source: branches/devel/Bonmin/src/BonminAmplInterface/BonAmplTMINLP.cpp @ 60

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1// (C) Copyright International Business Machines Corporation and Carnegie Mellon University 2004
2// All Rights Reserved.
3// This code is published under the Common Public License.
4//
5// Authors :
6// Carl D. Laird, Carnegie Mellon University,
7// Andreas Waechter, International Business Machines Corporation
8// Pierre Bonami, Carnegie Mellon University,
9//
10// Date : 12/01/2004
11#include "IpBlas.hpp"
12
13#include "AmplTNLP.hpp"
14#include "BonAmplTMINLP.hpp"
15#include <iostream>
16
17#include "asl.h"
18#include "asl_pfgh.h"
19#include "getstub.h"
20#include "CoinHelperFunctions.hpp"
21
22namespace ampl_utils
23{
24  void sos_kludge(int nsos, int *sosbeg, double *sosref);
25}
26namespace Bonmin
27{
28
29  AmplTMINLP::AmplTMINLP()
30      :
31      TMINLP(),
32      ampl_tnlp_(NULL),
33      branch_(),
34      sos_()
35  {}
36
37
38  AmplTMINLP::AmplTMINLP(const SmartPtr<const Journalist>& jnlst,
39      const SmartPtr<OptionsList> options,
40      char**& argv,
41      AmplSuffixHandler* suffix_handler /*=NULL*/,
42      const std::string& appName,
43      std::string* nl_file_content /* = NULL */)
44      :
45      TMINLP(),
46      ampl_tnlp_(NULL),
47      branch_(),
48      sos_(),
49      suffix_handler_(NULL)
50  {
51    Initialize(jnlst, options, argv, suffix_handler, appName, nl_file_content);
52  }
53
54  void
55  AmplTMINLP::Initialize(const SmartPtr<const Journalist>& jnlst,
56      const SmartPtr<OptionsList> options,
57      char**& argv,
58      AmplSuffixHandler* suffix_handler /*=NULL*/,
59      const std::string& appName,
60      std::string* nl_file_content /* = NULL */)
61  {
62
63
64    if(suffix_handler==NULL)
65      suffix_handler_ = suffix_handler = new AmplSuffixHandler();
66
67    // Add the suffix handler for scaling
68    suffix_handler->AddAvailableSuffix("scaling_factor", AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Number_Type);
69    suffix_handler->AddAvailableSuffix("scaling_factor", AmplSuffixHandler::Constraint_Source, AmplSuffixHandler::Number_Type);
70    suffix_handler->AddAvailableSuffix("scaling_factor", AmplSuffixHandler::Objective_Source, AmplSuffixHandler::Number_Type);
71 
72    // priority suffix
73    suffix_handler->AddAvailableSuffix("priority", AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Index_Type);
74    suffix_handler->AddAvailableSuffix("direction", AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Number_Type);
75    suffix_handler->AddAvailableSuffix("downPseudocost", AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Number_Type);
76    suffix_handler->AddAvailableSuffix("upPseudocost", AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Number_Type);
77
78
79
80    // sos suffixes
81    suffix_handler->AddAvailableSuffix("ref", AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Number_Type);
82    suffix_handler->AddAvailableSuffix("sos",AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Index_Type);
83    suffix_handler->AddAvailableSuffix("sos",AmplSuffixHandler::Constraint_Source, AmplSuffixHandler::Index_Type);
84    suffix_handler->AddAvailableSuffix("sosno",AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Number_Type);
85    suffix_handler->AddAvailableSuffix("sosref",AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Number_Type);
86    suffix_handler->AddAvailableSuffix("sstatus", AmplSuffixHandler::Variable_Source, AmplSuffixHandler::Index_Type);
87    suffix_handler->AddAvailableSuffix("sstatus", AmplSuffixHandler::Constraint_Source, AmplSuffixHandler::Index_Type);
