bound data, in particular to release
197  * all LP rows that he has created or captured.
198  *
199  * input:
200  * - scip : SCIP main data structure
201  * - conshdlr : the constraint handler itself
202  * - conss : array of constraints of the constraint handler
203  * - nconss : number of constraints of the constraint handler
204  * - restart : was this exit solve call triggered by a restart?
205  */
206 #define SCIP_DECL_CONSEXITSOL(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss, SCIP_Bool restart)
207 
208 /** frees specific constraint data
209  *
210  * @warning There may exist unprocessed events. For example, a variable's bound may have been already changed, but the
211  * corresponding bound change event was not yet processed.
212  *
213  * input:
214  * - scip : SCIP main data structure
215  * - conshdlr : the constraint handler itself
216  * - cons : the constraint belonging to the constraint data
217  * - consdata : pointer to the constraint data to free
218  */
219 #define SCIP_DECL_CONSDELETE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons, SCIP_CONSDATA** consdata)
220 
221 /** transforms constraint data into data belonging to the transformed problem
222  *
223  * input:
224  * - scip : SCIP main data structure
225  * - conshdlr : the constraint handler itself
226  * - sourcecons : source constraint to transform
227  * - targetcons : pointer to store created target constraint
228  */
229 #define SCIP_DECL_CONSTRANS(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* sourcecons, SCIP_CONS** targetcons)
230 
231 /** LP initialization method of constraint handler (called before the initial LP relaxation at a node is solved)
232  *
233  * Puts the LP relaxations of all "initial" constraints into the LP. The method should put a canonic LP relaxation
234  * of all given constraints to the LP with calls to SCIPaddRow().
235  *
236  * @warning It is not guaranteed that the problem is going to be declared infeasible if the infeasible pointer is set
237  * to TRUE. Therefore, it is recommended that users do not end this method prematurely when an infeasiblity
238  * is detected.
239  *
240  * input:
241  * - scip : SCIP main data structure
242  * - conshdlr : the constraint handler itself
243  * - conss : array of constraints to process
244  * - nconss : number of constraints to process
245  *
246  * output:
247  * - infeasible : pointer to store whether an infeasibility was detected while building the LP
248  */
249 #define SCIP_DECL_CONSINITLP(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss, SCIP_Bool* infeasible)
250 
251 /** separation method of constraint handler for LP solution
252  *
253  * Separates all constraints of the constraint handler. The method is called in the LP solution loop,
254  * which means that a valid LP solution exists.
255  *
256  * The first nusefulconss constraints are the ones, that are identified to likely be violated. The separation
257  * method should process only the useful constraints in most runs, and only occasionally the remaining
258  * nconss - nusefulconss constraints.
259  *
260  * input:
261  * - scip : SCIP main data structure
262  * - conshdlr : the constraint handler itself
263  * - conss : array of constraints to process
264  * - nconss : number of constraints to process
265  * - nusefulconss : number of useful (non-obsolete) constraints to process
266  * - result : pointer to store the result of the separation call
267  *
268  * possible return values for *result (if more than one applies, the first in the list should be used):
269  * - SCIP_CUTOFF : the node is infeasible in the variable's bounds and can be cut off
270  * - SCIP_CONSADDED : an additional constraint was generated
271  * - SCIP_REDUCEDDOM : a variable's domain was reduced
272  * - SCIP_SEPARATED : a cutting plane was generated
273  * - SCIP_NEWROUND : a cutting plane was generated and a new separation round should immediately start
274  * - SCIP_DIDNOTFIND : the separator searched, but did not find domain reductions, cutting planes, or cut constraints
275  * - SCIP_DIDNOTRUN : the separator was skipped
276  * - SCIP_DELAYED : the separator was skipped, but should be called again
277  */
278 #define SCIP_DECL_CONSSEPALP(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, \
279  int nconss, int nusefulconss, SCIP_RESULT* result)
280 
281 /** separation method of constraint handler for arbitrary primal solution
282  *
283  * Separates all constraints of the constraint handler. The method is called outside the LP solution loop (e.g., by
284  * a relaxator or a primal heuristic), which means that there is no valid LP solution.
285  * Instead, the method should produce cuts that separate the given solution.
286  *
287  * The first nusefulconss constraints are the ones, that are identified to likely be violated. The separation
288  * method should process only the useful constraints in most runs, and only occasionally the remaining
289  * nconss - nusefulconss constraints.
290  *
291  * input:
292  * - scip : SCIP main data structure
293  * - conshdlr : the constraint handler itself
294  * - conss : array of constraints to process
295  * - nconss : number of constraints to process
296  * - nusefulconss : number of useful (non-obsolete) constraints to process
297  * - sol : primal solution that should be separated
298  * - result : pointer to store the result of the separation call
299  *
300  * possible return values for *result (if more than one applies, the first in the list should be used):
301  * - SCIP_CUTOFF : the node is infeasible in the variable's bounds and can be cut off
302  * - SCIP_CONSADDED : an additional constraint was generated
303  * - SCIP_REDUCEDDOM : a variable's domain was reduced
304  * - SCIP_SEPARATED : a cutting plane was generated
305  * - SCIP_NEWROUND : a cutting plane was generated and a new separation round should immediately start
306  * - SCIP_DIDNOTFIND : the separator searched, but did not find domain reductions, cutting planes, or cut constraints
307  * - SCIP_DIDNOTRUN : the separator was skipped
308  * - SCIP_DELAYED : the separator was skipped, but should be called again
309  */
310 #define SCIP_DECL_CONSSEPASOL(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, \
311  int nconss, int nusefulconss, SCIP_SOL* sol, SCIP_RESULT* result)
312 
313 /** constraint enforcing method of constraint handler for LP solutions
314  *
315  * The method is called at the end of the node processing loop for a node where the LP was solved.
