Scippy

    SCIP

    Solving Constraint Integer Programs

    sepa_interminor.c
    Go to the documentation of this file.
    1/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
    2/* */
    3/* This file is part of the program and library */
    4/* SCIP --- Solving Constraint Integer Programs */
    5/* */
    6/* Copyright (c) 2002-2025 Zuse Institute Berlin (ZIB) */
    7/* */
    8/* Licensed under the Apache License, Version 2.0 (the "License"); */
    9/* you may not use this file except in compliance with the License. */
    10/* You may obtain a copy of the License at */
    11/* */
    12/* http://www.apache.org/licenses/LICENSE-2.0 */
    13/* */
    14/* Unless required by applicable law or agreed to in writing, software */
    15/* distributed under the License is distributed on an "AS IS" BASIS, */
    16/* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. */
    17/* See the License for the specific language governing permissions and */
    18/* limitations under the License. */
    19/* */
    20/* You should have received a copy of the Apache-2.0 license */
    21/* along with SCIP; see the file LICENSE. If not visit scipopt.org. */
    22/* */
    23/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
    24
    25/**@file sepa_interminor.c
    26 * @ingroup DEFPLUGINS_SEPA
    27 * @brief minor separator with intersection cuts
    28 * @author Felipe Serrano
    29 * @author Antonia Chmiela
    30 *
    31 * Let X be the matrix of auxiliary variables added for bilinear terms, X_{ij} = x_ix_j.
    32 * The separator enforces quadratic constraints det(2x2 minor of X) = 0 via intersection cuts.
    33 */
    34
    35/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
    36
    37#include <assert.h>
    38#include <string.h>
    39
    41#include "scip/expr.h"
    42#include "scip/expr_var.h"
    43#include "scip/expr_pow.h"
    44#include "scip/expr_product.h"
    45#include "scip/nlpi_ipopt.h"
    46#include "scip/cons_nonlinear.h"
    47
    48
    49
    50#define SEPA_NAME "interminor"
    51#define SEPA_DESC "intersection cuts separator to ensure that 2x2 minors of X (= xx') have determinant 0"
    52#define SEPA_PRIORITY 0
    53#define SEPA_FREQ -1
    54#define SEPA_MAXBOUNDDIST 1.0
    55#define SEPA_USESSUBSCIP FALSE /**< does the separator use a secondary SCIP instance? */
    56#define SEPA_DELAY FALSE /**< should separation method be delayed, if other separators found cuts? */
    57
    58#define DEFAULT_MINCUTVIOL 1e-4 /**< default minimum required violation of a cut */
    59#define DEFAULT_RANDSEED 157 /**< default random seed */
    60#define DEFAULT_MAXROUNDS 10 /**< maximal number of separation rounds per node (-1: unlimited) */
    61#define DEFAULT_MAXROUNDSROOT -1 /**< maximal number of separation rounds in the root node (-1: unlimited) */
    62#define BINSEARCH_MAXITERS 120 /**< default iteration limit for binary search */
    63#define DEFAULT_USESTRENGTHENING FALSE /**< default for using strengthend intersection cuts to separate */
    64#define DEFAULT_USEBOUNDS FALSE /**< default for using nonnegativity bounds when separating */
    65
    66/* TODO find a smarter less blunt way how to handle problems with many 2x2 minors (eigena2, elec100, sjup2) */
    67#define MAXNMINORS 100000 /**< maximal minors to consider; minor detection stops when MAXNMINORS many have been found */
    68
    69/*
    70 * Data structures
    71 */
    72
    73/** separator data */
    74struct SCIP_SepaData
    75{
    76 SCIP_VAR** minors; /**< variables of 2x2 minors; each minor is stored like (auxvar_x^2,auxvar_y^2,auxvar_xy) */
    77 SCIP_Bool* isdiagonal; /**< bool array determining if the variables appearing in the minor are diagonal */
    78 int nminors; /**< total number of minors */
    79 int minorssize; /**< size of minors array */
    80 int maxrounds; /**< maximal number of separation rounds per node (-1: unlimited) */
    81 int maxroundsroot; /**< maximal number of separation rounds in the root node (-1: unlimited) */
    82 SCIP_Bool detectedminors; /**< has minor detection be called? */
    83 SCIP_Real mincutviol; /**< minimum required violation of a cut */
    84 SCIP_RANDNUMGEN* randnumgen; /**< random number generation */
    85 SCIP_Bool usestrengthening; /**< whether to use strengthened intersection cuts to separate minors */
    86 SCIP_Bool usebounds; /**< whether to also enforce nonegativity bounds of principle minors */
    87};
    88
    89/* these represent a row */
    90struct rowdata
    91{
    92 int* vals; /**< index of the column */
    93 int rowidx; /**< index corresponding to variable of that row */
    94 int nvals; /**< number of nonzero entries in column */
    95 int valssize; /**< size of the array that is currently allocated */
    96 SCIP_HASHMAP* auxvars; /**< entry of the matrix */
    97};
    98
    99/*
    100 * Local methods
    101 */
    102
    103/** helper method to store a 2x2 minor in the separation data */
    104static
    106 SCIP* scip, /**< SCIP data structure */
    107 SCIP_SEPADATA* sepadata, /**< separator data */
    108 SCIP_VAR* auxvarxik, /**< auxiliary variable X_ik = x_i * x_k */
    109 SCIP_VAR* auxvarxil, /**< auxiliary variable X_il = x_i * x_l */
    110 SCIP_VAR* auxvarxjk, /**< auxiliary variable X_jk = x_j * x_k */
    111 SCIP_VAR* auxvarxjl, /**< auxiliary variable X_jl = x_j * x_l */
    112 SCIP_Bool isauxvarxikdiag, /**< is X_ik diagonal? (i.e. i = k) */
    113 SCIP_Bool isauxvarxildiag, /**< is X_il diagonal? (i.e. i = l) */
    114 SCIP_Bool isauxvarxjkdiag, /**< is X_jk diagonal? (i.e. j = k) */
    115 SCIP_Bool isauxvarxjldiag /**< is X_jl diagonal? (i.e. j = l) */
    116 )
    117{
    118 assert(sepadata != NULL);
    119 assert(auxvarxik != NULL);
    120 assert(auxvarxil != NULL);
    121 assert(auxvarxjk != NULL);
    122 assert(auxvarxjl != NULL);
    123 assert(auxvarxik != auxvarxil);
    124 assert(auxvarxjk != auxvarxjl);
    125
    126 SCIPdebugMsg(scip, "store 2x2 minor: [%s %s, %s %s]\n", SCIPvarGetName(auxvarxik), SCIPvarGetName(auxvarxil),
    127 SCIPvarGetName(auxvarxjk), SCIPvarGetName(auxvarxjl));
    128
    129 /* reallocate if necessary */
    130 if( sepadata->minorssize < 4 * (sepadata->nminors + 1) )
    131 {
    132 int newsize = SCIPcalcMemGrowSize(scip, 4 * (sepadata->nminors + 1));
    133 assert(newsize >= 4 * (sepadata->nminors + 1));
    134
    135 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &(sepadata->minors), sepadata->minorssize, newsize) );
    136 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &(sepadata->isdiagonal), sepadata->minorssize, newsize) );
    137 sepadata->minorssize = newsize;
    138 }
    139
    140 /* store minor */
    141 sepadata->minors[4 * sepadata->nminors] = auxvarxik;
    142 sepadata->minors[4 * sepadata->nminors + 1] = auxvarxil;
    143 sepadata->minors[4 * sepadata->nminors + 2] = auxvarxjk;
    144 sepadata->minors[4 * sepadata->nminors + 3] = auxvarxjl;
    145 sepadata->isdiagonal[4 * sepadata->nminors] = isauxvarxikdiag;
    146 sepadata->isdiagonal[4 * sepadata->nminors + 1] = isauxvarxildiag;
    147 sepadata->isdiagonal[4 * sepadata->nminors + 2] = isauxvarxjkdiag;
    148 sepadata->isdiagonal[4 * sepadata->nminors + 3] = isauxvarxjldiag;
    149 ++(sepadata->nminors);
    150
    151 /* capture variables */
    152 SCIP_CALL( SCIPcaptureVar(scip, auxvarxik) );
    153 SCIP_CALL( SCIPcaptureVar(scip, auxvarxil) );
    154 SCIP_CALL( SCIPcaptureVar(scip, auxvarxjk) );
    155 SCIP_CALL( SCIPcaptureVar(scip, auxvarxjl) );
    156
    157 return SCIP_OKAY;
    158}
    159
    160/** helper method to clear separation data */
    161static
    163 SCIP* scip, /**< SCIP data structure */
    164 SCIP_SEPADATA* sepadata /**< separator data */
    165 )
    166{
    167 int i;
    168
    169 assert(sepadata != NULL);
    170
    171 SCIPdebugMsg(scip, "clear separation data\n");
    172
    173 /* release captured variables */
    174 for( i = 0; i < 4 * sepadata->nminors; ++i )
    175 {
    176 assert(sepadata->minors[i] != NULL);
    177 SCIP_CALL( SCIPreleaseVar(scip, &sepadata->minors[i]) );
    178 }
    179
    180 /* free memory */
    181 SCIPfreeBlockMemoryArrayNull(scip, &sepadata->minors, sepadata->minorssize);
    182 SCIPfreeBlockMemoryArrayNull(scip, &sepadata->isdiagonal, sepadata->minorssize);
    183
    184 /* reset counters */
    185 sepadata->nminors = 0;
    186 sepadata->minorssize = 0;
    187
    188 return SCIP_OKAY;
    189}
    190
    191/** helper method to get the variables associated to a minor */
    192static
    194 SCIP_SEPADATA* sepadata, /**< separator data */
    195 int idx, /**< index of the stored minor */
    196 SCIP_VAR** auxvarxik, /**< auxiliary variable X_ik = x_i * x_k */
    197 SCIP_VAR** auxvarxil, /**< auxiliary variable X_il = x_i * x_l */
    198 SCIP_VAR** auxvarxjk, /**< auxiliary variable X_jk = x_j * x_k */
    199 SCIP_VAR** auxvarxjl, /**< auxiliary variable X_jl = x_j * x_l */
    200 SCIP_Bool* isauxvarxikdiag, /**< is X_ik diagonal? (i.e. i = k) */
    201 SCIP_Bool* isauxvarxildiag, /**< is X_il diagonal? (i.e. i = l) */
    202 SCIP_Bool* isauxvarxjkdiag, /**< is X_jk diagonal? (i.e. j = k) */
    203 SCIP_Bool* isauxvarxjldiag /**< is X_jl diagonal? (i.e. j = l) */
    204 )
    205{
    206 assert(auxvarxik != NULL);
    207 assert(auxvarxil != NULL);
    208 assert(auxvarxjk != NULL);
    209 assert(auxvarxjl != NULL);
    210
    211 *auxvarxik = sepadata->minors[4 * idx];
    212 *auxvarxil = sepadata->minors[4 * idx + 1];
    213 *auxvarxjk = sepadata->minors[4 * idx + 2];
    214 *auxvarxjl = sepadata->minors[4 * idx + 3];
    215
    216 *isauxvarxikdiag = sepadata->isdiagonal[4 * idx];
    217 *isauxvarxildiag = sepadata->isdiagonal[4 * idx + 1];
    218 *isauxvarxjkdiag = sepadata->isdiagonal[4 * idx + 2];
    219 *isauxvarxjldiag = sepadata->isdiagonal[4 * idx + 3];
    220
    221 return SCIP_OKAY;
    222}
    223
    224
    225/** adds a new entry (i.e., auxvar) of in (row, col) of matrix M.
    226 *
    227 * we have a matrix, M, indexed by the variables
    228 * M(xi, xk) is the auxiliary variable of xi * xk if it exists
    229 * We store, for each row of the matrix, the indices of the nonzero column entries (assoc with the given row) and the auxiliary variable for xi * xk
    230 * The nonzero column entries are stored as an array (struct rowdata)
    231 * So we have a hashmap mapping each variable (row of the matrix) with its array representing the nonzero entries of the row.