88   
89
90    SmartPtr<AmplOptionsList> ampl_options_list = new AmplOptionsList();
91    fillAmplOptionList(GetRawPtr(ampl_options_list));
92    fillApplicationOptions(GetRawPtr(ampl_options_list) );
93    std::string options_id = appName + "_options";
94    ampl_tnlp_ = new AmplTNLP(jnlst, options, argv, suffix_handler, true,
95         ampl_options_list, options_id.c_str(),
96        appName.c_str(), appName.c_str(), nl_file_content);
97    /* Read suffixes */
98    read_priorities();
99    read_sos();
100  }
101
102  AmplTMINLP::~AmplTMINLP()
103  {delete ampl_tnlp_;}
104
105  void
106  AmplTMINLP::read_priorities()
107  {
108    int numcols, m, dummy1, dummy2;
109    TNLP::IndexStyleEnum index_style;
110    ampl_tnlp_->get_nlp_info(numcols, m, dummy1, dummy2, index_style);
111
112    const AmplSuffixHandler * suffix_handler = GetRawPtr(suffix_handler_);
113
114    const Index* pri = suffix_handler->GetIntegerSuffixValues("priority", AmplSuffixHandler::Variable_Source);
115    const Index* brac = suffix_handler->GetIntegerSuffixValues("direction", AmplSuffixHandler::Variable_Source);
116    const Number* upPs = suffix_handler->GetNumberSuffixValues("upPseudocost", AmplSuffixHandler::Variable_Source);
117    const Number* dwPs = suffix_handler->GetNumberSuffixValues("downPseudocost", AmplSuffixHandler::Variable_Source);
118
119
120    branch_.gutsOfDestructor();
121    branch_.size = numcols;
122    if(pri) {
123      branch_.priorities = new int[numcols];
124      for(int i = 0 ; i < numcols ; i++) {
125        branch_.priorities [i] = -pri[i] + 9999;
126      }
127    }
128    if(brac) {
129      branch_.branchingDirections = CoinCopyOfArray(brac,numcols);
130    }
131    if(upPs && !dwPs) dwPs = upPs;
132    else if(dwPs && !upPs) upPs = dwPs;
133 
134    if(upPs) {
135      branch_.upPsCosts = CoinCopyOfArray(upPs,numcols);
136    }
137    if(dwPs) {
138      branch_.downPsCosts = CoinCopyOfArray(dwPs,numcols);
139    }
140  } 
141
142  void
143  AmplTMINLP::read_sos()
144  {
145    ASL_pfgh* asl = ampl_tnlp_->AmplSolverObject();
146
147    int i = ASL_suf_sos_explict_free;
148    int copri[2], **p_sospri;
149    copri[0] = 0;
150    copri[1] = 0;
151    int * starts = NULL;
152    int * indices = NULL;
153    char * types = NULL;
154    double * weights = NULL;
155    int * priorities = NULL;
156    p_sospri = &priorities;
157
158    sos_.gutsOfDestructor();
159
160    sos_.num = suf_sos(i, &sos_.numNz, &types, p_sospri, copri,
161        &starts, &indices, &weights);
162    if (sos_.num) {
163      //Copy sos information
164      sos_.priorities = CoinCopyOfArray(priorities,sos_.num);
165      sos_.starts = CoinCopyOfArray(starts, sos_.num + 1);
166      sos_.indices = CoinCopyOfArray(indices, sos_.numNz);
167      sos_.types = CoinCopyOfArray(types, sos_.num);
168      sos_.weights = CoinCopyOfArray(weights, sos_.numNz);
169
170      ampl_utils::sos_kludge(sos_.num, sos_.starts, sos_.weights);
171      for (int ii=0;ii<sos_.num;ii++) {
172        int ichar = sos_.types[ii];
173        if(ichar != '1') {
174          std::cerr<<"Unsuported type of sos constraint: "<<sos_.types[ii]<<std::endl;
175          throw;
176        }
177        sos_.types[ii]= 1;
178      }
179    }
180  }
181
182  bool AmplTMINLP::get_nlp_info(Index& n, Index& m, Index& nnz_jac_g, Index& nnz_h_lag, TNLP::IndexStyleEnum& index_style)
183  {
184    return ampl_tnlp_->get_nlp_info(n, m, nnz_jac_g, nnz_h_lag, index_style);
185  }
186
187  bool AmplTMINLP::get_var_types(Index n, VariableType* var_types)
188  {
189    // The variables are sorted by type in AMPL, so all we need to
190    // know are the counts of each type.