316  * The LP solution has to be checked for feasibility. If possible, an infeasibility should be resolved by
317  * branching, reducing a variable's domain to exclude the solution or separating the solution with a valid
318  * cutting plane.
319  *
320  * The enforcing methods of the active constraint handlers are called in decreasing order of their enforcing
321  * priorities until the first constraint handler returned with the value SCIP_CUTOFF, SCIP_SEPARATED,
322  * SCIP_REDUCEDDOM, SCIP_CONSADDED, or SCIP_BRANCHED.
323  * The integrality constraint handler has an enforcing priority of zero. A constraint handler which can
324  * (or wants) to enforce its constraints only for integral solutions should have a negative enforcing priority
325  * (e.g. the alldiff-constraint can only operate on integral solutions).
326  * A constraint handler which wants to incorporate its own branching strategy even on non-integral
327  * solutions must have an enforcing priority greater than zero (e.g. the SOS-constraint incorporates
328  * SOS-branching on non-integral solutions).
329  *
330  * The first nusefulconss constraints are the ones, that are identified to likely be violated. The enforcing
331  * method should process the useful constraints first. The other nconss - nusefulconss constraints should only
332  * be enforced, if no violation was found in the useful constraints.
333  *
334  * input:
335  * - scip : SCIP main data structure
336  * - conshdlr : the constraint handler itself
337  * - conss : array of constraints to process
338  * - nconss : number of constraints to process
339  * - nusefulconss : number of useful (non-obsolete) constraints to process
340  * - solinfeasible : was the solution already declared infeasible by a constraint handler?
341  * - result : pointer to store the result of the enforcing call
342  *
343  * possible return values for *result (if more than one applies, the first in the list should be used):
344  * - SCIP_CUTOFF : the node is infeasible in the variable's bounds and can be cut off
345  * - SCIP_CONSADDED : an additional constraint was generated
346  * - SCIP_REDUCEDDOM : a variable's domain was reduced
347  * - SCIP_SEPARATED : a cutting plane was generated
348  * - SCIP_SOLVELP : the LP should be solved again because the LP primal feasibility tolerance has been tightened
349  * - SCIP_BRANCHED : no changes were made to the problem, but a branching was applied to resolve an infeasibility
350  * - SCIP_INFEASIBLE : at least one constraint is infeasible, but it was not resolved
351  * - SCIP_FEASIBLE : all constraints of the handler are feasible
352  */
353 #define SCIP_DECL_CONSENFOLP(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss, int nusefulconss, \
354  SCIP_Bool solinfeasible, SCIP_RESULT* result)
355 
356 /** constraint enforcing method of constraint handler for relaxation solutions
357  *
358  * input:
359  * - scip : SCIP main data structure
360  * - sol : relaxation solution
361  * - conshdlr : the constraint handler itself
362  * - conss : array of constraints to process
363  * - nconss : number of constraints to process
364  * - nusefulconss : number of useful (non-obsolete) constraints to process
365  * - solinfeasible : was the solution already declared infeasible by a constraint handler?
366  * - result : pointer to store the result of the enforcing call
367  *
368  * possible return values for *result (if more than one applies, the first in the list should be used):
369  * - SCIP_CUTOFF : the node is infeasible in the variable's bounds and can be cut off
370  * - SCIP_CONSADDED : an additional constraint was generated
371  * - SCIP_REDUCEDDOM : a variable's domain was reduced
372  * - SCIP_SEPARATED : a cutting plane was generated
373  * - SCIP_BRANCHED : no changes were made to the problem, but a branching was applied to resolve an infeasibility
374  * - SCIP_SOLVELP : at least one constraint is infeasible, and this can only be resolved by solving the LP
375  * - SCIP_INFEASIBLE : at least one constraint is infeasible, but it was not resolved
376  * - SCIP_FEASIBLE : all constraints of the handler are feasible
377  */
378 #define SCIP_DECL_CONSENFORELAX(x) SCIP_RETCODE x (SCIP* scip, SCIP_SOL* sol, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss, int nusefulconss, \
379  SCIP_Bool solinfeasible, SCIP_RESULT* result)
380 
381 /** constraint enforcing method of constraint handler for pseudo solutions
382  *
383  * The method is called at the end of the node processing loop for a node where the LP was not solved.
384  * The pseudo solution has to be checked for feasibility. If possible, an infeasibility should be resolved by
385  * branching, reducing a variable's domain to exclude the solution or adding an additional constraint.
386  * Separation is not possible, since the LP is not processed at the current node. All LP informations like
387  * LP solution, slack values, or reduced costs are invalid and must not be accessed.