    232 */
    233static
    235 SCIP* scip, /**< SCIP data structure */
    236 SCIP_HASHMAP* rowmap, /**< hashmap of the rows of the matrix */
    237 SCIP_VAR* row, /**< variable corresponding to row of new entry */
    238 SCIP_VAR* col, /**< variable corresponding to column of new entry */
    239 SCIP_VAR* auxvar, /**< auxvar to insert into the matrix */
    240 int* rowindices, /**< array of indices of all variables corresponding to a row */
    241 int* nrows /**< number of rows */
    242 )
    243{
    244 SCIPdebugMsg(scip, "inserting %s in row %s and col %s \n", SCIPvarGetName(auxvar), SCIPvarGetName(row), SCIPvarGetName(col));
    245
    246 /* check whether variable has an array associated to it */
    247 if( SCIPhashmapExists(rowmap, (void*)row) )
    248 {
    249 struct rowdata* arr;
    250
    251 arr = (struct rowdata*)SCIPhashmapGetImage(rowmap, (void *)row);
    252
    253 /* reallocate if necessary */
    254 if( arr->valssize < arr->nvals + 1 )
    255 {
    256 int newsize = SCIPcalcMemGrowSize(scip, arr->nvals + 1);
    257 assert(newsize > arr->nvals + 1);
    258
    259 SCIP_CALL( SCIPreallocBufferArray(scip, &(arr->vals), newsize) );
    260 arr->valssize = newsize;
    261 }
    262
    263 /* insert */
    264 arr->vals[arr->nvals] = SCIPvarGetProbindex(col);
    265 SCIP_CALL( SCIPhashmapInsert(arr->auxvars, (void*)col, (void *)auxvar) );
    266 arr->nvals += 1;
    267 }
    268 else
    269 {
    270 struct rowdata* arr;
    271
    272 /* create index array */
    274 arr->valssize = 10;
    275 arr->nvals = 0;
    278
    279 /* insert */
    280 arr->rowidx = SCIPvarGetProbindex(row);
    281 arr->vals[arr->nvals] = SCIPvarGetProbindex(col);
    282 SCIP_CALL( SCIPhashmapInsert(arr->auxvars, (void*)col, (void *)auxvar) );
    283 arr->nvals += 1;
    284
    285 /* store in hashmap */
    286 SCIP_CALL( SCIPhashmapInsert(rowmap, (void*)row, (void *)arr) );
    287
    288 /* remember the new row */
    289 rowindices[*nrows] = SCIPvarGetProbindex(row);
    290 *nrows += 1;
    291 }
    292
    293 return SCIP_OKAY;
    294}
    295
    296/** method to detect and store principal minors */
    297static
    299 SCIP* scip, /**< SCIP data structure */
    300 SCIP_SEPADATA* sepadata /**< separator data */
    301 )
    302{
    303 SCIP_CONSHDLR* conshdlr;
    304 SCIP_EXPRITER* it;
    305 SCIP_HASHMAP* rowmap;
    306 int* rowvars = NULL;
    307 int* intersection;
    308 int nrowvars = 0;
    309 int c;
    310 int i;
    311
    312#ifdef SCIP_STATISTIC
    313 SCIP_Real totaltime = -SCIPgetTotalTime(scip);
    314#endif
    315
    316 assert(sepadata != NULL);
    317
    318 /* check whether minor detection has been called already */
    319 if( sepadata->detectedminors )
    320 return SCIP_OKAY;
    321
    322 assert(sepadata->minors == NULL);
    323 assert(sepadata->nminors == 0);
    324
    325 /* we assume that the auxiliary variables in the nonlinear constraint handler have been already generated */
    326 sepadata->detectedminors = TRUE;
    327
    328 /* check whether there are nonlinear constraints available */
    329 conshdlr = SCIPfindConshdlr(scip, "nonlinear");
    330 if( conshdlr == NULL || SCIPconshdlrGetNConss(conshdlr) == 0 )
    331 return SCIP_OKAY;
    332
    333 SCIPdebugMsg(scip, "call detectMinors()\n");
    334
    335 /* allocate memory */
    340
    341 /* initialize iterator */
    343
    344 for( c = 0; c < SCIPconshdlrGetNConss(conshdlr); ++c )
    345 {
    346 SCIP_CONS* cons;
    347 SCIP_EXPR* expr;
    348 SCIP_EXPR* root;
    349
    350 cons = SCIPconshdlrGetConss(conshdlr)[c];
    351 assert(cons != NULL);
    352 root = SCIPgetExprNonlinear(cons);
    353 assert(root != NULL);
    354
    355 for( expr = SCIPexpriterRestartDFS(it, root); !SCIPexpriterIsEnd(it); expr = SCIPexpriterGetNext(it) ) /*lint !e441*//*lint !e440*/
    356 {
    357 SCIP_EXPR** children;
    358 SCIP_VAR* auxvar;
    359
    360 SCIPdebugMsg(scip, "visit expression %p in constraint %s\n", (void*)expr, SCIPconsGetName(cons));
    361
    362 /* check whether the expression has an auxiliary variable */
    363 auxvar = SCIPgetExprAuxVarNonlinear(expr);
    364 if( auxvar == NULL )
    365 {
    366 SCIPdebugMsg(scip, "expression has no auxiliary variable -> skip\n");
    367 continue;
    368 }
    369
    370 children = SCIPexprGetChildren(expr);
    371
    372 /* check for expr = (x)^2 */
    373 if( SCIPexprGetNChildren(expr) == 1 && SCIPisExprPower(scip, expr)
    374 && SCIPgetExponentExprPow(expr) == 2.0
    375 && SCIPgetExprAuxVarNonlinear(children[0]) != NULL )
    376 {
    377 SCIP_VAR* quadvar;
    378
    379 assert(children[0] != NULL);
    380
    381 quadvar = SCIPgetExprAuxVarNonlinear(children[0]);
    382 assert(quadvar != NULL);
    383
    384 SCIP_CALL( insertIndex(scip, rowmap, quadvar, quadvar, auxvar, rowvars, &nrowvars) );
    385 }
    386 /* check for expr = x_i * x_k */
    387 else if( SCIPexprGetNChildren(expr) == 2 && SCIPisExprProduct(scip, expr)
    388 && SCIPgetExprAuxVarNonlinear(children[0]) != NULL && SCIPgetExprAuxVarNonlinear(children[1]) != NULL )
    389 {
    390 SCIP_VAR* xi;
    391 SCIP_VAR* xk;
    392
    393 assert(children[0] != NULL);
    394 assert(children[1] != NULL);
    395
    396 xi = SCIPgetExprAuxVarNonlinear(children[0]);
    397 xk = SCIPgetExprAuxVarNonlinear(children[1]);
    398
    399 SCIP_CALL( insertIndex(scip, rowmap, xk, xi, auxvar, rowvars, &nrowvars) );
    400 SCIP_CALL( insertIndex(scip, rowmap, xi, xk, auxvar, rowvars, &nrowvars) );
    401 }
    402 }
    403 }
    404
    405 /* sort the column entries */
    406 for( i = 0; i < nrowvars; ++i )
    407 {
    408 struct rowdata* row;
    409
    410 row = (struct rowdata*)SCIPhashmapGetImage(rowmap, (void *)SCIPgetVars(scip)[rowvars[i]]);
    411 SCIPsortInt(row->vals, row->nvals);
    412 }
    413
    414 /* store 2x2 minors */
    415 /* TODO: we might store some minors twice since the matrix is symmetric. Handle that! (see unit test for example) */
    416 for( i = 0; i < nrowvars; ++i )
    417 {
    418 int j;
    419 struct rowdata* rowi;
    420
    421 rowi = (struct rowdata*)SCIPhashmapGetImage(rowmap, (void *)SCIPgetVars(scip)[rowvars[i]]);
    422
    423 for( j = i + 1; j < nrowvars && sepadata->nminors < MAXNMINORS ; ++j )
    424 {
    425 struct rowdata* rowj;
    426 int ninter;
    427
    428 rowj = (struct rowdata*)SCIPhashmapGetImage(rowmap, (void *)SCIPgetVars(scip)[rowvars[j]]);
    429
    430 SCIPcomputeArraysIntersectionInt(rowi->vals, rowi->nvals, rowj->vals, rowj->nvals, intersection, &ninter);
    431
    432 if( ninter > 1)
    433 {
    434 int p;
    435
    436 for( p = 0; p < ninter - 1; ++p )
    437 {
    438 int q;
    439
    440 for( q = p + 1; q < ninter; ++q )
    441 {
    442 SCIP_HASHMAP* rowicols;
    443 SCIP_HASHMAP* rowjcols;
    444 SCIP_VAR* colk;
    445 SCIP_VAR* coll;
    446 SCIP_VAR* auxvarik;
    447 SCIP_VAR* auxvaril;
    448 SCIP_VAR* auxvarjk;
    449 SCIP_VAR* auxvarjl;
    450 int ii;
    451 int jj;
    452 int k;
    453 int l;
    454 SCIP_Bool isauxvarikdiag = FALSE;
    455 SCIP_Bool isauxvarildiag = FALSE;
    456 SCIP_Bool isauxvarjkdiag = FALSE;
    457 SCIP_Bool isauxvarjldiag = FALSE;
    458
    459 ii = rowi->rowidx;
    460 jj = rowj->rowidx;
    461 k = intersection[p];
    462 l = intersection[q];
    463
    464 rowicols = rowi->auxvars;
    465 rowjcols = rowj->auxvars;
    466
    467 colk = SCIPgetVars(scip)[k];
    468 coll = SCIPgetVars(scip)[l];
    469
    470 auxvarik = (SCIP_VAR*) SCIPhashmapGetImage(rowicols, colk);
    471 auxvaril = (SCIP_VAR*) SCIPhashmapGetImage(rowicols, coll);
    472 auxvarjk = (SCIP_VAR*) SCIPhashmapGetImage(rowjcols, colk);
    473 auxvarjl = (SCIP_VAR*) SCIPhashmapGetImage(rowjcols, coll);
    474
    475 if( ii == k )
    476 isauxvarikdiag = TRUE;
    477 else if( ii == l )
    478 isauxvarildiag = TRUE;
    479 if( jj == k )
    480 isauxvarjkdiag = TRUE;
    481 else if( jj == l )
    482 isauxvarjldiag = TRUE;
    483
    484 SCIP_CALL( sepadataAddMinor(scip, sepadata, auxvarik, auxvaril, auxvarjk, auxvarjl,
    485 isauxvarikdiag, isauxvarildiag, isauxvarjkdiag, isauxvarjldiag) );
    486 }
    487 }
    488 }
    489 }
    491 SCIPhashmapFree(&rowi->auxvars);
    493 }
    494
    495 SCIPdebugMsg(scip, "found %d principal minors in total\n", sepadata->nminors);
    496
    497 /* free memory */
    498 SCIPfreeBufferArray(scip, &intersection);
    499 SCIPfreeBufferArray(scip, &rowvars);
    500 SCIPhashmapFree(&rowmap);
    501 SCIPfreeExpriter(&it);
    502
    503#ifdef SCIP_STATISTIC
    504 totaltime += SCIPgetTotalTime(scip);
    505 SCIPstatisticMessage("MINOR DETECT %s %f %d %d\n", SCIPgetProbName(scip), totaltime, sepadata->nminors, maxminors);
    506#endif
    507
    508 return SCIP_OKAY;
    509}
    510
    511/** constructs map between lp position of a basic variable and its row in the tableau */
    512static
    514 SCIP* scip, /**< SCIP data structure */
    515 int* map /**< buffer to store the map */
    516 )
    517{
    518 int* basisind;
    519 int nrows;
    520 int i;
    521
    522 nrows = SCIPgetNLPRows(scip);
    523 SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
    524
    525 SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );
    526 for( i = 0; i < nrows; ++i )
    527 {
    528 if( basisind[i] >= 0 )
    529 map[basisind[i]] = i;
    530 }
    531
    532 SCIPfreeBufferArray(scip, &basisind);
    533
    534 return SCIP_OKAY;
    535}
    536
    537/** The restriction of the function representing the maximal S-free set to zlp + t * ray has the form
    538 * sqrt(A t^2 + B t + C) - (D t + E).
    539 * This function computes the coefficients A, B, C, D, E for the given ray.