191
192
193    Index n_non_linear_b= 0;
194    Index n_non_linear_bi= 0;
195    Index n_non_linear_c= 0;
196    Index n_non_linear_ci = 0;
197    Index n_non_linear_o= 0;
198    Index n_non_linear_oi = 0;
199    Index n_binaries = 0;
200    Index n_integers = 0;
201    ampl_tnlp_->get_discrete_info(n_non_linear_b, n_non_linear_bi, n_non_linear_c,
202        n_non_linear_ci, n_non_linear_o, n_non_linear_oi,
203        n_binaries, n_integers);
204    int totalNumberOfNonContinuous = 0;
205    //begin with variables non-linear both in the objective function and in some constraints
206    // The first ones are continuous
207    Index start = 0;
208    Index end = n_non_linear_b - n_non_linear_bi;
209    for (int i=start; i<end; i++) {
210      var_types[i] = CONTINUOUS;
211    }
212
213    // The second ones are integers
214    start = end;
215    end = start + n_non_linear_bi;
216    for (int i=start; i < end; i++) {
217      var_types[i] = INTEGER;
218      totalNumberOfNonContinuous++;
219    }
220
221    //next variables non-linear in some constraints
222    // The first ones are continuous
223    start = end;
224    end = max(start,end + n_non_linear_c - n_non_linear_ci - n_non_linear_b);
225    for (int i=start; i<end; i++) {
226      var_types[i] = CONTINUOUS;
227    }
228
229    // The second ones are integers
230    start = end;
231    end = start + n_non_linear_ci;
232    for (int i=start; i < end; i++) {
233      var_types[i] = INTEGER;
234      totalNumberOfNonContinuous++;
235    }
236
237    //next variables non-linear in the objective function
238    // The first ones are continuous
239    start = end;
240    end = max(start,end + n_non_linear_o - max(n_non_linear_b, n_non_linear_c) - n_non_linear_oi);
241    for (int i=start; i<end; i++) {
242      var_types[i] = CONTINUOUS;
243    }
244
245    // The second ones are integers
246    start = end;
247    end = start + n_non_linear_oi;
248    for (int i=start; i < end; i++) {
249      var_types[i] = INTEGER;
250      totalNumberOfNonContinuous++;
251    }
252
253    //At last the linear variables
254    // The first ones are continuous
255    start = end;
256    end = n - n_binaries - n_integers;
257    for (int i=start; i<end; i++) {
258      var_types[i] = CONTINUOUS;
259    }
260
261    // The second ones are binaries
262    start = end;
263    end = start + n_binaries;
264    for (int i=start; i < end; i++) {
265      var_types[i] = BINARY;
266      totalNumberOfNonContinuous++;
267    }
268
269    // The third ones are integers
270    start = end;
271    end = start + n_integers;
272    for (int i=start; i < end; i++) {
273      var_types[i] = INTEGER;
274      totalNumberOfNonContinuous++;
275    }
276    //    std::cout<<"Number of integer and binaries : "<<totalNumberOfNonContinuous<<std::endl;
277    return true;
278  }
279
280  bool AmplTMINLP::get_constraints_types(Index n, ConstraintType* const_types)
281  {
282    ASL_pfgh* asl = ampl_tnlp_->AmplSolverObject();
283    //check that n is good
284    DBG_ASSERT(n == n_con);
285    // check that there are no network constraints
286    DBG_ASSERT(nlnc == 0 && lnc == 0);
287    //the first nlc constraints are non linear the rest is linear
288    int i;
289    for(i = 0 ; i < nlc ; i++)
290      const_types[i]=NON_LINEAR;
291    // the rest is linear
292    for(; i < n_con ; i++)
293      const_types[i]=LINEAR;
294    return true;
295  }
296
297  bool AmplTMINLP::get_bounds_info(Index n, Number* x_l, Number* x_u,
298      Index m, Number* g_l, Number* g_u)
299  {
300    return ampl_tnlp_->get_bounds_info(n, x_l, x_u, m, g_l, g_u);
301  }
302
303  bool AmplTMINLP::get_starting_point(Index n, bool init_x, Number* x,
304                                    bool init_z, Number* z_L, Number* z_U,
305      Index m, bool init_lambda, Number* lambda)
306  {
307    return ampl_tnlp_->get_starting_point(n, init_x, x,
308        init_z, z_L, z_U,
309        m, init_lambda, lambda);
310  }
311