388  *
389  * Like in the enforcing method for LP solutions, the enforcing methods of the active constraint handlers are
390  * called in decreasing order of their enforcing priorities until the first constraint handler returned with
391  * the value SCIP_CUTOFF, SCIP_REDUCEDDOM, SCIP_CONSADDED, SCIP_BRANCHED, or SCIP_SOLVELP.
392  *
393  * The first nusefulconss constraints are the ones, that are identified to likely be violated. The enforcing
394  * method should process the useful constraints first. The other nconss - nusefulconss constraints should only
395  * be enforced, if no violation was found in the useful constraints.
396  *
397  * If the pseudo solution's objective value is lower than the lower bound of the node, it cannot be feasible
398  * and the enforcing method may skip it's check and set *result to SCIP_DIDNOTRUN. However, it can also process
399  * its constraints and return any other possible result code.
400  *
401  * input:
402  * - scip : SCIP main data structure
403  * - conshdlr : the constraint handler itself
404  * - conss : array of constraints to process
405  * - nconss : number of constraints to process
406  * - nusefulconss : number of useful (non-obsolete) constraints to process
407  * - solinfeasible : was the solution already declared infeasible by a constraint handler?
408  * - objinfeasible : is the solution infeasible anyway due to violating lower objective bound?
409  * - result : pointer to store the result of the enforcing call
410  *
411  * possible return values for *result (if more than one applies, the first in the list should be used):
412  * - SCIP_CUTOFF : the node is infeasible in the variable's bounds and can be cut off
413  * - SCIP_CONSADDED : an additional constraint was generated
414  * - SCIP_REDUCEDDOM : a variable's domain was reduced
415  * - SCIP_BRANCHED : no changes were made to the problem, but a branching was applied to resolve an infeasibility
416  * - SCIP_SOLVELP : at least one constraint is infeasible, and this can only be resolved by solving the LP
417  * - SCIP_INFEASIBLE : at least one constraint is infeasible, but it was not resolved
418  * - SCIP_FEASIBLE : all constraints of the handler are feasible
419  * - SCIP_DIDNOTRUN : the enforcement was skipped (only possible, if objinfeasible is true)
420  */
421 #define SCIP_DECL_CONSENFOPS(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss, int nusefulconss, \
422  SCIP_Bool solinfeasible, SCIP_Bool objinfeasible, SCIP_RESULT* result)
423 
424 /** feasibility check method of constraint handler for integral solutions
425  *
426  * The given solution has to be checked for feasibility.
427  *
428  * The check methods of the active constraint handlers are called in decreasing order of their check
429  * priorities until the first constraint handler returned with the result SCIP_INFEASIBLE.
430  * The integrality constraint handler has a check priority of zero. A constraint handler which can
431  * (or wants) to check its constraints only for integral solutions should have a negative check priority
432  * (e.g. the alldiff-constraint can only operate on integral solutions).
433  * A constraint handler which wants to check feasibility even on non-integral solutions must have a
434  * check priority greater than zero (e.g. if the check is much faster than testing all variables for
435  * integrality).
436  *
437  * In some cases, integrality conditions or rows of the current LP don't have to be checked, because their
438  * feasibility is already checked or implicitly given. In these cases, 'checkintegrality' or
439  * 'checklprows' is FALSE.
440  *
441  * If the solution is not NULL, SCIP should also be informed about the constraint violation with a call to
442  * SCIPupdateSolConsViolation() and additionally SCIPupdateSolLPRowViolation() for every row of the constraint's current
443  * representation in the LP relaxation, if any such rows exist.
444  * As a convenience method, SCIPupdateSolLPConsViolation() can be used if the constraint
445  * is represented completely by a set of LP rows, meaning that the current constraint violation is equal to the maximum
446  * of the contraint violations of the corresponding LP rows.
447  *
448  * input:
449  * - scip : SCIP main data structure
450  * - conshdlr : the constraint handler itself
451  * - conss : array of constraints to process
452  * - nconss : number of constraints to process
453  * - sol : the solution to check feasibility for
454  * - checkintegrality: Has integrality to be checked?
455  * - checklprows : Do constraints represented by rows in the current LP have to be checked?
456  * - printreason : Should the reason for the violation be printed?
457  * - completely : Should all violations be checked?
458  * - result : pointer to store the result of the feasibility checking call
459  *
460  * possible return values for *result:
461  * - SCIP_INFEASIBLE : at least one constraint of the handler is infeasible
462  * - SCIP_FEASIBLE : all constraints of the handler are feasible
463  */
464 #define SCIP_DECL_CONSCHECK(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss, SCIP_SOL* sol, \
465  SCIP_Bool checkintegrality, SCIP_Bool checklprows, SCIP_Bool printreason, SCIP_Bool completely, SCIP_RESULT* result)
466 
467 /** domain propagation method of constraint handler
468  *
469  * The first nusefulconss constraints are the ones, that are identified to likely be violated. The propagation
470  * method should process only the useful constraints in most runs, and only occasionally the remaining
471  * nconss - nusefulconss constraints.
472  *
473  * @note if the constraint handler uses dual information in propagation it is nesassary to check via calling
474  * SCIPallowWeakDualReds and SCIPallowStrongDualReds if dual reductions and propgation with the current cutoff bound, resp.,
475  * are allowed.