    540 */
    541static
    543 SCIP* scip, /**< SCIP data structure */
    544 SCIP_Real* ray, /**< coefficients of ray */
    545 SCIP_VAR** vars, /**< variables */
    546 SCIP_Real* coefs, /**< buffer to store A, B, C, D, and E of cases 1, 2, 3, or 4a*/
    547 SCIP_Real* coefs4b, /**< buffer to store A, B, C, D, and E of case 4b */
    548 SCIP_Real* coefscondition, /**< buffer to store coefs for checking whether we are in case 4a or 4b */
    549 SCIP_Bool usebounds, /**< TRUE if we want to separate non-negative bound */
    550 SCIP_Real* ad, /**< coefs a and d for the hyperplane aTx + dTy <= 0 */
    551 SCIP_Bool* success /**< FALSE if we need to abort generation because of numerics */
    552 )
    553{
    554 SCIP_Real eigenvectors[16] = {1.0, 1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 1.0, -1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0};
    555 SCIP_Real eigenvalues[4] = {0.5, 0.5, -0.5, -0.5};
    556 SCIP_Real eigencoef = 0.7071067811865475244008443621048490;
    557 SCIP_Real* a;
    558 SCIP_Real* b;
    559 SCIP_Real* c;
    560 SCIP_Real* d;
    561 SCIP_Real* e;
    564 SCIP_Real norm1;
    565 SCIP_Real norm2;
    566 int negidx;
    567 int posidx;
    568 int i;
    569
    570 *success = TRUE;
    571
    572 /* set all coefficients to zero */
    573 memset(coefs, 0, 5 * sizeof(SCIP_Real));
    574 memset(coefs4b, 0, 5 * sizeof(SCIP_Real));
    575 norm1 = 0.0;
    576 norm2 = 0.0;
    577
    578 a = coefs;
    579 b = coefs + 1;
    580 c = coefs + 2;
    581 d = coefs + 3;
    582 e = coefs + 4;
    583
    584 negidx = 2;
    585 posidx = 0;
    586 for( i = 0; i < 4; ++i )
    587 {
    588 int j;
    589 SCIP_Real vzlp;
    590 SCIP_Real vdotray;
    591
    592 vzlp = 0;
    593 vdotray = 0;
    594
    595 /* compute eigenvec * ray and eigenvec * solution */
    596 for( j = 0; j < 4; ++j )
    597 {
    598 vdotray += eigencoef * eigenvectors[4 * i + j] * ray[j];
    599 vzlp += eigencoef * eigenvectors[4 * i + j] * SCIPvarGetLPSol(vars[j]);
    600 }
    601
    602 if( eigenvalues[i] > 0 )
    603 {
    604 /* positive eigenvalue: compute D and E */
    605 *d += eigenvalues[i] * vzlp * vdotray;
    606 *e += eigenvalues[i] * SQR( vzlp );
    607
    608 if( usebounds )
    609 {
    610 norm1 += eigenvalues[i] * (1 - SQR( ad[posidx] )) * SQR( vzlp );
    611 norm2 += sqrt( eigenvalues[i] ) * ad[posidx] * vzlp;
    612 ++posidx;
    613 }
    614 }
    615 else
    616 {
    617 /* negative eigenvalue: compute A, B, and C */
    618 *a -= eigenvalues[i] * SQR( vdotray );
    619 *b -= 2.0 * eigenvalues[i] * vzlp * vdotray;
    620 *c -= eigenvalues[i] * SQR( vzlp );
    621
    622 if( usebounds )
    623 {
    624 coefs4b[0] -= eigenvalues[i] * (1 - SQR( ad[negidx] )) * SQR( vdotray );
    625 coefs4b[1] -= 2.0 * eigenvalues[i] * (1 - SQR( ad[negidx] )) * vzlp * vdotray;
    626 coefs4b[2] -= eigenvalues[i] * (1 - SQR( ad[negidx] )) * SQR( vzlp );
    627 coefs4b[3] += sqrt( -eigenvalues[i] ) * ad[negidx] * vdotray;
    628 coefs4b[4] += sqrt( -eigenvalues[i] ) * ad[negidx] * vzlp;
    629 ++negidx;
    630 }
    631 }
    632 }
    633
    634 assert(*e > 0);
    635
    636 if( sqrt( *c ) - sqrt( *e ) >= 0.0 )
    637 {
    638 assert(sqrt( *c ) - sqrt( *e ) < 1e-6);
    639 *success = FALSE;
    640 return SCIP_OKAY;
    641 }
    642
    643 /* finish computation of coefficients when using bounds */
    644 if( usebounds )
    645 {
    646 coefscondition[0] = norm2 / sqrt( *e );
    647 coefscondition[1] = coefs4b[3];
    648 coefscondition[2] = coefs4b[4];
    649
    650 coefs4b[0] *= norm1 / *e;
    651 coefs4b[1] *= norm1 / *e;
    652 coefs4b[2] *= norm1 / *e;
    653 coefs4b[3] *= norm2 / sqrt( *e );
    654 coefs4b[4] *= norm2 / sqrt( *e );
    655
    656 coefs4b[3] += *d / sqrt( *e );
    657 coefs4b[4] += sqrt( *e );
    658
    659 assert( sqrt( coefs4b[2] ) - coefs4b[4] < 0.0 );
    660 }
    661
    662 /* finish computation of D and E */
    663 *e = sqrt( *e );
    664 *d /= *e;
    665
    666 /* maybe we want to avoid a large dynamism between A, B and C */
    667 max = 0.0;
    669 for( i = 0; i < 3; ++i )
    670 {
    671 SCIP_Real absval;
    672
    673 absval = ABS(coefs[i]);
    674 if( max < absval )
    675 max = absval;
    676 if( absval != 0.0 && absval < min )
    677 min = absval;
    678 }
    679
    680 if( SCIPisHugeValue(scip, max / min) )
    681 {
    682#ifdef DEBUG_INTERSECTIONCUT
    683 printf("Bad numerics: max(A,B,C)/min(A,B,C) is too large (%g)\n", max / min);
    684#endif
    685 *success = FALSE;
    686 return SCIP_OKAY;
    687 }
    688
    689 /* some sanity checks */
    690 assert(*c >= 0); /* radicand at zero */
    691 assert(sqrt( *c ) - *e < 0); /* the function at 0 must be negative */
    692 assert(*a >= 0); /* the function inside the root is convex */
    693
    694#ifdef DEBUG_INTERSECTIONCUT
    695 SCIPinfoMessage(scip, NULL, "Restriction yields: a,b,c,d,e %g %g %g %g %g\n", coefs[0], coefs[1], coefs[2], coefs[3], coefs[4]);
    696#endif
    697
    698 return SCIP_OKAY;
    699}
    700
    701/** returns phi(zlp + t * ray) = sqrt(A t^2 + B t + C) - (D t + E) */ /*lint -e{715}*/
    702static
    704 SCIP* scip, /**< SCIP data structure */
    705 SCIP_Real t, /**< argument of phi restricted to ray */
    706 SCIP_Real a, /**< value of A */
    707 SCIP_Real b, /**< value of B */
    708 SCIP_Real c, /**< value of C */
    709 SCIP_Real d, /**< value of D */
    710 SCIP_Real e /**< value of E */
    711 )
    712{
    713#ifdef INTERCUTS_DBLDBL
    714 SCIP_Real QUAD(lin);
    715 SCIP_Real QUAD(disc);
    716 SCIP_Real QUAD(tmp);
    717 SCIP_Real QUAD(root);
    718
    719 /* d * t + e */
    720 SCIPquadprecProdDD(lin, d, t);
    721 SCIPquadprecSumQD(lin, lin, e);
    722
    723 /* a * t * t */
    724 SCIPquadprecSquareD(disc, t);
    725 SCIPquadprecProdQD(disc, disc, a);
    726
    727 /* b * t */
    728 SCIPquadprecProdDD(tmp, b, t);
    729
    730 /* a * t * t + b * t */
    731 SCIPquadprecSumQQ(disc, disc, tmp);
    732
    733 /* a * t * t + b * t + c */
    734 SCIPquadprecSumQD(disc, disc, c);
    735
    736 /* sqrt(above): can't take sqrt of 0! */
    737 if( QUAD_TO_DBL(disc) == 0 )
    738 {
    739 QUAD_ASSIGN(root, 0.0);
    740 }
    741 else
    742 {
    743 SCIPquadprecSqrtQ(root, disc);
    744 }
    745
    746 /* final result */
    747 QUAD_SCALE(lin, -1.0);
    748 SCIPquadprecSumQQ(tmp, root, lin);
    749
    750 assert(!SCIPisInfinity(scip, t) || QUAD_TO_DBL(tmp) <= 0);
    751
    752 return QUAD_TO_DBL(tmp);
    753#else
    754 return sqrt( a * t * t + b * t + c ) - ( d * t + e );
    755#endif
    756}
    757
    758/** helper function of computeRoot: we want phi to be <= 0 */
    759static
    761 SCIP* scip, /**< SCIP data structure */
    762 SCIP_Real a, /**< value of A */
    763 SCIP_Real b, /**< value of B */
    764 SCIP_Real c, /**< value of C */
    765 SCIP_Real d, /**< value of D */
    766 SCIP_Real e, /**< value of E */
    767 SCIP_Real* sol /**< buffer to store solution; also gives initial point */
    768 )
    769{
    770 SCIP_Real lb = 0.0;
    771 SCIP_Real ub = *sol;
    772 SCIP_Real curr;
    773 int i;
    774
    775 for( i = 0; i < BINSEARCH_MAXITERS; ++i )
    776 {
    777 SCIP_Real phival;
    778
    779 curr = (lb + ub) / 2.0;
    780 phival = evalPhiAtRay(scip, curr, a, b, c, d, e);
    781#ifdef INTERCUT_MOREDEBUG
    782 printf("%d: lb,ub %.10f, %.10f. curr = %g -> phi at curr %g -> phi at lb %g \n", i, lb, ub, curr, phival, evalPhiAtRay(scip, lb, a, b, c, d, e));
    783#endif
    784
    785 if( phival <= 0.0 )
    786 {
    787 lb = curr;
    788 if( SCIPisFeasZero(scip, phival) || SCIPisFeasEQ(scip, ub, lb) )
    789 break;
    790 }
    791 else
    792 ub = curr;
    793 }
    794
    795 *sol = lb;
    796}
    797
    798/** checks if we are in case 4a, i.e., if
    799 * (num(xhat_{r+1}(zlp)) / E) * sqrt(A * tsol^2 + B * tsol + C) + w(ray) * tsol + num(yhat_{s+1}(zlp)) <= 0
    800 */
    801static
    803 SCIP_Real tsol, /**< t in the above formula */
    804 SCIP_Real* coefs, /**< coefficients A, B, C, D, and E of case 4a */
    805 SCIP_Real* coefscondition /**< extra coefficients needed for the evaluation of the condition:
    806 * num(xhat_{r+1}(zlp)) / E; w(ray); num(yhat_{s+1}(zlp)) */
    807 )
    808{
    809 return (coefscondition[0] * sqrt( coefs[0] * SQR( tsol ) + coefs[1] * tsol + coefs[2] ) + coefscondition[1] *
    810 tsol + coefscondition[2]) <= 0.0;
    811}
    812
    813/** finds smallest positive root phi by finding the smallest positive root of
    814 * (A - D^2) t^2 + (B - 2 D*E) t + (C - E^2) = 0
    815 *
    816 * However, we are conservative and want a solution such that phi is negative, but close to 0;
    817 * thus we correct the result with a binary search
    818 */
    819static
    821 SCIP* scip, /**< SCIP data structure */
    822 SCIP_Real* coefs /**< value of A */
    823 )
    824{
    825 SCIP_Real sol;
    826 SCIP_INTERVAL bounds;
    827 SCIP_INTERVAL result;
    828 SCIP_Real a = coefs[0];
    829 SCIP_Real b = coefs[1];
    830 SCIP_Real c = coefs[2];
    831 SCIP_Real d = coefs[3];
    832 SCIP_Real e = coefs[4];
    833
    834 /* there is an intersection point if and only if sqrt(A) > D: here we are beliving in math, this might cause
    835 * numerical issues
    836 */
    837 if( sqrt( a ) <= d )
    838 {
    839 sol = SCIPinfinity(scip);
    840
    841 return sol;
    842 }
    843
    845
    846 /* SCIPintervalSolveUnivariateQuadExpressionPositiveAllScalar finds all x such that a x^2 + b x >= c and x in bounds.
    847 * it is known that if tsol is the root we are looking for, then gamma(zlp + t * ray) <= 0 between 0 and tsol, thus
    848 * tsol is the smallest t such that (A - D^2) t^2 + (B - 2 D*E) t + (C - E^2) >= 0
    849 */
    851 e, -(c - e * e), bounds);
    852
    853 /* it can still be empty because of our infinity, I guess... */
    855
    856 /* check that solution is acceptable, ideally it should be <= 0, however when it is positive, we trigger a binary
    857 * search to make it negative. This binary search might return a solution point that is not at accurately 0 as the
    858 * one obtained from the function above. Thus, it might fail to satisfy the condition of case 4b in some cases, e.g.,
    859 * ex8_3_1, bchoco05, etc
    860 */
    861 if( evalPhiAtRay(scip, sol, a, b, c, d, e) <= 1e-10 )
    862 {
    863#ifdef INTERCUT_MOREDEBUG
    864 printf("interval solution returned %g -> phival = %g, believe it\n", sol, evalPhiAtRay(sol, a, b, c, d, e));
    865 printf("don't do bin search\n");
    866#endif
    867
    868 return sol;
    869 }
    870 else
    871 {
    872 /* perform a binary search to make it negative: this might correct a wrong infinity (e.g. crudeoil_lee1_05) */
    873#ifdef INTERCUT_MOREDEBUG
    874 printf("do bin search because phival is %g\n", evalPhiAtRay(scip, sol, a, b, c, d, e));
    875#endif
    876 doBinarySearch(scip, a, b, c, d, e, &sol);
    877 }
    878
    879 return sol;
    880}
    881
    882/** The maximal S-free set is gamma(z) <= 0; we find the intersection point of the ray `ray` starting from zlp with the
    883 * boundary of the S-free set.
    884 * That is, we find t >= 0 such that gamma(zlp + t * ray) = 0.
    885 *
    886 * In cases 1,2, and 3, gamma is of the form
    887 * gamma(zlp + t * ray) = sqrt(A t^2 + B t + C) - (D t + E)
    888 *
    889 * In the case 4 gamma is of the form
    890 * gamma(zlp + t * ray) = sqrt(A t^2 + B t + C) - (D t + E) if some condition holds
    891 * sqrt(A' t^2 + B' t + C') - (D' t + E') otherwise
    892 *
    893 * It can be shown (given the special properties of gamma) that the smallest positive root of each function of the form
    894 * sqrt(a t^2 + b t + c) - (d t + e)
    895 * is the same as the smallest positive root of the quadratic equation:
    896 * (sqrt(a t^2 + b t + c) - (d t + e)) * (sqrt(a t^2 + b t + c) + (d t + e)) = 0
    897 * <==> (a - d^2) t^2 + (b - 2 d*e) t + (c - e^2) = 0
    898 *
    899 * So, in cases 1, 2, and 3, this function just returns the solution of the above equation.
    900 * In case 4, it first solves the equation assuming we are in the first piece.
    901 * If there is no solution, then the second piece can't have a solution (first piece >= second piece for all t)
    902 * Then we check if the solution satisfies the condition.
    903 * If it doesn't then we solve the equation for the second piece.
    904 * If it has a solution, then it _has_ to be the solution.