312  bool AmplTMINLP::eval_f(Index n, const Number* x, bool new_x, Number& obj_value)
313  {
314    return ampl_tnlp_->eval_f(n, x, new_x, obj_value);
315  }
316
317  bool AmplTMINLP::eval_grad_f(Index n, const Number* x, bool new_x, Number* grad_f)
318  {
319    return ampl_tnlp_->eval_grad_f(n, x, new_x, grad_f);
320  }
321
322  bool AmplTMINLP::eval_g(Index n, const Number* x, bool new_x, Index m, Number* g)
323  {
324    return ampl_tnlp_->eval_g(n, x, new_x, m, g);
325  }
326
327  bool AmplTMINLP::eval_jac_g(Index n, const Number* x, bool new_x,
328      Index m, Index nele_jac, Index* iRow,
329      Index *jCol, Number* values)
330  {
331    return ampl_tnlp_->eval_jac_g(n, x, new_x,
332        m, nele_jac, iRow, jCol,
333        values);
334  }
335
336  bool AmplTMINLP::eval_h(Index n, const Number* x, bool new_x,
337      Number obj_factor, Index m, const Number* lambda,
338      bool new_lambda, Index nele_hess, Index* iRow,
339      Index* jCol, Number* values)
340  {
341    return ampl_tnlp_->eval_h(n, x, new_x, obj_factor,
342        m, lambda, new_lambda, nele_hess, iRow,
343        jCol, values);
344  }
345
346  void AmplTMINLP::finalize_solution(SolverReturn status,
347      Index n, const Number* x, const Number* z_L, const Number* z_U,
348      Index m, const Number* g, const Number* lambda,
349      Number obj_value)
350  {
351    // Not sure if ampl require a different form of solution file
352    // for MINLPs - we may have to write a different solution file here instead of
353    // passing this back to ampl.
354    ampl_tnlp_->finalize_solution(status,
355        n, x, z_L, z_U,
356        m, g, lambda,
357        obj_value);
358
359    ASL_pfgh* asl = ampl_tnlp_->AmplSolverObject();
360    solve_result_num = 0;
361  }
362
363  void AmplTMINLP::write_solution(const std::string & message, const Number *x_sol, const Number * lambda_sol)
364  {
365    ASL_pfgh* asl = ampl_tnlp_->AmplSolverObject();
366    ;
367    DBG_ASSERT(asl);
368    //    DBG_ASSERT(x_sol);
369
370    // We need to copy the message into a non-const char array to make
371    // it work with the AMPL C function.
372    char* cmessage = new char[message.length()+1];
373    strcpy(cmessage, message.c_str());
374
375    // In order to avoid casting into non-const, we copy the data here...
376    double* x_sol_copy = NULL;
377    if (x_sol) {
378      x_sol_copy = new double[n_var];
379      for (int i=0; i<n_var; i++) {
380        x_sol_copy[i] = x_sol[i];
381      }
382    }
383    double* lambda_sol_copy = NULL;
384    if (lambda_sol_copy) {
385      lambda_sol_copy = new double[n_con];
386      for (int i=0; i<n_con; i++) {
387        lambda_sol_copy[i] = lambda_sol[i];
388      }
389    }
390    write_sol(cmessage, x_sol_copy, lambda_sol_copy, NULL);
391
392    delete [] x_sol_copy;
393    delete [] lambda_sol_copy;
394    delete [] cmessage;
395
396  }
397
398
399  /** This methods gives the linear part of the objective function */
400  void AmplTMINLP::getLinearPartOfObjective(double * obj)
401  {
402    Index n, m, nnz_jac_g, nnz_h_lag;
403    TNLP::IndexStyleEnum index_style = TNLP::FORTRAN_STYLE;
404    get_nlp_info( n, m, nnz_jac_g, nnz_h_lag, index_style);
405    eval_grad_f(n, NULL, 0,obj);
406    Index n_non_linear_b= 0;
407    Index n_non_linear_bi= 0;
408    Index n_non_linear_c= 0;
409    Index n_non_linear_ci = 0;
410    Index n_non_linear_o= 0;
411    Index n_non_linear_oi = 0;
412    Index n_binaries = 0;
413    Index n_integers = 0;
414    ampl_tnlp_->get_discrete_info(n_non_linear_b, n_non_linear_bi, n_non_linear_c,
415        n_non_linear_ci, n_non_linear_o, n_non_linear_oi,
416        n_binaries, n_integers);
417
418    // Now get the coefficients of variables wich are linear in the objective
419    // The first ones are not
420    Index start = 0;
421    Index end = n_non_linear_b;
422    for (int i=start; i<end; i++) {
423      obj[i] = 0.;
424    }
425
426    //next variables should be linear in the objective just skip them