476  *
477  * input:
478  * - scip : SCIP main data structure
479  * - conshdlr : the constraint handler itself
480  * - conss : array of constraints to process
481  * - nconss : number of constraints to process
482  * - nusefulconss : number of useful (non-obsolete) constraints to process
483  * - nmarkedconss : number of constraints which are marked to be definitely propagated
484  * - proptiming : current point in the node solving loop
485  * - result : pointer to store the result of the propagation call
486  *
487  * possible return values for *result:
488  * - SCIP_CUTOFF : the node is infeasible in the variable's bounds and can be cut off
489  * - SCIP_REDUCEDDOM : at least one domain reduction was found
490  * - SCIP_DIDNOTFIND : the propagator searched but did not find any domain reductions
491  * - SCIP_DIDNOTRUN : the propagator was skipped
492  * - SCIP_DELAYED : the propagator was skipped, but should be called again
493  * - SCIP_DELAYNODE : the current node should be postponed (return value only valid for BEFORELP propagation)
494  */
495 #define SCIP_DECL_CONSPROP(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss, int nusefulconss, \
496  int nmarkedconss, SCIP_PROPTIMING proptiming, SCIP_RESULT* result)
497 
498 /** presolving method of constraint handler
499  *
500  * The presolver should go through the variables and constraints and tighten the domains or
501  * constraints. Each tightening should increase the given total number of changes.
502  *
503  * input:
504  * - scip : SCIP main data structure
505  * - conshdlr : the constraint handler itself
506  * - conss : array of constraints to process
507  * - nconss : number of constraints to process
508  * - nrounds : number of presolving rounds already done
509  * - presoltiming : current presolving timing
510  * - nnewfixedvars : number of variables fixed since the last call to the presolving method
511  * - nnewaggrvars : number of variables aggregated since the last call to the presolving method
512  * - nnewchgvartypes : number of variable type changes since the last call to the presolving method
513  * - nnewchgbds : number of variable bounds tightened since the last call to the presolving method
514  * - nnewholes : number of domain holes added since the last call to the presolving method
515  * - nnewdelconss : number of deleted constraints since the last call to the presolving method
516  * - nnewaddconss : number of added constraints since the last call to the presolving method
517  * - nnewupgdconss : number of upgraded constraints since the last call to the presolving method
518  * - nnewchgcoefs : number of changed coefficients since the last call to the presolving method
519  * - nnewchgsides : number of changed left or right hand sides since the last call to the presolving method
520  *
521  * @note the counters state the changes since the last call including the changes of this presolving method during its
522  * call
523  *
524  * @note if the constraint handler performs dual presolving it is nesassary to check via calling SCIPallowWeakDualReds
525  * and SCIPallowStrongDualReds if dual reductions are allowed.
526  *
527  * input/output:
528  * - nfixedvars : pointer to count total number of variables fixed of all presolvers
529  * - naggrvars : pointer to count total number of variables aggregated of all presolvers
530  * - nchgvartypes : pointer to count total number of variable type changes of all presolvers
531  * - nchgbds : pointer to count total number of variable bounds tightened of all presolvers
532  * - naddholes : pointer to count total number of domain holes added of all presolvers
533  * - ndelconss : pointer to count total number of deleted constraints of all presolvers
534  * - naddconss : pointer to count total number of added constraints of all presolvers
535  * - nupgdconss : pointer to count total number of upgraded constraints of all presolvers
536  * - nchgcoefs : pointer to count total number of changed coefficients of all presolvers
537  * - nchgsides : pointer to count total number of changed left/right hand sides of all presolvers
538  *
539  * output:
540  * - result : pointer to store the result of the presolving call
541  *
542  * possible return values for *result:
543  * - SCIP_UNBOUNDED : at least one variable is not bounded by any constraint in obj. direction -> problem is unbounded
544  * - SCIP_CUTOFF : at least one constraint is infeasible in the variable's bounds -> problem is infeasible
545  * - SCIP_SUCCESS : the presolving method found a reduction
546  * - SCIP_DIDNOTFIND : the presolving method searched, but did not find a presolving change
547  * - SCIP_DIDNOTRUN : the presolving method was skipped
548  * - SCIP_DELAYED : the presolving method was skipped, but should be called again
549  */
550 #define SCIP_DECL_CONSPRESOL(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss, int nrounds, \
551  SCIP_PRESOLTIMING presoltiming, int nnewfixedvars, int nnewaggrvars, int nnewchgvartypes, int nnewchgbds, int nnewholes, \
552  int nnewdelconss, int nnewaddconss, int nnewupgdconss, int nnewchgcoefs, int nnewchgsides, \
553  int* nfixedvars, int* naggrvars, int* nchgvartypes, int* nchgbds, int* naddholes, \
554  int* ndelconss, int* naddconss, int* nupgdconss, int* nchgcoefs, int* nchgsides, SCIP_RESULT* result)
555 
556 /** propagation conflict resolving method of constraint handler
557  *
558  * This method is called during conflict analysis. If the constraint handler wants to support conflict analysis,
559  * it should call SCIPinferVarLbCons() or SCIPinferVarUbCons() in domain propagation instead of SCIPchgVarLb() or
560  * SCIPchgVarUb() in order to deduce bound changes on variables.