    905 */
    906static
    908 SCIP* scip, /**< SCIP data structure */
    909 SCIP_Bool usebounds, /**< whether we are in case 4 or not */
    910 SCIP_Real* coefs, /**< values of A, B, C, D, and E of cases 1, 2, 3, or 4a */
    911 SCIP_Real* coefs4b, /**< values of A, B, C, D, and E of case 4b */
    912 SCIP_Real* coefscondition /**< values needed to evaluate condition of case 4 */
    913 )
    914{
    915 SCIP_Real sol;
    916 SCIP_Real sol4b;
    917
    918 assert(coefs != NULL);
    919
    920 if( ! usebounds )
    921 return computeRoot(scip, coefs);
    922
    923 assert(coefs4b != NULL);
    924 assert(coefscondition != NULL);
    925
    926 /* compute solution of first piece */
    927 sol = computeRoot(scip, coefs);
    928
    929 /* if there is no solution --> second piece doesn't have solution */
    930 if( SCIPisInfinity(scip, sol) )
    931 {
    932 /* this assert fails on multiplants_mtg5 the problem is that sqrt(A) <= D in 4a but not in 4b,
    933 * now, this is impossible since the phi4a >= phi4b, so actually sqrt(A) is 10e-15 away from
    934 * D in 4b
    935 */
    936 /* assert(SCIPisInfinity(scip, computeRoot(scip, coefs4b))); */
    937 return sol;
    938 }
    939
    940 /* if solution of 4a is in 4a, then return */
    941 if( isCase4a(sol, coefs, coefscondition) )
    942 return sol;
    943
    944 /* not on 4a --> then the intersection point is whatever 4b says: as phi4a >= phi4b, the solution of phi4b should
    945 * always be larger (but shouldn't be equal at this point given that isCase4a failed, and the condition function
    946 * evaluates to 0 when phi4a == phi4b) than the solution of phi4a; However, because of numerics (or limits in the
    947 * binary search) we can find a slightly smaller solution; thus, we just keep the larger one
    948 */
    949 sol4b = computeRoot(scip, coefs4b);
    950
    951 return MAX(sol, sol4b);
    952}
    953
    954/** adds cutcoef * (col - col*) to rowprep */
    955static
    957 SCIP* scip, /**< SCIP data structure */
    958 SCIP_ROWPREP* rowprep, /**< rowprep to store intersection cut */
    959 SCIP_Real cutcoef, /**< cut coefficient */
    960 SCIP_COL* col /**< column to add to rowprep */
    961 )
    962{
    963 assert(col != NULL);
    964
    965#ifdef DEBUG_INTERCUTS_NUMERICS
    966 SCIPinfoMessage(scip, NULL, "adding col %s to cut. %g <= col <= %g\n", SCIPvarGetName(SCIPcolGetVar(col)),
    968 SCIPinfoMessage(scip, NULL, "col is active at %s. Value %.15f\n", SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_LOWER ? "lower bound" :
    969 "upper bound" , SCIPcolGetPrimsol(col));
    970#endif
    971
    972 SCIP_CALL( SCIPaddRowprepTerm(scip, rowprep, SCIPcolGetVar(col), cutcoef) );
    973 SCIProwprepAddConstant(rowprep, -cutcoef * SCIPcolGetPrimsol(col) );
    974
    975 return SCIP_OKAY;
    976}
    977
    978/** adds cutcoef * (slack - slack*) to rowprep
    979 *
    980 * row is lhs <= <coefs, vars> + constant <= rhs, thus slack is defined by
    981 * slack + <coefs, vars> + constant = side
    982 * If row (slack) is at upper, it means that <coefs,vars*> + constant = rhs, and so
    983 * slack* = side - rhs --> slack - slack* = rhs - <coefs, vars> - constant.
    984 * If row (slack) is at lower, then <coefs,vars*> + constant = lhs, and so
    985 * slack* = side - lhs --> slack - slack* = lhs - <coefs, vars> - constant.
    986 */
    987static
    989 SCIP* scip, /**< SCIP data structure */
    990 SCIP_ROWPREP* rowprep, /**< rowprep to store intersection cut */
    991 SCIP_Real cutcoef, /**< cut coefficient */
    992 SCIP_ROW* row, /**< row, whose slack we are adding to rowprep */
    993 SCIP_Bool* success /**< buffer to store whether the row is nonbasic enough */
    994 )
    995{
    996 int i;
    997 SCIP_COL** rowcols;
    998 SCIP_Real* rowcoefs;
    999 int nnonz;
    1000
    1001 assert(row != NULL);
    1002
    1003 rowcols = SCIProwGetCols(row);
    1004 rowcoefs = SCIProwGetVals(row);
    1005 nnonz = SCIProwGetNLPNonz(row);
    1006
    1007#ifdef DEBUG_INTERCUTS_NUMERICS
    1008 SCIPinfoMessage(scip, NULL, "adding slack var row_%d to cut. %g <= row <= %g\n", SCIProwGetLPPos(row), SCIProwGetLhs(row), SCIProwGetRhs(row));
    1009 SCIPinfoMessage(scip, NULL, "row is active at %s = %.15f Activity %.15f\n", SCIProwGetBasisStatus(row) == SCIP_BASESTAT_LOWER ? "lhs" :
    1011 SCIPgetRowActivity(scip, row));
    1012#endif
    1013
    1015 {
    1016 assert(!SCIPisInfinity(scip, -SCIProwGetLhs(row)));
    1018 {
    1019 *success = FALSE;
    1020 return SCIP_OKAY;
    1021 }
    1022
    1023 SCIProwprepAddConstant(rowprep, SCIProwGetLhs(row) * cutcoef);
    1024 }
    1025 else
    1026 {
    1027 assert(!SCIPisInfinity(scip, SCIProwGetRhs(row)));
    1029 {
    1030 *success = FALSE;
    1031 return SCIP_OKAY;
    1032 }
    1033
    1034 SCIProwprepAddConstant(rowprep, SCIProwGetRhs(row) * cutcoef);
    1035 }
    1036
    1037 for( i = 0; i < nnonz; i++ )
    1038 {
    1039 SCIP_CALL( SCIPaddRowprepTerm(scip, rowprep, SCIPcolGetVar(rowcols[i]), -rowcoefs[i] * cutcoef) );
    1040 }
    1041
    1042 SCIProwprepAddConstant(rowprep, -SCIProwGetConstant(row) * cutcoef);
    1043
    1044 return SCIP_OKAY;
    1045}
    1046
    1047/** get the tableau rows of the variables in vars */
    1048static
    1050 SCIP* scip, /**< SCIP data structure */
    1051 SCIP_VAR** vars, /**< variables in the minor */
    1052 int* basicvarpos2tableaurow,/**< map between basic var and its tableau row */
    1053 SCIP_HASHMAP* tableau, /**< map between var an its tableau row */
    1054 SCIP_Real** tableaurows, /**< buffer to store tableau row */
    1055 SCIP_Bool* success /**< set to TRUE if no variable had basisstat = ZERO */
    1056 )
    1057{
    1058 int v;
    1059 int nrows;
    1060 int ncols;
    1061
    1062 *success = TRUE;
    1063
    1064 nrows = SCIPgetNLPRows(scip);
    1065 ncols = SCIPgetNLPCols(scip);
    1066
    1067 /* check if we have the tableau row of the variable and if not compute it */
    1068 for( v = 0; v < 4; ++v )
    1069 {
    1070 if( ! SCIPhashmapExists(tableau, (void*)vars[v]) )
    1071 {
    1072 SCIP_COL* col;
    1073
    1074 /* get column of variable */
    1075 col = SCIPvarGetCol(vars[v]);
    1076
    1077 /* if variable is basic, then get its tableau row and insert it in the hashmap */
    1079 {
    1080 int lppos;
    1081 SCIP_Real* densetableaurow;
    1082
    1083 lppos = SCIPcolGetLPPos(col);
    1084 SCIP_CALL( SCIPallocBufferArray(scip, &densetableaurow, ncols + nrows) );
    1085
    1086 SCIP_CALL( SCIPgetLPBInvRow(scip, basicvarpos2tableaurow[lppos], &densetableaurow[ncols], NULL, NULL) );
    1087 SCIP_CALL( SCIPgetLPBInvARow(scip, basicvarpos2tableaurow[lppos], &densetableaurow[ncols], densetableaurow, NULL, NULL) );
    1088
    1089 /* insert tableau row in hashmap*/
    1090 SCIP_CALL( SCIPhashmapInsert(tableau, (void*)vars[v], (void *)densetableaurow) );
    1091 }
    1092 else if( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_ZERO )
    1093 {
    1094 *success = FALSE;
    1095 return SCIP_OKAY; /* don't even bother */
    1096 }
    1097 else
    1098 {
    1099 SCIP_CALL( SCIPhashmapInsert(tableau, (void*)vars[v], (void *)NULL) );
    1100 }
    1101 }
    1102
    1103 /* get tableau row of var */
    1104 tableaurows[v] = (SCIP_Real *)SCIPhashmapGetImage(tableau, (void*)vars[v]);
    1105 }
    1106 return SCIP_OKAY;
    1107}
    1108
    1109/** computes the cut coefs of the non-basic (non-slack) variables (correspond to cols) and adds them to the
    1110 * intersection cut
    1111 */
    1112static
    1114 SCIP* scip, /**< SCIP data structure */
    1115 SCIP_VAR** vars, /**< variables */
    1116 SCIP_Real** tableaurows, /**< tableau rows corresponding to the variables in vars */
    1117 SCIP_ROWPREP* rowprep, /**< store cut */
    1118 SCIP_Real* rays, /**< buffer to store rays */
    1119 int* nrays, /**< pointer to store number of nonzero rays */
    1120 int* rayslppos, /**< buffer to store lppos of nonzero rays */
    1121 SCIP_Real* interpoints, /**< buffer to store intersection points or NULL if not needed */
    1122 SCIP_Bool usebounds, /**< TRUE if we want to separate non-negative bound */
    1123 SCIP_Real* ad, /**< coefs a and d for the hyperplane aTx + dTy <= 0 */
    1124 SCIP_Bool* success /**< pointer to store whether the generation of cutcoefs was successful */
    1125 )
    1126{
    1127 int i;
    1128 int ncols;
    1129 SCIP_COL** cols;
    1130
    1131 *success = TRUE;
    1132
    1133 /* loop over non-basic (non-slack) variables */
    1134 cols = SCIPgetLPCols(scip);
    1135 ncols = SCIPgetNLPCols(scip);
    1136 for( i = 0; i < ncols; ++i )
    1137 {
    1138 SCIP_COL* col;
    1139 SCIP_Real coefs[5];
    1140 SCIP_Real coefs4b[5];
    1141 SCIP_Real coefscondition[3];
    1142 SCIP_Real factor;
    1143 SCIP_Bool israynonzero;
    1144 SCIP_Real cutcoef;
    1145 SCIP_Real interpoint;
    1146 int v;
    1147
    1148 col = cols[i];
    1149
    1150 /* set factor to store entries of ray as = [-BinvL, BinvU] */
    1152 factor = -1.0;
    1154 factor = 1.0;
    1155 else if( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_ZERO )
    1156 {
    1157 *success = FALSE;
    1158 return SCIP_OKAY;
    1159 }
    1160 else
    1161 continue;
    1162
    1163 /* build the ray */
    1164 israynonzero = FALSE;
    1165 for( v = 0; v < 4; ++v )
    1166 {
    1167 if( tableaurows[v] != NULL )
    1168 rays[(*nrays) * 4 + v] = factor * (SCIPisZero(scip, tableaurows[v][i]) ? 0.0 : tableaurows[v][i]);
    1169 else
    1170 {
    1171 if( col == SCIPvarGetCol(vars[v]) )
    1172 rays[(*nrays) * 4 + v] = -factor;
    1173 else
    1174 rays[(*nrays) * 4 + v] = 0.0;
    1175 }
    1176
    1177 israynonzero = israynonzero || (rays[(*nrays) * 4 + v] != 0.0);
    1178 }
    1179
    1180 /* do nothing if ray is 0 */
    1181 if( ! israynonzero )
    1182 continue;
    1183
    1184 /* compute the cut */
    1185 SCIP_CALL( computeRestrictionToRay(scip, &rays[(*nrays) * 4], vars, coefs, coefs4b, coefscondition, usebounds,
    1186 ad, success) );
    1187
    1188 if( *success == FALSE )
    1189 return SCIP_OKAY;
    1190
    1191 /* compute intersection point */
    1192 interpoint = computeIntersectionPoint(scip, usebounds, coefs, coefs4b, coefscondition);
    1193
    1194 /* store intersection points */
    1195 interpoints[*nrays] = interpoint;
    1196
    1197 /* remember lppos */
    1198 rayslppos[*nrays] = i;
    1199
    1200 /* count nonzero rays */
    1201 *nrays += 1;
    1202
    1203 /* compute cut coef */
    1204 cutcoef = SCIPisInfinity(scip, interpoint) ? 0.0 : 1.0 / interpoint;
    1205
    1206 /* add var to cut: if variable is nonbasic at upper we have to flip sign of cutcoef */
    1209 cutcoef, col) );
    1210 }
    1211
    1212 return SCIP_OKAY;
    1213}
    1214