427    // (from current end to (end + n_non_linear_c - n_non_linear_ci - n_non_linear_b;)
428
429
430    // Those are nonlinear in the objective
431    start = end + n_non_linear_c;
432    end = start + n_non_linear_o;
433    for (int i=start; i < end; i++) {
434      obj[i]=0.;
435    }
436    //The rest is linear keep the values of the gradient
437  }
438
439
440  void
441  AmplTMINLP::fillAmplOptionList(AmplOptionsList* amplOptList)
442  {
443    amplOptList->AddAmplOption("bonmin.algorithm","bonmin.algorithm",
444        AmplOptionsList::String_Option,
445        "Choice of the algorithm.");
446
447    amplOptList->AddAmplOption("bonmin.bb_log_level","bonmin.bb_log_level",
448        AmplOptionsList::Integer_Option,
449        "specify BB log level");
450
451    amplOptList->AddAmplOption("bonmin.lp_log_level","bonmin.lp_log_level",
452        AmplOptionsList::Integer_Option,
453        "specify sub-LP log level");
454
455    amplOptList->AddAmplOption("bonmin.milp_log_level","bonmin.milp_log_level",
456        AmplOptionsList::Integer_Option,
457        "specify sub-MILP log level");
458
459    amplOptList->AddAmplOption("bonmin.oa_log_level","bonmin.oa_log_level",
460        AmplOptionsList::Integer_Option,
461        "specify OA log level");
462
463    amplOptList->AddAmplOption("bonmin.oa_log_frequency","bonmin.oa_log_frequency",
464        AmplOptionsList::Number_Option,
465        "specify OA log frequency");
466
467    amplOptList->AddAmplOption("bonmin.nlp_log_level","bonmin.nlp_log_level",
468        AmplOptionsList::Integer_Option,
469        "specify sub-NLP log level");
470
471    amplOptList->AddAmplOption("bonmin.print_user_options","bonmin.print_user_options",
472        AmplOptionsList::String_Option,
473        "print options list");
474
475    amplOptList->AddAmplOption("bonmin.bb_log_interval","bonmin.bb_log_interval",
476        AmplOptionsList::Integer_Option,
477        "Interval at which bound output is given");
478
479    amplOptList->AddAmplOption("bonmin.allowable_gap","bonmin.allowable_gap",
480        AmplOptionsList::Number_Option,
481        "Specify allowable absolute gap");
482
483    amplOptList->AddAmplOption("bonmin.allowable_fraction_gap","bonmin.allowable_fraction_gap",
484        AmplOptionsList::Number_Option,
485        "Specify allowable relative gap");
486
487    amplOptList->AddAmplOption("bonmin.cutoff_decr","bonmin.cutoff_decr",
488        AmplOptionsList::Number_Option,
489        "Specify cutoff decrement");
490
491    amplOptList->AddAmplOption("bonmin.cutoff","bonmin.cutoff",
492        AmplOptionsList::Number_Option,
493        "Specify cutoff");
494
495    amplOptList->AddAmplOption("bonmin.nodeselect_stra","bonmin.nodeselect_stra",
496        AmplOptionsList::String_Option,
497        "Choose the node selection strategy");
498
499
500    amplOptList->AddAmplOption("bonmin.number_strong_branch", "bonmin.number_strong_branch",
501        AmplOptionsList::Integer_Option,
502        "Chooes number of variable for strong branching");
503
504    amplOptList->AddAmplOption("bonmin.number_before_trust", "bonmin.number_before_trust",
505        AmplOptionsList::Integer_Option,
506        "Set number of branches on a variable before its pseudo-costs are to be believed");
507
508    amplOptList->AddAmplOption("bonmin.time_limit", "bonmin.time_limit",
509        AmplOptionsList::Number_Option,
510        "Set maximum computation time for Algorithm");
511
512    amplOptList->AddAmplOption("bonmin.node_limit","bonmin.node_limit",
513        AmplOptionsList::Integer_Option,
514        "Set maximum number of nodes explored");
515
516    amplOptList->AddAmplOption("bonmin.integer_tolerance", "bonmin.integer_tolerance",
517        AmplOptionsList::Number_Option,
518        "Set integer tolerance");
519
520    amplOptList->AddAmplOption("bonmin.warm_start","bonmin.warm_start",
521        AmplOptionsList::String_Option,
522        "Set warm start method");
523