561  * In the SCIPinferVarLbCons() and SCIPinferVarUbCons() calls, the handler provides the constraint, that deduced the
562  * variable's bound change, and an integer value "inferinfo" that can be arbitrarily chosen.
563  * The propagation conflict resolving method can then be implemented, to provide a "reason" for the bound
564  * changes, i.e., the bounds of variables at the time of the propagation, that forced the constraint to set the
565  * conflict variable's bound to its current value. It can use the "inferinfo" tag to identify its own propagation
566  * rule and thus identify the "reason" bounds. The bounds that form the reason of the assignment must then be provided
567  * by calls to SCIPaddConflictLb(), SCIPaddConflictUb(), SCIPaddConflictBd(), SCIPaddConflictRelaxedLb(),
568  * SCIPaddConflictRelaxedUb(), SCIPaddConflictRelaxedBd(), and/or SCIPaddConflictBinvar() in the propagation conflict
569  * resolving method.
570  *
571  * For example, the logicor constraint c = "x or y or z" fixes variable z to TRUE (i.e. changes the lower bound of z
572  * to 1.0), if both, x and y, are assigned to FALSE (i.e. if the upper bounds of these variables are 0.0). It uses
573  * SCIPinferVarLbCons(scip, z, 1.0, c, 0) to apply this assignment (an inference information tag is not needed by the
574  * constraint handler and is set to 0).
575  * In the conflict analysis, the constraint handler may be asked to resolve the lower bound change on z with
576  * constraint c, that was applied at a time given by a bound change index "bdchgidx".
577  * With a call to SCIPgetVarLbAtIndex(scip, z, bdchgidx, TRUE), the handler can find out, that the lower bound of
578  * variable z was set to 1.0 at the given point of time, and should call SCIPaddConflictUb(scip, x, bdchgidx) and
579  * SCIPaddConflictUb(scip, y, bdchgidx) to tell SCIP, that the upper bounds of x and y at this point of time were
580  * the reason for the deduction of the lower bound of z.
581  *
582  * input:
583  * - scip : SCIP main data structure
584  * - conshdlr : the constraint handler itself
585  * - cons : the constraint that deduced the bound change of the conflict variable
586  * - infervar : the conflict variable whose bound change has to be resolved
587  * - inferinfo : the user information passed to the corresponding SCIPinferVarLbCons() or SCIPinferVarUbCons() call
588  * - boundtype : the type of the changed bound (lower or upper bound)
589  * - bdchgidx : the index of the bound change, representing the point of time where the change took place
590  * - relaxedbd : the relaxed bound which is sufficient to be explained
591  *
592  * output:
593  * - result : pointer to store the result of the propagation conflict resolving call
594  *
595  * possible return values for *result:
596  * - SCIP_SUCCESS : the conflicting bound change has been successfully resolved by adding all reason bounds
597  * - SCIP_DIDNOTFIND : the conflicting bound change could not be resolved and has to be put into the conflict set
598  *
599  * @note it is sufficient to explain/resolve the relaxed bound
600  */
601 #define SCIP_DECL_CONSRESPROP(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons, \
602  SCIP_VAR* infervar, int inferinfo, SCIP_BOUNDTYPE boundtype, SCIP_BDCHGIDX* bdchgidx, SCIP_Real relaxedbd, \
603  SCIP_RESULT* result)
604 
605 /** variable rounding lock method of constraint handler
606  *
607  * This method is called, after a constraint is added or removed from the transformed problem.
608  * It should update the rounding locks of the given type of all associated variables with calls to
609  * SCIPaddVarLocksType(), depending on the way, the variable is involved in the constraint:
610  * - If the constraint may get violated by decreasing the value of a variable, it should call
611  * SCIPaddVarLocksType(scip, var, locktype, nlockspos, nlocksneg), saying that rounding down is
612  * potentially rendering the (positive) constraint infeasible and rounding up is potentially rendering the
613  * negation of the constraint infeasible.
614  * - If the constraint may get violated by increasing the value of a variable, it should call
615  * SCIPaddVarLocksType(scip, var, locktype, nlocksneg, nlockspos), saying that rounding up is
616  * potentially rendering the constraint's negation infeasible and rounding up is potentially rendering the
617  * constraint itself infeasible.
618  * - If the constraint may get violated by changing the variable in any direction, it should call
619  * SCIPaddVarLocksType(scip, var, locktype, nlockspos + nlocksneg, nlockspos + nlocksneg).
620  *
621  * Consider the linear constraint "3x -5y +2z <= 7" as an example. The variable rounding lock method of the
622  * linear constraint handler should call SCIPaddVarLocksType(scip, x, locktype, nlocksneg, nlockspos),
623  * SCIPaddVarLocksType(scip, y, locktype, nlockspos, nlocksneg) and
624  * SCIPaddVarLocksType(scip, z, type, nlocksneg, nlockspos) to tell SCIP, that rounding up of x and z and rounding
625  * down of y can destroy the feasibility of the constraint, while rounding down of x and z and rounding up of y can
626  * destroy the feasibility of the constraint's negation "3x -5y +2z > 7".