    1215/** computes the cut coefs of the non-basic slack variables (correspond to rows) and adds them to the
    1216 * intersection cut
    1217 */
    1218static
    1220 SCIP* scip, /**< SCIP data structure */
    1221 SCIP_VAR** vars, /**< variables */
    1222 SCIP_Real** tableaurows, /**< tableau rows corresponding to the variables in vars */
    1223 SCIP_ROWPREP* rowprep, /**< store cut */
    1224 SCIP_Real* rays, /**< buffer to store rays */
    1225 int* nrays, /**< pointer to store number of nonzero rays */
    1226 int* rayslppos, /**< buffer to store lppos of nonzero rays */
    1227 SCIP_Real* interpoints, /**< buffer to store intersection points or NULL if not needed */
    1228 SCIP_Bool usebounds, /**< TRUE if we want to separate non-negative bound */
    1229 SCIP_Real* ad, /**< coefs a and d for the hyperplane aTx + dTy <= 0 */
    1230 SCIP_Bool* success /**< pointer to store whether the generation of cutcoefs was successful */
    1231 )
    1232{
    1233 int i;
    1234 int nrows;
    1235 int ncols;
    1236 SCIP_ROW** rows;
    1237
    1238 nrows = SCIPgetNLPRows(scip);
    1239 ncols = SCIPgetNLPCols(scip);
    1240
    1241 *success = TRUE;
    1242
    1243 /* loop over non-basic slack variables */
    1244 rows = SCIPgetLPRows(scip);
    1245 for( i = 0; i < nrows; ++i )
    1246 {
    1247 SCIP_ROW* row;
    1248 SCIP_Real coefs[5];
    1249 SCIP_Real coefs4b[5];
    1250 SCIP_Real coefscondition[3];
    1251 SCIP_Real factor;
    1252 SCIP_Bool israynonzero;
    1253 SCIP_Real cutcoef;
    1254 SCIP_Real interpoint;
    1255 int v;
    1256
    1257 row = rows[i];
    1258
    1259 /* set factor to store entries of ray as = [BinvL, -BinvU] */
    1261 factor = 1.0;
    1263 factor = -1.0;
    1264 else if( SCIProwGetBasisStatus(row) == SCIP_BASESTAT_ZERO )
    1265 {
    1266 *success = FALSE;
    1267 return SCIP_OKAY;
    1268 }
    1269 else
    1270 continue;
    1271
    1272 /* build the ray */
    1273 israynonzero = FALSE;
    1274 for( v = 0; v < 4; ++v )
    1275 {
    1276 int idx;
    1277
    1278 idx = ncols + i;
    1279
    1280 if( tableaurows[v] != NULL )
    1281 rays[(*nrays) * 4 + v] = factor * (SCIPisZero(scip, tableaurows[v][idx]) ? 0.0 : tableaurows[v][idx]);
    1282 else
    1283 {
    1284 /* TODO: We assume that slack variables can never occure in the minor. This is correct, right? */
    1285 rays[(*nrays) * 4 + v] = 0.0;
    1286 }
    1287
    1288 israynonzero = israynonzero || (rays[(*nrays) * 4 + v] != 0.0);
    1289 }
    1290
    1291 /* do nothing if ray is 0 */
    1292 if( ! israynonzero )
    1293 continue;
    1294
    1295 /* compute the cut */
    1296 SCIP_CALL( computeRestrictionToRay(scip, &rays[(*nrays) * 4], vars, coefs, coefs4b, coefscondition, usebounds,
    1297 ad, success) );
    1298
    1299 if( *success == FALSE )
    1300 return SCIP_OKAY;
    1301
    1302 /* compute intersection point */
    1303 interpoint = computeIntersectionPoint(scip, usebounds, coefs, coefs4b, coefscondition);
    1304
    1305 /* store intersection points */
    1306 interpoints[*nrays] = interpoint;
    1307
    1308 /* store lppos of ray, make it negative so we can differentiate between cols and rows */
    1309 rayslppos[*nrays] = -i - 1;
    1310
    1311 /* count nonzero rays */
    1312 *nrays += 1;
    1313
    1314 /* compute cut coef */
    1315 cutcoef = SCIPisInfinity(scip, interpoint) ? 0.0 : 1.0 / interpoint;
    1316
    1317 /* add var to cut: if variable is nonbasic at upper we have to flip sign of cutcoef */
    1319
    1321 -cutcoef, row, success) ); /* rows have flipper base status! */
    1322 }
    1323
    1324 return SCIP_OKAY;
    1325}
    1326
    1327/* checks if two rays are linearly dependent */
    1328static
    1330 SCIP* scip, /**< SCIP data structure */
    1331 SCIP_Real* ray1, /**< coefficients of ray 1 */
    1332 SCIP_Real* ray2, /**< coefficients of ray 2 */
    1333 SCIP_Real* coef /**< pointer to store coef (s.t. r1 = coef * r2) in case rays are dependent */
    1334 )
    1335{
    1336 int i;
    1337
    1338 *coef = 0.0;
    1339
    1340 for( i = 0; i < 4; ++i )
    1341 {
    1342 /* rays cannot be dependent if one ray has zero entry and the other one doesn't */
    1343 if( (SCIPisZero(scip, ray1[i]) && ! SCIPisZero(scip, ray2[i])) ||
    1344 (! SCIPisZero(scip, ray1[i]) && SCIPisZero(scip, ray2[i])) )
    1345 {
    1346 return FALSE;
    1347 }
    1348
    1349 if( *coef != 0.0 )
    1350 {
    1351 /* cannot be dependent if the coefs aren't equal for all entries */
    1352 if( ! SCIPisFeasEQ(scip, *coef, ray1[i] / ray2[i]) )
    1353 return FALSE;
    1354 }
    1355 else
    1356 *coef = ray1[i] / ray2[i];
    1357 }
    1358
    1359 return TRUE;
    1360}
    1361
    1362/** finds the smallest negative steplength for the current ray r_idx such that the combination
    1363 * of r_idx with all rays not in the recession cone is in the recession cone
    1364 */
    1365static
    1367 SCIP* scip, /**< SCIP data structure */
    1368 SCIP_Real* rays, /**< rays */
    1369 int nrays, /**< number of nonzero rays */
    1370 int idx, /**< index of current ray we want to find rho for */
    1371 SCIP_Real* interpoints, /**< intersection points of nonzero rays */
    1372 SCIP_VAR** vars, /**< variables */
    1373 SCIP_Real* rho, /**< pointer to store the optimal rho */
    1374 SCIP_Bool usebounds, /**< TRUE if we want to separate non-negative bound */
    1375 SCIP_Real* ad, /**< coefs a and d for the hyperplane aTx + dTy <= 0 */
    1376 SCIP_Bool* success /**< TRUE if computation of rho was successful */
    1377 )
    1378{
    1379 int i;
    1380
    1381 *success = TRUE;
    1382
    1383 /* go through all rays not in the recession cone and compute the largest negative steplength possible. The
    1384 * smallest of them is then the steplength rho we use for the current ray */
    1385 *rho = 0;
    1386 for( i = 0; i < nrays; ++i )
    1387 {
    1388 SCIP_Real currentrho;
    1389 SCIP_Real coef;
    1390
    1391 if( SCIPisInfinity(scip, interpoints[i]) )
    1392 continue;
    1393
    1394 /* if the rays are linearly independent, we don't need to search for rho */
    1395 if( raysAreDependent(scip, &rays[4 * i], &rays[4 * idx], &coef) )
    1396 currentrho = coef * interpoints[i];
    1397 else
    1398 {
    1399 SCIP_Real lb;
    1400 SCIP_Real ub;
    1401 SCIP_Real alpha;
    1402 int j;
    1403
    1404 /* do binary search by lookig at the convex combinations of r_i and r_j */
    1405 lb = 0.0;
    1406 ub = 1.0;
    1407
    1408 for( j = 0; j < BINSEARCH_MAXITERS; ++j )
    1409 {
    1410 SCIP_Real coefs[5];
    1411 SCIP_Real coefs4b[5];
    1412 SCIP_Real coefscondition[3];
    1413 SCIP_Real newray[4];
    1414 SCIP_Real interpoint;
    1415 int k;
    1416
    1417 alpha = (lb + ub) / 2.0;
    1418
    1419 /* build the ray alpha * ray_i + (1 - alpha) * ray_idx */
    1420 for( k = 0; k < 4; ++k )
    1421 newray[k] = alpha * rays[4 * i + k] - (1 - alpha) * rays[4 * idx + k];
    1422
    1423 /* restrict phi to the "new" ray */
    1424 SCIP_CALL( computeRestrictionToRay(scip, newray, vars, coefs, coefs4b, coefscondition, usebounds,
    1425 ad, success) );
    1426
    1427 if( ! *success )
    1428 return SCIP_OKAY;
    1429
    1430 /* check if restriction to "new" ray is numerically nasty. If so, treat the corresponding rho as if phi is
    1431 * positive
    1432 */
    1433
    1434 /* compute intersection point */
    1435 interpoint = computeIntersectionPoint(scip, usebounds, coefs, coefs4b, coefscondition);
    1436
    1437 /* no root exists */
    1438 if( SCIPisInfinity(scip, interpoint) )
    1439 {
    1440 lb = alpha;
    1441 if( SCIPisEQ(scip, ub, lb) )
    1442 break;
    1443 }
    1444 else
    1445 ub = alpha;
    1446 }
    1447
    1448 /* now we found the best convex combination which we use to derive the corresponding coef. If alpha = 0, we
    1449 * cannot move the ray in the recession cone, i.e. strengthening is not possible */
    1450 if( SCIPisZero(scip, alpha) )
    1451 {
    1452 *rho = -SCIPinfinity(scip);
    1453 return SCIP_OKAY;
    1454 }
    1455 else
    1456 currentrho = (alpha - 1) * interpoints[i] / alpha;
    1457 }
    1458
    1459 if( currentrho < *rho )
    1460 *rho = currentrho;
    1461 }
    1462
    1463 return SCIP_OKAY;
    1464}
    1465
    1466/** computes negative steplengths for the rays that are in the recession cone of the S-free set, i.e.,
    1467 * which have an infinite intersection point.
    1468 */
    1469static
    1471 SCIP* scip, /**< SCIP data structure */
    1472 SCIP_VAR** vars, /**< variables */
    1473 SCIP_Real* rays, /**< rays */
    1474 int nrays, /**< number of nonzero rays */
    1475 int* rayslppos, /**< lppos of nonzero rays */
    1476 SCIP_Real* interpoints, /**< intersection points */
    1477 SCIP_ROWPREP* rowprep, /**< rowprep for the generated cut */
    1478 SCIP_Bool usebounds, /**< TRUE if we want to separate non-negative bound */
    1479 SCIP_Real* ad, /**< coefs a and d for the hyperplane aTx + dTy <= 0 */
    1480 SCIP_Bool* success /**< if a cut candidate could be computed */
    1481 )
    1482{
    1483 SCIP_COL** cols;
    1484 SCIP_ROW** rows;
    1485 int i;
    1486
    1487 *success = TRUE;
    1488
    1489 cols = SCIPgetLPCols(scip);
    1490 rows = SCIPgetLPRows(scip);
    1491
    1492 /* go through all intersection points that are equal to infinity -> these correspond to the rays which are in the
    1493 * recession cone of C, i.e. the rays for which we (possibly) can compute a negative steplength */
    1494 for( i = 0; i < nrays ; ++i )
    1495 {
    1496 SCIP_Real rho;
    1497 SCIP_Real cutcoef;
    1498 int lppos;
    1499
    1500 if( !SCIPisInfinity(scip, interpoints[i]) )
    1501 continue;
    1502
    1503 /* compute the smallest rho */
    1504 SCIP_CALL( findRho(scip, rays, nrays, i, interpoints, vars, &rho, usebounds, ad, success) );
    1505
    1506 if( ! *success )
    1507 continue;
    1508
    1509 /* compute cut coef */
    1510 cutcoef = SCIPisInfinity(scip, -rho) ? 0.0 : 1.0 / rho;
    1511
    1512 /* add var to cut: if variable is nonbasic at upper we have to flip sign of cutcoef */
    1513 lppos = rayslppos[i];
    1514 if( lppos < 0 )
    1515 {
    1516 lppos = -lppos - 1;
    1517
    1518 assert(SCIProwGetBasisStatus(rows[lppos]) == SCIP_BASESTAT_LOWER || SCIProwGetBasisStatus(rows[lppos]) ==
    1520
    1521 SCIP_CALL( addRowToCut(scip, rowprep, SCIProwGetBasisStatus(rows[lppos]) == SCIP_BASESTAT_UPPER ? cutcoef :
    1522 -cutcoef, rows[lppos], success) ); /* rows have flipped base status! */
    1523
    1524 if( ! *success )
    1525 return SCIP_OKAY;
    1526 }
    1527 else
    1528 {
    1529 assert(SCIPcolGetBasisStatus(cols[lppos]) == SCIP_BASESTAT_UPPER || SCIPcolGetBasisStatus(cols[lppos]) ==
    1531 SCIP_CALL( addColToCut(scip, rowprep, SCIPcolGetBasisStatus(cols[lppos]) == SCIP_BASESTAT_UPPER ? -cutcoef :
    1532 cutcoef, cols[lppos]) );