524    amplOptList->AddAmplOption("bonmin.sos_constraints","bonmin.sos_constraints",
525        AmplOptionsList::String_Option,
526        "Disable SOS contraints");
527
528    amplOptList->AddAmplOption("bonmin.max_random_point_radius",
529        "bonmin.max_random_point_radius",
530        AmplOptionsList::Number_Option,
531        "Set max value for a random point");
532
533    amplOptList->AddAmplOption("bonmin.max_consecutive_failures",
534        "bonmin.max_consecutive_failures",
535        AmplOptionsList::Integer_Option,
536        "Number of consecutive unsolved problems before aborting.");
537
538    amplOptList->AddAmplOption("bonmin.num_iterations_suspect",
539        "bonmin.num_iterations_suspect",
540        AmplOptionsList::Integer_Option,
541        "Number of iteration over which a node is considered suspect");
542
543    amplOptList->AddAmplOption("bonmin.nlp_failure_behavior",
544        "bonmin.nlp_failure_behavior",
545        AmplOptionsList::String_Option,
546        "Set the behavior when the nlp fails.");
547
548    amplOptList->AddAmplOption("bonmin.num_retry_unsolved_random_point",
549        "bonmin.num_retry_unsolved_random_point",
550        AmplOptionsList::Integer_Option,
551        "Number of tries to resolve a failed NLP with a random starting point");
552
553    amplOptList->AddAmplOption("bonmin.max_consecutive_infeasible",
554        "bonmin.max_consecutive_infeasible",
555        AmplOptionsList::Integer_Option,
556        "Number of consecutive infeasible problems before continuing a"
557        " branch.");
558
559    amplOptList->AddAmplOption("bonmin.num_resolve_at_root", "bonmin.num_resolve_at_root",
560        AmplOptionsList::Integer_Option,
561        "Number of tries to resolve the root node with different starting point (only usefull in non-convex).");
562
563    amplOptList->AddAmplOption("bonmin.num_resolve_at_node","bonmin.num_resolve_at_node",
564        AmplOptionsList::Integer_Option,
565        "Number of tries to resolve a non root node with different starting point (only usefull in non-convex).");
566
567
568    amplOptList->AddAmplOption("bonmin.nlp_solve_frequency","bonmin.nlp_solve_frequency",
569        AmplOptionsList::Integer_Option,
570        "Specify the frequency at which nlp relaxations are solved in hybrid.");
571
572    amplOptList->AddAmplOption("bonmin.oa_dec_time_limit", "bonmin.oa_dec_time_limit",
573        AmplOptionsList::Number_Option,
574        "Specify the maximum amount of time spent in OA decomposition iteratrions.");
575
576    amplOptList->AddAmplOption("bonmin.tiny_element","bonmin.tiny_element",
577        AmplOptionsList::Number_Option,
578        "Value for tiny element in OA cut");
579
580    amplOptList->AddAmplOption("bonmin.very_tiny_element","bonmin.very_tiny_element",
581        AmplOptionsList::Number_Option,
582        "Value for very tiny element in OA cut");
583
584    amplOptList->AddAmplOption("bonmin.milp_subsolver", "bonmin.milp_subsolver",
585        AmplOptionsList::String_Option,
586        "Choose the subsolver to solve MILPs sub-problems in OA decompositions.");
587
588    amplOptList->AddAmplOption("bonmin.Gomory_cuts", "bonmin.Gomory_cuts",
589        AmplOptionsList::Integer_Option,
590        "Frequency for Generating Gomory cuts in branch-and-cut.");
591
592    amplOptList->AddAmplOption("bonmin.probing_cuts", "bonmin.probing_cuts",
593        AmplOptionsList::Integer_Option,
594        "Frequency for Generating probing cuts in branch-and-cut");
595
596    amplOptList->AddAmplOption("bonmin.cover_cuts", "bonmin.cover_cuts",
597        AmplOptionsList::Integer_Option,
598        "Frequency for Generating cover cuts in branch-and-cut");
599
600
601    amplOptList->AddAmplOption("bonmin.mir_cuts", "bonmin.mir_cuts",
602        AmplOptionsList::Integer_Option,
603        "Frequency for Generating MIR cuts in branch-and-cut");
604
605  }
606} // namespace Ipopt
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