627  * A linear constraint "2 <= 3x -5y +2z <= 7" should call
628  * SCIPaddVarLocksType(scip, ..., nlockspos + nlocksneg, nlockspos + nlocksneg) on all variables, since rounding in both
629  * directions of each variable can destroy both the feasibility of the constraint and it's negation
630  * "3x -5y +2z < 2 or 3x -5y +2z > 7".
631  *
632  * If the constraint itself contains other constraints as sub constraints (e.g. the "or" constraint concatenation
633  * "c(x) or d(x)"), the rounding lock methods of these constraints should be called in a proper way.
634  * - If the constraint may get violated by the violation of the sub constraint c, it should call
635  * SCIPaddConsLocksType(scip, c, locktype, nlockspos, nlocksneg), saying that infeasibility of c may lead to
636  * infeasibility of the (positive) constraint, and infeasibility of c's negation (i.e. feasibility of c) may lead
637  * to infeasibility of the constraint's negation (i.e. feasibility of the constraint).
638  * - If the constraint may get violated by the feasibility of the sub constraint c, it should call
639  * SCIPaddConsLocksType(scip, c, locktype, nlocksneg, nlockspos), saying that infeasibility of c may lead to
640  * infeasibility of the constraint's negation (i.e. feasibility of the constraint), and infeasibility of c's negation
641  * (i.e. feasibility of c) may lead to infeasibility of the (positive) constraint.
642  * - If the constraint may get violated by any change in the feasibility of the sub constraint c, it should call
643  * SCIPaddConsLocksType(scip, c, locktype, nlockspos + nlocksneg, nlockspos + nlocksneg).
644  *
645  * Consider the or concatenation "c(x) or d(x)". The variable rounding lock method of the or constraint handler
646  * should call SCIPaddConsLocksType(scip, c, locktype, nlockspos, nlocksneg) and
647  * SCIPaddConsLocksType(scip, d, locktype, nlockspos, nlocksneg) to tell SCIP, that infeasibility of c and d can lead
648  * to infeasibility of "c(x) or d(x)".
649  *
650  * As a second example, consider the equivalence constraint "y <-> c(x)" with variable y and constraint c. The
651  * constraint demands, that y == 1 if and only if c(x) is satisfied. The variable lock method of the corresponding
652  * constraint handler should call SCIPaddVarLocksType(scip, y, locktype, nlockspos + nlocksneg, nlockspos + nlocksneg) and
653  * SCIPaddConsLocksType(scip, c, locktype, nlockspos + nlocksneg, nlockspos + nlocksneg), because any modification to the
654  * value of y or to the feasibility of c can alter the feasibility of the equivalence constraint.
655  *
656  * input:
657  * - scip : SCIP main data structure
658  * - conshdlr : the constraint handler itself
659  * - cons : the constraint that should lock rounding of its variables, or NULL if the constraint handler
660  * does not need constraints
661  * - locktype : type of rounding locks, i.e., SCIP_LOCKTYPE_MODEL or SCIP_LOCKTYPE_CONFLICT
662  * - nlockspos : number of times, the roundings should be locked for the constraint (may be negative)
663  * - nlocksneg : number of times, the roundings should be locked for the constraint's negation (may be negative)
664  */
665 #define SCIP_DECL_CONSLOCK(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons, SCIP_LOCKTYPE locktype, int nlockspos, int nlocksneg)
666 
667 /** constraint activation notification method of constraint handler
668  *
669  * WARNING! There may exist unprocessed events. For example, a variable's bound may have been already changed, but
670  * the corresponding bound change event was not yet processed.
671  *
672  * This method is always called after a constraint of the constraint handler was activated. The constraint
673  * handler may use this call to update his own (statistical) data.
674  *
675  * input:
676  * - scip : SCIP main data structure
677  * - conshdlr : the constraint handler itself
678  * - cons : the constraint that has been activated
679  */
680 #define SCIP_DECL_CONSACTIVE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons)
681 
682 /** constraint deactivation notification method of constraint handler
683  *
684  * WARNING! There may exist unprocessed events. For example, a variable's bound may have been already changed, but
685  * the corresponding bound change event was not yet processed.
686  *
687  * This method is always called before a constraint of the constraint handler is deactivated. The constraint
688  * handler may use this call to update his own (statistical) data.
689  *
690  * input:
691  * - scip : SCIP main data structure
692  * - conshdlr : the constraint handler itself
693  * - cons : the constraint that will be deactivated
694  */
695 #define SCIP_DECL_CONSDEACTIVE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons)
696 
697 /** constraint enabling notification method of constraint handler
698  *
699  * WARNING! There may exist unprocessed events. For example, a variable's bound may have been already changed, but
700  * the corresponding bound change event was not yet processed.
701  *
702  * This method is always called after a constraint of the constraint handler was enabled. The constraint
703  * handler may use this call to update his own (statistical) data.
704  *
705  * input:
706  * - scip : SCIP main data structure
707  * - conshdlr : the constraint handler itself
708  * - cons : the constraint that has been enabled
709  */
710 #define SCIP_DECL_CONSENABLE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons)
711 
712 /** constraint disabling notification method of constraint handler
713  *
714  * WARNING! There may exist unprocessed events. For example, a variable's bound may have been already changed, but
715  * the corresponding bound change event was not yet processed.
716  *
717  * This method is always called before a constraint of the constraint handler is disabled. The constraint
718  * handler may use this call to update his own (statistical) data.