    1533 }
    1534 }
    1535
    1536 return SCIP_OKAY;
    1537}
    1538
    1539/** separates cuts for stored principal minors */
    1540static
    1542 SCIP* scip, /**< SCIP data structure */
    1543 SCIP_SEPA* sepa, /**< separator */
    1544 SCIP_SEPADATA* sepadata, /**< separator data */
    1545 SCIP_VAR* xik, /**< variable X_ik = x_i * x_k */
    1546 SCIP_VAR* xil, /**< variable X_il = x_i * x_l */
    1547 SCIP_VAR* xjk, /**< variable X_jk = x_j * x_k */
    1548 SCIP_VAR* xjl, /**< variable X_jl = x_j * x_l */
    1549 SCIP_Bool* isxikdiag, /**< is X_ik diagonal? (i.e. i = k) */
    1550 SCIP_Bool* isxildiag, /**< is X_il diagonal? (i.e. i = l) */
    1551 SCIP_Bool* isxjkdiag, /**< is X_jk diagonal? (i.e. j = k) */
    1552 SCIP_Bool* isxjldiag, /**< is X_jl diagonal? (i.e. j = l) */
    1553 int* basicvarpos2tableaurow,/**< map from basic var to its tableau row */
    1554 SCIP_HASHMAP* tableau, /**< map from var to its tableau row */
    1555 SCIP_RESULT* result /**< pointer to store the result of the separation call */
    1556 )
    1557{
    1558 SCIP_ROWPREP* rowprep;
    1559 SCIP_VAR* vars[4] = {xik, xjl, xil, xjk};
    1560 SCIP_Real* tableaurows[4];
    1561 SCIP_Real* interpoints;
    1562 SCIP_Real* rays;
    1563 int nrays;
    1564 int* rayslppos;
    1565 int ncols;
    1566 int nrows;
    1567 SCIP_Bool success;
    1568 SCIP_Real ad[4] = {0.0, 0.0, 0.0, 0.0};
    1569 SCIP_Real solxik;
    1570 SCIP_Real solxil;
    1571 SCIP_Real solxjk;
    1572 SCIP_Real solxjl;
    1573 SCIP_Real viol;
    1574
    1575 ncols = SCIPgetNLPCols(scip);
    1576 nrows = SCIPgetNLPRows(scip);
    1577
    1578 /* allocate memory for intersection points */
    1579 SCIP_CALL( SCIPallocBufferArray(scip, &interpoints, ncols + nrows) );
    1580
    1581 /* allocate memory for rays */
    1582 SCIP_CALL( SCIPallocBufferArray(scip, &rays, 4 * (ncols + nrows)) );
    1583 SCIP_CALL( SCIPallocBufferArray(scip, &rayslppos, ncols + nrows) );
    1584
    1585 /* cut (in the nonbasic space) is of the form alpha^T x >= 1 */
    1587 SCIProwprepAddSide(rowprep, 1.0);
    1588
    1589 /* check if we have the tableau row of the variable and if not compute it */
    1590 SCIP_CALL( getTableauRows(scip, vars, basicvarpos2tableaurow, tableau, tableaurows, &success) );
    1591
    1592 if( ! success )
    1593 goto CLEANUP;
    1594
    1595 /* if we want to enforce bounds, set the right a and d to enforce aTx + dTy <= 0 */
    1596 if( sepadata->usebounds )
    1597 {
    1598 solxik = SCIPvarGetLPSol(xik);
    1599 solxil = SCIPvarGetLPSol(xil);
    1600 solxjk = SCIPvarGetLPSol(xjk);
    1601 solxjl = SCIPvarGetLPSol(xjl);
    1602
    1603 if( isxikdiag && SCIPisFeasNegative(scip, solxik) )
    1604 {
    1605 ad[0] = -1.0;
    1606 ad[2] = 1.0;
    1607 }
    1608 else if( isxjldiag && SCIPisFeasNegative(scip, solxjl) )
    1609 {
    1610 ad[0] = -1.0;
    1611 ad[2] = -1.0;
    1612 }
    1613 else if( isxildiag && SCIPisFeasNegative(scip, solxil) )
    1614 {
    1615 ad[1] = 1.0;
    1616 ad[3] = -1.0;
    1617 }
    1618 else if( isxjkdiag && SCIPisFeasNegative(scip, solxjk) )
    1619 {
    1620 ad[1] = -1.0;
    1621 ad[3] = -1.0;
    1622 }
    1623 }
    1624
    1625 nrays = 0;
    1626 /* loop over each non-basic var; get the ray; compute cut coefficient */
    1627 SCIP_CALL( addCols(scip, vars, tableaurows, rowprep, rays, &nrays, rayslppos, interpoints, sepadata->usebounds, ad, &success) );
    1628
    1629 if( ! success )
    1630 goto CLEANUP;
    1631
    1632 /* loop over non-basic slack variables */
    1633 SCIP_CALL( addRows(scip, vars, tableaurows, rowprep, rays, &nrays, rayslppos, interpoints, sepadata->usebounds, ad, &success) );
    1634
    1635 if( ! success )
    1636 goto CLEANUP;
    1637
    1638 /* do strengthening */
    1639 if( sepadata->usestrengthening )
    1640 {
    1641 SCIP_CALL( computeNegCutcoefs(scip, vars, rays, nrays, rayslppos, interpoints, rowprep, sepadata->usebounds, ad, &success) );
    1642
    1643 if( ! success )
    1644 goto CLEANUP;
    1645 }
    1646
    1647 /* merge coefficients that belong to same variable */
    1648 SCIPmergeRowprepTerms(scip, rowprep);
    1649
    1650 SCIP_CALL( SCIPcleanupRowprep2(scip, rowprep, NULL, SCIPgetHugeValue(scip), &success) );
    1651
    1652 if( !success )
    1653 goto CLEANUP;
    1654
    1655 viol = SCIPgetRowprepViolation(scip, rowprep, NULL, &success);
    1656
    1657 /* if cut is violated, create row out of rowprep and add it */
    1658 if( success && viol >= sepadata->mincutviol )
    1659 {
    1660 SCIP_ROW* row;
    1661 SCIP_Bool infeasible;
    1662
    1663 /* create row */
    1664 SCIP_CALL( SCIPgetRowprepRowSepa(scip, &row, rowprep, sepa) );
    1665
    1666 assert(SCIPgetCutEfficacy(scip, NULL, row) > 0.0);
    1667
    1668 /* add row */
    1669 SCIP_CALL( SCIPaddRow(scip, row, FALSE, &infeasible) );
    1670
    1671 if( infeasible )
    1672 *result = SCIP_CUTOFF;
    1673 else
    1674 *result = SCIP_SEPARATED;
    1675
    1676 SCIP_CALL( SCIPreleaseRow(scip, &row) );
    1677 }
    1678
    1679CLEANUP:
    1680 SCIPfreeRowprep(scip, &rowprep);
    1681 SCIPfreeBuffer(scip, &rayslppos);
    1682 SCIPfreeBuffer(scip, &rays);
    1683 SCIPfreeBuffer(scip, &interpoints);
    1684
    1685 return SCIP_OKAY;
    1686}
    1687
    1688
    1689/** separates cuts for stored principal minors */
    1690static
    1692 SCIP* scip, /**< SCIP data structure */
    1693 SCIP_SEPA* sepa, /**< separator */
    1694 SCIP_RESULT* result /**< pointer to store the result of the separation call */
    1695 )
    1696{
    1697 SCIP_SEPADATA* sepadata;
    1698 SCIP_HASHMAP* tableau = NULL;
    1699 int* basicvarpos2tableaurow = NULL; /* map between basic var and its tableau row */
    1700 int i;
    1701
    1702 assert(sepa != NULL);
    1703 assert(result != NULL);
    1704
    1705 *result = SCIP_DIDNOTRUN;
    1706
    1707 sepadata = SCIPsepaGetData(sepa);
    1708 assert(sepadata != NULL);
    1709
    1710 /* check whether there are some minors available */
    1711 if( sepadata->nminors == 0 )
    1712 return SCIP_OKAY;
    1713
    1714 *result = SCIP_DIDNOTFIND;
    1715
    1716 /* loop over the minors and if they are violated build cut */
    1717 for( i = 0; i < sepadata->nminors && (*result != SCIP_CUTOFF); ++i )
    1718 {
    1719 SCIP_VAR* auxvarxik;
    1720 SCIP_VAR* auxvarxil;
    1721 SCIP_VAR* auxvarxjk;
    1722 SCIP_VAR* auxvarxjl;
    1723 SCIP_Bool isauxvarxikdiag;
    1724 SCIP_Bool isauxvarxildiag;
    1725 SCIP_Bool isauxvarxjkdiag;
    1726 SCIP_Bool isauxvarxjldiag;
    1727 SCIP_Real solxik;
    1728 SCIP_Real solxil;
    1729 SCIP_Real solxjk;
    1730 SCIP_Real solxjl;
    1731 SCIP_Real det;
    1732
    1733 /* get variables of the i-th minor */
    1734 SCIP_CALL( getMinorVars(sepadata, i, &auxvarxik, &auxvarxil, &auxvarxjk, &auxvarxjl, &isauxvarxikdiag,
    1735 &isauxvarxildiag, &isauxvarxjkdiag, &isauxvarxjldiag) );
    1736
    1737 /* get current solution values */
    1738 solxik = SCIPvarGetLPSol(auxvarxik);
    1739 solxil = SCIPvarGetLPSol(auxvarxil);
    1740 solxjk = SCIPvarGetLPSol(auxvarxjk);
    1741 solxjl = SCIPvarGetLPSol(auxvarxjl);
    1742
    1743 det = solxik * solxjl - solxil * solxjk;
    1744
    1745 if( SCIPisFeasZero(scip, det) )
    1746 continue;
    1747
    1748 if( basicvarpos2tableaurow == NULL )
    1749 {
    1750 /* allocate memory */
    1751 SCIP_CALL( SCIPallocBufferArray(scip, &basicvarpos2tableaurow, SCIPgetNLPCols(scip)) );
    1753
    1754 /* construct basicvar to tableau row map */
    1755 SCIP_CALL( constructBasicVars2TableauRowMap(scip, basicvarpos2tableaurow) );
    1756 }
    1757 assert(tableau != NULL);
    1758
    1759 if( SCIPisFeasPositive(scip, det) )
    1760 {
    1761 SCIP_CALL( separateDeterminant(scip, sepa, sepadata, auxvarxik, auxvarxil, auxvarxjk, auxvarxjl, &isauxvarxikdiag,
    1762 &isauxvarxildiag, &isauxvarxjkdiag, &isauxvarxjldiag, basicvarpos2tableaurow, tableau, result) );
    1763 }
    1764 else
    1765 {
    1766 assert(SCIPisFeasNegative(scip, det));
    1767 SCIP_CALL( separateDeterminant(scip, sepa, sepadata, auxvarxil, auxvarxik, auxvarxjl, auxvarxjk, &isauxvarxildiag,
    1768 &isauxvarxikdiag, &isauxvarxjldiag, &isauxvarxjkdiag, basicvarpos2tableaurow, tableau, result) );
    1769 }
    1770 }
    1771
    1772 /* all minors were feasible, so no memory to free */
    1773 if( basicvarpos2tableaurow == NULL )
    1774 return SCIP_OKAY;
    1775
    1776 /* free memory */
    1777 for( i = 0; i < SCIPhashmapGetNEntries(tableau); ++i )
    1778 {
    1779 SCIP_HASHMAPENTRY* entry;
    1780
    1781 entry = SCIPhashmapGetEntry(tableau, i);
    1782
    1783 if( entry != NULL )
    1784 {
    1785 SCIP_Real* tableaurow;
    1786
    1787 tableaurow = (SCIP_Real *) SCIPhashmapEntryGetImage(entry);
    1788
    1789 SCIPfreeBufferArrayNull(scip, &tableaurow);
    1790 }
    1791 }
    1792 SCIPhashmapFree(&tableau);
    1793 SCIPfreeBufferArray(scip, &basicvarpos2tableaurow);
    1794
    1795 return SCIP_OKAY;
    1796}
    1797
    1798/*
    1799 * Callback methods of separator
    1800 */
    1801
    1802/** copy method for separator plugins (called when SCIP copies plugins) */
    1803static
    1805{ /*lint --e{715}*/
    1806 assert(scip != NULL);
    1807 assert(sepa != NULL);
    1808 assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
    1809
    1810 /* call inclusion method of constraint handler */
    1812
    1813 return SCIP_OKAY;
    1814}
    1815
    1816
    1817/** destructor of separator to free user data (called when SCIP is exiting) */
    1818static
    1820{ /*lint --e{715}*/
    1821 SCIP_SEPADATA* sepadata;
    1822
    1823 sepadata = SCIPsepaGetData(sepa);
    1824 assert(sepadata != NULL);
    1825 assert(sepadata->minors == NULL);
    1826 assert(sepadata->nminors == 0);
    1827 assert(sepadata->minorssize == 0);
    1828
    1829 /* free separator data */
    1830 SCIPfreeBlockMemory(scip, &sepadata);
    1831 SCIPsepaSetData(sepa, NULL);
    1832
    1833 return SCIP_OKAY;
    1834}
    1835
    1836
    1837/** initialization method of separator (called after problem was transformed) */
    1838static
    1840{ /*lint --e{715}*/
    1841 SCIP_SEPADATA* sepadata;
    1842
    1843 /* get separator data */
    1844 sepadata = SCIPsepaGetData(sepa);
    1845 assert(sepadata != NULL);
    1846 assert(sepadata->randnumgen == NULL);
    1847
    1848 /* create random number generator */
    1849 SCIP_CALL( SCIPcreateRandom(scip, &sepadata->randnumgen, DEFAULT_RANDSEED, TRUE) );
    1850
    1851 return SCIP_OKAY;
    1852}
    1853
    1854
    1855/** deinitialization method of separator (called before transformed problem is freed) */
    1856static
    1858{ /*lint --e{715}*/
    1859 SCIP_SEPADATA* sepadata;
    1860
    1861 /* get separator data */
    1862 sepadata = SCIPsepaGetData(sepa);
    1863 assert(sepadata != NULL);
    1864 assert(sepadata->randnumgen != NULL);
    1865
    1866 /* free random number generator */
    1867 SCIPfreeRandom(scip, &sepadata->randnumgen);
    1868
    1869 return SCIP_OKAY;
    1870}
    1871
    1872
    1873/** solving process initialization method of separator (called when branch and bound process is about to begin) */
    1874static
    1875SCIP_DECL_SEPAINITSOL(sepaInitsolMinor)
    1876{ /*lint --e{715}*/
    1877 return SCIP_OKAY;
    1878}
    1879
    1880
    1881/** solving process deinitialization method of separator (called before branch and bound process data is freed) */
    1882static
    1883SCIP_DECL_SEPAEXITSOL(sepaExitsolMinor)
    1884{ /*lint --e{715}*/
    1885 SCIP_SEPADATA* sepadata;
    1886
    1887 sepadata = SCIPsepaGetData(sepa);
    1888 assert(sepadata != NULL);
    1889
    1890 /* clear separation data */
    1891 SCIP_CALL( sepadataClear(scip, sepadata) );
    1892
    1893 return SCIP_OKAY;
    1894}
    1895
    1896
    1897/** LP solution separation method of separator */
    1898static
    1899SCIP_DECL_SEPAEXECLP(sepaExeclpMinor)
    1900{ /*lint --e{715}*/
    1901 SCIP_SEPADATA* sepadata;
    1902 int ncalls;
    1903 int currentdepth;
    1904
    1905 /* need routine to compute eigenvalues/eigenvectors */
    1907 return SCIP_OKAY;
    1908
    1909 sepadata = SCIPsepaGetData(sepa);
    1910 assert(sepadata != NULL);
    1911 currentdepth = SCIPgetDepth(scip);
    1912 ncalls = SCIPsepaGetNCallsAtNode(sepa);
    1913
    1914 /* only call the separator a given number of times at each node */
    1915 if( (currentdepth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
    1916 || (currentdepth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
    1917 {
    1918 SCIPdebugMsg(scip, "reached round limit for node\n");
    1919 return SCIP_OKAY;
    1920 }
    1921
    1922 /* try to detect minors */
    1923 SCIP_CALL( detectMinors(scip, sepadata) );
    1924
    1925 /* call separation method */
    1926 SCIP_CALL( separatePoint(scip, sepa, result) );
    1927
    1928 return SCIP_OKAY;
    1929}
    1930
    1931
    1932/*
    1933 * separator specific interface methods
    1934 */
    1935
    1936/** creates the minor separator and includes it in SCIP */
    1938 SCIP* scip /**< SCIP data structure */
    1939 )
    1940{
    1941 SCIP_SEPADATA* sepadata = NULL;
    1942 SCIP_SEPA* sepa = NULL;
    1943
    1944 /* create minor separator data */
    1945 SCIP_CALL( SCIPallocBlockMemory(scip, &sepadata) );
    1946 BMSclearMemory(sepadata);
    1947
    1948 /* include separator */
    1951 sepaExeclpMinor, NULL,
    1952 sepadata) );
    1953
    1954 assert(sepa != NULL);
    1955
    1956 /* set non fundamental callbacks via setter functions */
    1957 SCIP_CALL( SCIPsetSepaCopy(scip, sepa, sepaCopyMinor) );
    1958 SCIP_CALL( SCIPsetSepaFree(scip, sepa, sepaFreeMinor) );
    1959 SCIP_CALL( SCIPsetSepaInit(scip, sepa, sepaInitMinor) );
    1960 SCIP_CALL( SCIPsetSepaExit(scip, sepa, sepaExitMinor) );
    1961 SCIP_CALL( SCIPsetSepaInitsol(scip, sepa, sepaInitsolMinor) );
    1962 SCIP_CALL( SCIPsetSepaExitsol(scip, sepa, sepaExitsolMinor) );
    1963
    1964 /* add minor separator parameters */
    1966 "separating/" SEPA_NAME "/usestrengthening",
    1967 "whether to use strengthened intersection cuts to separate minors",
    1968 &sepadata->usestrengthening, FALSE, DEFAULT_USESTRENGTHENING, NULL, NULL) );
    1969
    1971 "separating/" SEPA_NAME "/usebounds",
    1972 "whether to also enforce nonegativity bounds of principle minors",
    1973 &sepadata->usebounds, FALSE, DEFAULT_USEBOUNDS, NULL, NULL) );
    1974
    1976 "separating/" SEPA_NAME "/mincutviol",
    1977 "minimum required violation of a cut",
    1978 &sepadata->mincutviol, FALSE, DEFAULT_MINCUTVIOL, 0.0, SCIP_REAL_MAX, NULL, NULL) );
    1979
    1981 "separating/" SEPA_NAME "/maxrounds",
    1982 "maximal number of separation rounds per node (-1: unlimited)",
    1983 &sepadata->maxrounds, FALSE, DEFAULT_MAXROUNDS, -1, INT_MAX, NULL, NULL) );
    1984
    1986 "separating/" SEPA_NAME "/maxroundsroot",
    1987 "maximal number of separation rounds in the root node (-1: unlimited)",
    1988 &sepadata->maxroundsroot, FALSE, DEFAULT_MAXROUNDSROOT, -1, INT_MAX, NULL, NULL) );
    1989
    1990 return SCIP_OKAY;
    1991}
    SCIP_VAR * a
    Definition: circlepacking.c:66
    SCIP_VAR ** b
    Definition: circlepacking.c:65
    constraint handler for nonlinear constraints specified by algebraic expressions
    #define SCIPquadprecSqrtQ(r, a)
    Definition: dbldblarith.h:71
    #define SCIPquadprecProdDD(r, a, b)
    Definition: dbldblarith.h:58
    #define SCIPquadprecProdQD(r, a, b)
    Definition: dbldblarith.h:63
    #define QUAD_SCALE(x, a)
    Definition: dbldblarith.h:50
    #define SCIPquadprecSumQD(r, a, b)
    Definition: dbldblarith.h:62
    #define QUAD_ASSIGN(a, constant)
    Definition: dbldblarith.h:51
    #define QUAD(x)
    Definition: dbldblarith.h:47
    #define SCIPquadprecSquareD(r, a)
    Definition: dbldblarith.h:59
    #define SCIPquadprecSumQQ(r, a, b)
    Definition: dbldblarith.h:67
    #define QUAD_TO_DBL(x)
    Definition: dbldblarith.h:49
    #define NULL
    Definition: def.h:248
    #define SCIP_REAL_MAX
    Definition: def.h:158
    #define SCIP_INTERVAL_INFINITY
    Definition: def.h:180
    #define SCIP_Bool
    Definition: def.h:91
    #define SCIP_Real
    Definition: def.h:156
    #define ABS(x)
    Definition: def.h:216
    #define SQR(x)
    Definition: def.h:199
    #define TRUE
    Definition: def.h:93
    #define FALSE
    Definition: def.h:94
    #define MAX(x, y)
    Definition: def.h:220
    #define SCIP_CALL(x)
    Definition: def.h:355
    private functions to work with algebraic expressions
    power and signed power expression handlers
    product expression handler
    variable expression handler
    void SCIPcomputeArraysIntersectionInt(int *array1, int narray1, int *array2, int narray2, int *intersectarray, int *nintersectarray)
    Definition: misc.c:10530
    SCIP_VAR * SCIPgetExprAuxVarNonlinear(SCIP_EXPR *expr)
    SCIP_EXPR * SCIPgetExprNonlinear(SCIP_CONS *cons)
    const char * SCIPgetProbName(SCIP *scip)
    Definition: scip_prob.c:1242
    int SCIPgetNVars(SCIP *scip)
    Definition: scip_prob.c:2246
    SCIP_VAR ** SCIPgetVars(SCIP *scip)
    Definition: scip_prob.c:2201
    void SCIPhashmapFree(SCIP_HASHMAP **hashmap)
    Definition: misc.c:3095
    void * SCIPhashmapEntryGetImage(SCIP_HASHMAPENTRY *entry)
    Definition: misc.c:3613
    void * SCIPhashmapGetImage(SCIP_HASHMAP *hashmap, void *origin)
    Definition: misc.c:3284
    SCIP_RETCODE SCIPhashmapInsert(SCIP_HASHMAP *hashmap, void *origin, void *image)
    Definition: misc.c:3143
    int SCIPhashmapGetNEntries(SCIP_HASHMAP *hashmap)
    Definition: misc.c:3584
    SCIP_HASHMAPENTRY * SCIPhashmapGetEntry(SCIP_HASHMAP *hashmap, int entryidx)
    Definition: misc.c:3592
    SCIP_RETCODE SCIPhashmapCreate(SCIP_HASHMAP **hashmap, BMS_BLKMEM *blkmem, int mapsize)
    Definition: misc.c:3061
    SCIP_Bool SCIPhashmapExists(SCIP_HASHMAP *hashmap, void *origin)
    Definition: misc.c:3466
    void SCIPinfoMessage(SCIP *scip, FILE *file, const char *formatstr,...)
    Definition: scip_message.c:208
    #define SCIPdebugMsg
    Definition: scip_message.h:78
    SCIP_Bool SCIPisIpoptAvailableIpopt(void)
    SCIP_RETCODE SCIPaddIntParam(SCIP *scip, const char *name, const char *desc, int *valueptr, SCIP_Bool isadvanced, int defaultvalue, int minvalue, int maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
    Definition: scip_param.c:83
    SCIP_RETCODE SCIPaddRealParam(SCIP *scip, const char *name, const char *desc, SCIP_Real *valueptr, SCIP_Bool isadvanced, SCIP_Real defaultvalue, SCIP_Real minvalue, SCIP_Real maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
    Definition: scip_param.c:139
    SCIP_RETCODE SCIPaddBoolParam(SCIP *scip, const char *name, const char *desc, SCIP_Bool *valueptr, SCIP_Bool isadvanced, SCIP_Bool defaultvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
    Definition: scip_param.c:57
    int SCIPcolGetLPPos(SCIP_COL *col)
    Definition: lp.c:17487
    SCIP_VAR * SCIPcolGetVar(SCIP_COL *col)
    Definition: lp.c:17425
    SCIP_Real SCIPcolGetPrimsol(SCIP_COL *col)
    Definition: lp.c:17379
    SCIP_BASESTAT SCIPcolGetBasisStatus(SCIP_COL *col)
    Definition: lp.c:17414
    int SCIPconshdlrGetNConss(SCIP_CONSHDLR *conshdlr)
    Definition: cons.c:4778
    SCIP_CONSHDLR * SCIPfindConshdlr(SCIP *scip, const char *name)
    Definition: scip_cons.c:940
    SCIP_CONS ** SCIPconshdlrGetConss(SCIP_CONSHDLR *conshdlr)
    Definition: cons.c:4735
    const char * SCIPconsGetName(SCIP_CONS *cons)
    Definition: cons.c:8389
    SCIP_Real SCIPgetCutEfficacy(SCIP *scip, SCIP_SOL *sol, SCIP_ROW *cut)
    Definition: scip_cut.c:94
    SCIP_RETCODE SCIPaddRow(SCIP *scip, SCIP_ROW *row, SCIP_Bool forcecut, SCIP_Bool *infeasible)
    Definition: scip_cut.c:225
    int SCIPexprGetNChildren(SCIP_EXPR *expr)
    Definition: expr.c:3872
    SCIP_Real SCIPgetExponentExprPow(SCIP_EXPR *expr)
    Definition: expr_pow.c:3448
    SCIP_Bool SCIPisExprProduct(SCIP *scip, SCIP_EXPR *expr)
    Definition: scip_expr.c:1490
    SCIP_Bool SCIPexpriterIsEnd(SCIP_EXPRITER *iterator)
    Definition: expriter.c:969
    SCIP_EXPR * SCIPexpriterRestartDFS(SCIP_EXPRITER *iterator, SCIP_EXPR *expr)
    Definition: expriter.c:630
    SCIP_RETCODE SCIPcreateExpriter(SCIP *scip, SCIP_EXPRITER **iterator)
    Definition: scip_expr.c:2362
    SCIP_Bool SCIPisExprPower(SCIP *scip, SCIP_EXPR *expr)
    Definition: scip_expr.c:1501
    SCIP_EXPR * SCIPexpriterGetNext(SCIP_EXPRITER *iterator)
    Definition: expriter.c:858
    SCIP_EXPR ** SCIPexprGetChildren(SCIP_EXPR *expr)
    Definition: expr.c:3882
    void SCIPfreeExpriter(SCIP_EXPRITER **iterator)
    Definition: scip_expr.c:2376
    SCIP_RETCODE SCIPexpriterInit(SCIP_EXPRITER *iterator, SCIP_EXPR *expr, SCIP_EXPRITER_TYPE type, SCIP_Bool allowrevisit)
    Definition: expriter.c:501
    SCIP_Real SCIPintervalGetInf(SCIP_INTERVAL interval)
    SCIP_Bool SCIPintervalIsEmpty(SCIP_Real infinity, SCIP_INTERVAL operand)
    void SCIPintervalSetBounds(SCIP_INTERVAL *resultant, SCIP_Real inf, SCIP_Real sup)
    void SCIPintervalSolveUnivariateQuadExpressionPositiveAllScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_Real sqrcoeff, SCIP_Real lincoeff, SCIP_Real rhs, SCIP_INTERVAL xbnds)
    SCIP_RETCODE SCIPgetLPBasisInd(SCIP *scip, int *basisind)
    Definition: scip_lp.c:692
    SCIP_ROW ** SCIPgetLPRows(SCIP *scip)
    Definition: scip_lp.c:611
    int SCIPgetNLPRows(SCIP *scip)
    Definition: scip_lp.c:632
    SCIP_RETCODE SCIPgetLPBInvARow(SCIP *scip, int r, SCIP_Real *binvrow, SCIP_Real *coefs, int *inds, int *ninds)
    Definition: scip_lp.c:791
    SCIP_COL ** SCIPgetLPCols(SCIP *scip)
    Definition: scip_lp.c:512
    int SCIPgetNLPCols(SCIP *scip)
    Definition: scip_lp.c:533