719  *
720  * input:
721  * - scip : SCIP main data structure
722  * - conshdlr : the constraint handler itself
723  * - cons : the constraint that will be disabled
724  */
725 #define SCIP_DECL_CONSDISABLE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons)
726 
727 /** variable deletion method of constraint handler
728  *
729  * This method is optinal and only of interest if you are using SCIP as a branch-and-price framework. That means, you
730  * are generating new variables during the search. If you are not doing that just define the function pointer to be
731  * NULL.
732  *
733  * If this method gets implemented you should iterate over all constraints of the constraint handler and delete all
734  * variables that were marked for deletion by SCIPdelVar().
735  *
736  * input:
737  * - scip : SCIP main data structure
738  * - conshdlr : the constraint handler itself
739  * - conss : array of constraints in transformed problem
740  * - nconss : number of constraints in transformed problem
741  */
742 #define SCIP_DECL_CONSDELVARS(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** conss, int nconss)
743 
744 /** constraint display method of constraint handler
745  *
746  * The constraint handler can store a representation of the constraint into the given text file. Use the method
747  * SCIPinfoMessage() to push a string into the file stream.
748  *
749  * @note There are several methods which help to display variables. These are SCIPwriteVarName(), SCIPwriteVarsList(),
750  * SCIPwriteVarsLinearsum(), and SCIPwriteVarsPolynomial().
751  *
752  * input:
753  * - scip : SCIP main data structure
754  * - conshdlr : the constraint handler itself
755  * - cons : the constraint that should be displayed
756  * - file : the text file to store the information into
757  */
758 #define SCIP_DECL_CONSPRINT(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons, FILE* file)
759 
760 /** constraint copying method of constraint handler
761  *
762  * The constraint handler can provide a copy method which copies a constraint from one SCIP data structure into an other
763  * SCIP data structure. If a copy of a constraint is created, the constraint has to be captured. (The capture is usually
764  * already done due to the creation of the constraint).
765  *
766  * If the copy process was one to one, the valid pointer can be set to TRUE. Otherwise, you have to set this pointer to
767  * FALSE. In case all problem defining objects (constraint handlers and variable pricers) return a TRUE valid for all
768  * their copying calls, SCIP assumes that it is a overall one to one copy of the original instance. In this case any
769  * reductions made in the copied SCIP instance can be transfered to the original SCIP instance. If the valid pointer is
770  * set to TRUE and it was not a one to one copy, it might happen that optimal solutions are cut off.
771  *
772  * To get a copy of a variable in the target SCIP you should use the function SCIPgetVarCopy().
773  *
774  * input:
775  * - scip : target SCIP data structure
776  * - cons : pointer to store the created target constraint
777  * - name : name of constraint, or NULL if the name of the source constraint should be used
778  * - sourcescip : source SCIP data structure
779  * - sourceconshdlr : source constraint handler of the source SCIP
780  * - sourcecons : source constraint of the source SCIP
781  * - varmap : a SCIP_HASHMAP mapping variables of the source SCIP to corresponding variables of the target SCIP
782  * - consmap : a SCIP_HASHMAP mapping constraints of the source SCIP to corresponding constraints of the target SCIP
783  * - initial : should the LP relaxation of constraint be in the initial LP?
784  * - separate : should the constraint be separated during LP processing?
785  * - enforce : should the constraint be enforced during node processing?
786  * - check : should the constraint be checked for feasibility?
787  * - propagate : should the constraint be propagated during node processing?
788  * - local : is constraint only valid locally?
789  * - modifiable : is constraint modifiable (subject to column generation)?
790  * - dynamic : is constraint subject to aging?
791  * - removable : should the relaxation be removed from the LP due to aging or cleanup?
792  * - stickingatnode : should the constraint always be kept at the node where it was added, even
793  * if it may be moved to a more global node?
794  * - global : should a global or a local copy be created?
795  *
796  * output:
797  * - valid : pointer to store whether the copying was valid or not
798  */
799 #define SCIP_DECL_CONSCOPY(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONS** cons, const char* name, \
800  SCIP* sourcescip, SCIP_CONSHDLR* sourceconshdlr, SCIP_CONS* sourcecons, SCIP_HASHMAP* varmap, SCIP_HASHMAP* consmap, \
801  SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, \
802  SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode, \
803  SCIP_Bool global, SCIP_Bool* valid)
804 
805 /** constraint parsing method of constraint handler
806  *
807  * The constraint handler can provide a callback to parse the output created by the display method
808  * (\ref SCIP_DECL_CONSPRINT) and to create a constraint out of it.
809  *
810  * @note For parsing there are several methods which are handy. Have a look at: SCIPparseVarName(),
811  * SCIPparseVarsList(), SCIPparseVarsLinearsum(), SCIPparseVarsPolynomial(), SCIPstrToRealValue(), and
812  * SCIPstrCopySection().
813  *
814  * input:
815  * - scip : SCIP main data structure
816  * - conshdlr : the constraint handler itself
817  * - cons : pointer to store the created constraint
818  * - name : name of the constraint
819  * - str : string to parse
820  * - initial : should the LP relaxation of constraint be in the initial LP?
821  * - separate : should the constraint be separated during LP processing?
822  * - enforce : should the constraint be enforced during node processing?
823  * - check : should the constraint be checked for feasibility?
824  * - propagate : should the constraint be propagated during node processing?
825  * - local : is constraint only valid locally?
826  * - modifiable : is constraint modifiable (subject to column generation)?
827  * - dynamic : is constraint subject to aging?
828  * - removable : should the relaxation be removed from the LP due to aging or cleanup?
829  * - stickingatnode : should the constraint always be kept at the node where it was added, even
830  * if it may be moved to a more global node?
831  * output:
832  * - success : pointer to store whether the parsing was successful or not
833  */
834 #define SCIP_DECL_CONSPARSE(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS** cons, \
835  const char* name, const char* str, \
836  SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, \
837  SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode, SCIP_Bool* success)
838 
839 /** constraint method of constraint handler which returns the variables (if possible)
840  *
841  * The constraint handler can (this callback is optional) provide this callback to return the variables which are
842  * involved in that particular constraint. If this is possible, the variables should be copyied into the variables
843  * array and the success pointers has to be set to TRUE. Otherwise the success has to be set FALSE or the callback
844  * should not be implemented.
845  *
846  * input:
847  * - scip : SCIP main data structure
848  * - conshdlr : the constraint handler itself
849  * - cons : the constraint that should return its variable data
850  * - varssize : available slots in vars array which is needed to check if the array is large enough
851  *
852  * output:
853  * - vars : array to store/copy the involved variables of the constraint
854  * - success : pointer to store whether the variables are successfully copied
855  */
856 #define SCIP_DECL_CONSGETVARS(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons, \
857  SCIP_VAR** vars, int varssize, SCIP_Bool* success)
858 
859 /** constraint method of constraint handler which returns the number of variables (if possible)
860  *
861  * The constraint handler can (this callback is optional) provide this callback to return the number variable which are
862  * involved in that particular constraint. If this is not possible, the success pointers has to be set to FALSE or the
863  * callback should not be implemented.
864  *
865  * input:
866  * - scip : SCIP main data structure
867  * - conshdlr : the constraint handler itself
868  * - cons : constraint for which the number of variables is wanted
869  *
870  * output:
871  * - nvars : pointer to store the number of variables
872  * - success : pointer to store whether the constraint successfully returned the number of variables
873  */
874 #define SCIP_DECL_CONSGETNVARS(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_CONS* cons, \
875  int* nvars, SCIP_Bool* success)
876 
877 /** constraint handler method to suggest dive bound changes during the generic diving algorithm
878  *
879  * This callback is used inside the various diving heuristics of SCIP and does not affect the normal branching of the
880  * actual search. The constraint handler can provide this callback to render the current solution (even more)
881  * infeasible by suggesting one or several variable bound changes. In fact, since diving heuristics do not necessarily
882  * solve LP relaxations at every probing depth, some of the variable local bounds might already be conflicting with the
883  * solution values. The solution is rendered infeasible by determining bound changes that should be applied to the
884  * next explored search node via SCIPaddDiveBoundChange(). An alternative in case that the preferred bound change(s)
885  * were detected infeasible must be provided.
886  *
887  * The constraint handler must take care to only add bound changes that further shrink the variable domain.
888  *
889  * The success pointer must be used to indicate whether the constraint handler succeeded in selecting diving bound
890  * changes. The infeasible pointer should be set to TRUE if the constraint handler found a local infeasibility. If the
891  * constraint handler needs to select between several candidates, it may use the scoring mechanism of the diveset
892  * argument to control its choice.
893  *
894  * This callback is optional.
895  *
896  * @note: @p sol is usually the LP relaxation solution unless the caller of the method, usually a diving heuristic,
897  * does not solve LP relaxations at every depth
898  *
899  * input:
900  * - scip : SCIP main data structure
901  * - conshdlr : the constraint handler itself
902  * - diveset : diving settings for scoring
903  * - sol : current diving solution, usually the LP relaxation solution
904  *
905  * output:
906  * - success : pointer to store whether the constraint handler succeeded to determine dive bound changes
907  * - infeasible : pointer to store whether the constraint handler detected an infeasibility in the local node
908  */
909 #define SCIP_DECL_CONSGETDIVEBDCHGS(x) SCIP_RETCODE x (SCIP* scip, SCIP_CONSHDLR* conshdlr, SCIP_DIVESET* diveset, \
910  SCIP_SOL* sol, SCIP_Bool* success, SCIP_Bool* infeasible)
911 
912 #ifdef __cplusplus
913 }
914 #endif
915 
916 #endif
enum SCIP_LinConstype SCIP_LINCONSTYPE
Definition: type_cons.h:81
timing definitions for SCIP
type definitions for return codes for SCIP methods
SCIP_LinConstype
Definition: type_cons.h:61
type definitions for LP management
type definitions for primal heuristics
type definitions for SCIP&#39;s main datastructure
type definitions for problem variables
struct SCIP_ConsData SCIP_CONSDATA
Definition: type_cons.h:56
type definitions for storing primal CIP solutions
result codes for SCIP callback methods
struct SCIP_ConshdlrData SCIP_CONSHDLRDATA
Definition: type_cons.h:55
common defines and data types used in all packages of SCIP