    SCIP_RETCODE SCIPgetLPBInvRow(SCIP *scip, int r, SCIP_Real *coefs, int *inds, int *ninds)
    Definition: scip_lp.c:720
    #define SCIPfreeBuffer(scip, ptr)
    Definition: scip_mem.h:134
    BMS_BLKMEM * SCIPblkmem(SCIP *scip)
    Definition: scip_mem.c:57
    int SCIPcalcMemGrowSize(SCIP *scip, int num)
    Definition: scip_mem.c:139
    #define SCIPallocBufferArray(scip, ptr, num)
    Definition: scip_mem.h:124
    #define SCIPreallocBufferArray(scip, ptr, num)
    Definition: scip_mem.h:128
    #define SCIPfreeBufferArray(scip, ptr)
    Definition: scip_mem.h:136
    #define SCIPallocBuffer(scip, ptr)
    Definition: scip_mem.h:122
    #define SCIPreallocBlockMemoryArray(scip, ptr, oldnum, newnum)
    Definition: scip_mem.h:99
    #define SCIPfreeBlockMemory(scip, ptr)
    Definition: scip_mem.h:108
    #define SCIPfreeBlockMemoryArrayNull(scip, ptr, num)
    Definition: scip_mem.h:111
    #define SCIPfreeBufferArrayNull(scip, ptr)
    Definition: scip_mem.h:137
    #define SCIPallocBlockMemory(scip, ptr)
    Definition: scip_mem.h:89
    SCIP_Real SCIProwGetLhs(SCIP_ROW *row)
    Definition: lp.c:17686
    SCIP_COL ** SCIProwGetCols(SCIP_ROW *row)
    Definition: lp.c:17632
    SCIP_Real SCIProwGetRhs(SCIP_ROW *row)
    Definition: lp.c:17696
    int SCIProwGetNLPNonz(SCIP_ROW *row)
    Definition: lp.c:17621
    int SCIProwGetLPPos(SCIP_ROW *row)
    Definition: lp.c:17895
    SCIP_Real SCIPgetRowActivity(SCIP *scip, SCIP_ROW *row)
    Definition: scip_lp.c:2068
    SCIP_RETCODE SCIPreleaseRow(SCIP *scip, SCIP_ROW **row)
    Definition: scip_lp.c:1508
    SCIP_Real SCIProwGetConstant(SCIP_ROW *row)
    Definition: lp.c:17652
    SCIP_Real * SCIProwGetVals(SCIP_ROW *row)
    Definition: lp.c:17642
    SCIP_BASESTAT SCIProwGetBasisStatus(SCIP_ROW *row)
    Definition: lp.c:17734
    SCIP_RETCODE SCIPsetSepaExit(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAEXIT((*sepaexit)))
    Definition: scip_sepa.c:205
    SCIP_RETCODE SCIPsetSepaInitsol(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAINITSOL((*sepainitsol)))
    Definition: scip_sepa.c:221
    SCIP_RETCODE SCIPincludeSepaBasic(SCIP *scip, SCIP_SEPA **sepa, const char *name, const char *desc, int priority, int freq, SCIP_Real maxbounddist, SCIP_Bool usessubscip, SCIP_Bool delay, SCIP_DECL_SEPAEXECLP((*sepaexeclp)), SCIP_DECL_SEPAEXECSOL((*sepaexecsol)), SCIP_SEPADATA *sepadata)
    Definition: scip_sepa.c:115
    const char * SCIPsepaGetName(SCIP_SEPA *sepa)
    Definition: sepa.c:746
    int SCIPsepaGetNCallsAtNode(SCIP_SEPA *sepa)
    Definition: sepa.c:893
    SCIP_RETCODE SCIPsetSepaFree(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAFREE((*sepafree)))
    Definition: scip_sepa.c:173
    SCIP_RETCODE SCIPsetSepaExitsol(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAEXITSOL((*sepaexitsol)))
    Definition: scip_sepa.c:237
    SCIP_SEPADATA * SCIPsepaGetData(SCIP_SEPA *sepa)
    Definition: sepa.c:636
    void SCIPsepaSetData(SCIP_SEPA *sepa, SCIP_SEPADATA *sepadata)
    Definition: sepa.c:646
    SCIP_RETCODE SCIPsetSepaCopy(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPACOPY((*sepacopy)))
    Definition: scip_sepa.c:157
    SCIP_RETCODE SCIPsetSepaInit(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAINIT((*sepainit)))
    Definition: scip_sepa.c:189
    SCIP_Real SCIPgetTotalTime(SCIP *scip)
    Definition: scip_timing.c:351
    SCIP_Real SCIPinfinity(SCIP *scip)
    SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
    SCIP_Bool SCIPisFeasZero(SCIP *scip, SCIP_Real val)
    SCIP_Bool SCIPisHugeValue(SCIP *scip, SCIP_Real val)
    SCIP_Bool SCIPisInfinity(SCIP *scip, SCIP_Real val)
    SCIP_Bool SCIPisFeasNegative(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_Bool SCIPisFeasPositive(SCIP *scip, SCIP_Real val)
    int SCIPgetDepth(SCIP *scip)
    Definition: scip_tree.c:672
    SCIP_COL * SCIPvarGetCol(SCIP_VAR *var)
    Definition: var.c:23683
    SCIP_Real SCIPvarGetUbLocal(SCIP_VAR *var)
    Definition: var.c:24268
    int SCIPvarGetProbindex(SCIP_VAR *var)
    Definition: var.c:23662
    const char * SCIPvarGetName(SCIP_VAR *var)
    Definition: var.c:23267
    SCIP_RETCODE SCIPreleaseVar(SCIP *scip, SCIP_VAR **var)
    Definition: scip_var.c:1887
    SCIP_Real SCIPvarGetLPSol(SCIP_VAR *var)
    Definition: var.c:24664
    SCIP_Real SCIPvarGetLbLocal(SCIP_VAR *var)
    Definition: var.c:24234
    SCIP_RETCODE SCIPcaptureVar(SCIP *scip, SCIP_VAR *var)
    Definition: scip_var.c:1853
    void SCIPfreeRandom(SCIP *scip, SCIP_RANDNUMGEN **randnumgen)
    SCIP_RETCODE SCIPcreateRandom(SCIP *scip, SCIP_RANDNUMGEN **randnumgen, unsigned int initialseed, SCIP_Bool useglobalseed)
    SCIP_RETCODE SCIPcleanupRowprep2(SCIP *scip, SCIP_ROWPREP *rowprep, SCIP_SOL *sol, SCIP_Real maxcoefbound, SCIP_Bool *success)
    void SCIPmergeRowprepTerms(SCIP *scip, SCIP_ROWPREP *rowprep)
    SCIP_Real SCIPgetRowprepViolation(SCIP *scip, SCIP_ROWPREP *rowprep, SCIP_SOL *sol, SCIP_Bool *reliable)
    Definition: misc_rowprep.c:972
    void SCIProwprepAddConstant(SCIP_ROWPREP *rowprep, SCIP_Real constant)
    Definition: misc_rowprep.c:760
    SCIP_RETCODE SCIPgetRowprepRowSepa(SCIP *scip, SCIP_ROW **row, SCIP_ROWPREP *rowprep, SCIP_SEPA *sepa)
    SCIP_RETCODE SCIPaddRowprepTerm(SCIP *scip, SCIP_ROWPREP *rowprep, SCIP_VAR *var, SCIP_Real coef)
    Definition: misc_rowprep.c:913
    SCIP_RETCODE SCIPcreateRowprep(SCIP *scip, SCIP_ROWPREP **rowprep, SCIP_SIDETYPE sidetype, SCIP_Bool local)
    Definition: misc_rowprep.c:563
    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
    SCIP_RETCODE SCIPincludeSepaInterminor(SCIP *scip)
    void SCIPsortInt(int *intarray, int len)
    #define BMSclearMemory(ptr)
    Definition: memory.h:129
    Rational & max(Rational &r1, Rational &r2)
    Rational & min(Rational &r1, Rational &r2)
    Ipopt NLP interface.
    #define SCIPstatisticMessage
    Definition: pub_message.h:123
    static SCIP_RETCODE insertIndex(SCIP *scip, SCIP_HASHMAP *rowmap, SCIP_VAR *row, SCIP_VAR *col, SCIP_VAR *auxvar, int *rowindices, int *nrows)
    #define SEPA_PRIORITY
    static SCIP_Real computeIntersectionPoint(SCIP *scip, SCIP_Bool usebounds, SCIP_Real *coefs, SCIP_Real *coefs4b, SCIP_Real *coefscondition)
    #define DEFAULT_USEBOUNDS
    static SCIP_DECL_SEPAINIT(sepaInitMinor)
    #define DEFAULT_USESTRENGTHENING
    #define SEPA_DELAY
    static SCIP_RETCODE addRows(SCIP *scip, SCIP_VAR **vars, SCIP_Real **tableaurows, SCIP_ROWPREP *rowprep, SCIP_Real *rays, int *nrays, int *rayslppos, SCIP_Real *interpoints, SCIP_Bool usebounds, SCIP_Real *ad, SCIP_Bool *success)
    static SCIP_RETCODE getMinorVars(SCIP_SEPADATA *sepadata, int idx, SCIP_VAR **auxvarxik, SCIP_VAR **auxvarxil, SCIP_VAR **auxvarxjk, SCIP_VAR **auxvarxjl, SCIP_Bool *isauxvarxikdiag, SCIP_Bool *isauxvarxildiag, SCIP_Bool *isauxvarxjkdiag, SCIP_Bool *isauxvarxjldiag)
    static SCIP_DECL_SEPAEXECLP(sepaExeclpMinor)
    static SCIP_RETCODE sepadataClear(SCIP *scip, SCIP_SEPADATA *sepadata)
    #define SEPA_DESC
    static SCIP_RETCODE findRho(SCIP *scip, SCIP_Real *rays, int nrays, int idx, SCIP_Real *interpoints, SCIP_VAR **vars, SCIP_Real *rho, SCIP_Bool usebounds, SCIP_Real *ad, SCIP_Bool *success)
    #define DEFAULT_MAXROUNDSROOT
    #define SEPA_USESSUBSCIP
    static SCIP_RETCODE getTableauRows(SCIP *scip, SCIP_VAR **vars, int *basicvarpos2tableaurow, SCIP_HASHMAP *tableau, SCIP_Real **tableaurows, SCIP_Bool *success)
    static SCIP_DECL_SEPAFREE(sepaFreeMinor)
    static SCIP_DECL_SEPACOPY(sepaCopyMinor)
    static SCIP_Real isCase4a(SCIP_Real tsol, SCIP_Real *coefs, SCIP_Real *coefscondition)
    static SCIP_RETCODE addRowToCut(SCIP *scip, SCIP_ROWPREP *rowprep, SCIP_Real cutcoef, SCIP_ROW *row, SCIP_Bool *success)
    static SCIP_RETCODE separateDeterminant(SCIP *scip, SCIP_SEPA *sepa, SCIP_SEPADATA *sepadata, SCIP_VAR *xik, SCIP_VAR *xil, SCIP_VAR *xjk, SCIP_VAR *xjl, SCIP_Bool *isxikdiag, SCIP_Bool *isxildiag, SCIP_Bool *isxjkdiag, SCIP_Bool *isxjldiag, int *basicvarpos2tableaurow, SCIP_HASHMAP *tableau, SCIP_RESULT *result)
    static SCIP_DECL_SEPAEXITSOL(sepaExitsolMinor)
    static SCIP_Real computeRoot(SCIP *scip, SCIP_Real *coefs)
    static SCIP_Real evalPhiAtRay(SCIP *scip, SCIP_Real t, SCIP_Real a, SCIP_Real b, SCIP_Real c, SCIP_Real d, SCIP_Real e)
    #define DEFAULT_MINCUTVIOL
    static SCIP_RETCODE detectMinors(SCIP *scip, SCIP_SEPADATA *sepadata)
    static SCIP_RETCODE sepadataAddMinor(SCIP *scip, SCIP_SEPADATA *sepadata, SCIP_VAR *auxvarxik, SCIP_VAR *auxvarxil, SCIP_VAR *auxvarxjk, SCIP_VAR *auxvarxjl, SCIP_Bool isauxvarxikdiag, SCIP_Bool isauxvarxildiag, SCIP_Bool isauxvarxjkdiag, SCIP_Bool isauxvarxjldiag)
    #define SEPA_MAXBOUNDDIST
    static SCIP_RETCODE addCols(SCIP *scip, SCIP_VAR **vars, SCIP_Real **tableaurows, SCIP_ROWPREP *rowprep, SCIP_Real *rays, int *nrays, int *rayslppos, SCIP_Real *interpoints, SCIP_Bool usebounds, SCIP_Real *ad, SCIP_Bool *success)
    static SCIP_DECL_SEPAEXIT(sepaExitMinor)
    #define SEPA_FREQ
    #define DEFAULT_RANDSEED
    #define SEPA_NAME
    static SCIP_DECL_SEPAINITSOL(sepaInitsolMinor)
    #define MAXNMINORS
    #define BINSEARCH_MAXITERS
    #define DEFAULT_MAXROUNDS
    static SCIP_RETCODE computeNegCutcoefs(SCIP *scip, SCIP_VAR **vars, SCIP_Real *rays, int nrays, int *rayslppos, SCIP_Real *interpoints, SCIP_ROWPREP *rowprep, SCIP_Bool usebounds, SCIP_Real *ad, SCIP_Bool *success)
    static void doBinarySearch(SCIP *scip, SCIP_Real a, SCIP_Real b, SCIP_Real c, SCIP_Real d, SCIP_Real e, SCIP_Real *sol)
    static SCIP_RETCODE addColToCut(SCIP *scip, SCIP_ROWPREP *rowprep, SCIP_Real cutcoef, SCIP_COL *col)
    static SCIP_RETCODE constructBasicVars2TableauRowMap(SCIP *scip, int *map)
    static SCIP_RETCODE computeRestrictionToRay(SCIP *scip, SCIP_Real *ray, SCIP_VAR **vars, SCIP_Real *coefs, SCIP_Real *coefs4b, SCIP_Real *coefscondition, SCIP_Bool usebounds, SCIP_Real *ad, SCIP_Bool *success)
    static SCIP_Bool raysAreDependent(SCIP *scip, SCIP_Real *ray1, SCIP_Real *ray2, SCIP_Real *coef)
    static SCIP_RETCODE separatePoint(SCIP *scip, SCIP_SEPA *sepa, SCIP_RESULT *result)
    int * vals
    SCIP_HASHMAP * auxvars
    @ SCIP_EXPRITER_DFS
    Definition: type_expr.h:718
    @ SCIP_SIDETYPE_LEFT
    Definition: type_lp.h:65
    @ SCIP_BASESTAT_BASIC
    Definition: type_lpi.h:92
    @ SCIP_BASESTAT_UPPER
    Definition: type_lpi.h:93
    @ SCIP_BASESTAT_LOWER
    Definition: type_lpi.h:91
    @ SCIP_BASESTAT_ZERO
    Definition: type_lpi.h:94
    @ SCIP_DIDNOTRUN
    Definition: type_result.h:42
    @ SCIP_CUTOFF
    Definition: type_result.h:48
    @ SCIP_DIDNOTFIND
    Definition: type_result.h:44
    @ SCIP_SEPARATED
    Definition: type_result.h:49
    enum SCIP_Result SCIP_RESULT
    Definition: type_result.h:61
    @ SCIP_OKAY
    Definition: type_retcode.h:42
    enum SCIP_Retcode SCIP_RETCODE
    Definition: type_retcode.h:63
    struct SCIP_SepaData SCIP_SEPADATA
    Definition: type_sepa.h:52