source: branches/devel/Cbc/src/CbcStrategy.cpp @ 426

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1// Copyright (C) 2005, International Business Machines
2// Corporation and others.  All Rights Reserved.
3#if defined(_MSC_VER)
4// Turn off compiler warning about long names
5#  pragma warning(disable:4786)
6#endif
7
8#include "CbcConfig.h"
9
10#include <cassert>
11#include <cmath>
12#include <cfloat>
13
14#include "OsiSolverInterface.hpp"
15#ifdef COIN_HAS_CLP
16#include "OsiClpSolverInterface.hpp"
17#endif
18#include "CbcModel.hpp"
19#include "CbcMessage.hpp"
20#include "CbcStrategy.hpp"
21#include "CbcCutGenerator.hpp"
22#include "CbcBranchActual.hpp"
23#include "CbcNode.hpp"
24#include "CoinWarmStart.hpp"
25#include "CglPreProcess.hpp"
26// Cuts
27
28#include "CglGomory.hpp"
29#include "CglProbing.hpp"
30#include "CglKnapsackCover.hpp"
31#include "CglOddHole.hpp"
32#include "CglClique.hpp"
33#include "CglFlowCover.hpp"
34#include "CglMixedIntegerRounding2.hpp"
35
36// Heuristics
37
38#include "CbcHeuristic.hpp"
39
40// Default Constructor
41CbcStrategy::CbcStrategy() 
42  :depth_(0),
43   preProcessState_(0),
44   process_(NULL)
45{
46}
47
48// Destructor
49CbcStrategy::~CbcStrategy ()
50{
51  delete process_;
52}
53// Delete pre-processing object to save memory
54void 
55CbcStrategy::deletePreProcess()
56{ 
57  delete process_;
58  process_=NULL;
59}
60// Return a new Full node information pointer (descendant of CbcFullNodeInfo)
61CbcNodeInfo * 
62CbcStrategy::fullNodeInfo(CbcModel * model,int numberRowsAtContinuous) const
63{
64  return new CbcFullNodeInfo(model,numberRowsAtContinuous);
65}
66// Return a new Partial node information pointer (descendant of CbcPartialNodeInfo)
67CbcNodeInfo * 
68CbcStrategy::partialNodeInfo(CbcModel * model, CbcNodeInfo * parent, CbcNode * owner,
69                             int numberChangedBounds,const int * variables,
70                             const double * boundChanges,
71                             const CoinWarmStartDiff *basisDiff) const
72{
73  return new CbcPartialNodeInfo(parent, owner, numberChangedBounds, variables,
74                            boundChanges,basisDiff);
75}
76/* After a CbcModel::resolve this can return a status
77   -1 no effect
78   0 treat as optimal
79   1 as 0 but do not do any more resolves (i.e. no more cuts)
80   2 treat as infeasible
81*/
82int
83CbcStrategy::status(CbcModel * model, CbcNodeInfo * parent,int whereFrom)
84{
85  return -1;
86}
87
88// Default Constructor
89CbcStrategyDefault::CbcStrategyDefault(bool cutsOnlyAtRoot,
90                                       int numberStrong,
91                                       int numberBeforeTrust,
92                                       int printLevel)
93  :CbcStrategy(),
94   cutsOnlyAtRoot_(cutsOnlyAtRoot),
95   numberStrong_(numberStrong),
96   numberBeforeTrust_(numberBeforeTrust),
97   printLevel_(printLevel),
98   desiredPreProcess_(0),
99   preProcessPasses_(0)
100{
101}
102
103
104// Destructor
105CbcStrategyDefault::~CbcStrategyDefault ()
106{
107}
108
109// Clone
110CbcStrategy *
111CbcStrategyDefault::clone() const
112{
113  return new CbcStrategyDefault(*this);
114}
115
116// Copy constructor
117CbcStrategyDefault::CbcStrategyDefault(const CbcStrategyDefault & rhs)
118:
119  CbcStrategy(rhs),
120  cutsOnlyAtRoot_(rhs.cutsOnlyAtRoot_),
121  numberStrong_(rhs.numberStrong_),
122  numberBeforeTrust_(rhs.numberBeforeTrust_),
123  printLevel_(rhs.printLevel_),
124  desiredPreProcess_(rhs.desiredPreProcess_),
125  preProcessPasses_(rhs.preProcessPasses_)
126{
127  setNested(rhs.getNested());
128}
129
130// Setup cut generators
131void 
132CbcStrategyDefault::setupCutGenerators(CbcModel & model)
133{
134  // Set up some cut generators and defaults
135  // Probing first as gets tight bounds on continuous
136
137  CglProbing generator1;
138  generator1.setUsingObjective(true);
139  generator1.setMaxPass(1);
140  // Number of unsatisfied variables to look at
141  generator1.setMaxProbe(10);
142  // How far to follow the consequences
143  generator1.setMaxLook(10);
144  // Only look at rows with fewer than this number of elements
145  generator1.setMaxElements(200);
146  //generator1.setRowCuts(3);
147
148  CglGomory generator2;
149  // try larger limit
150  generator2.setLimit(300);
151
152  CglKnapsackCover generator3;
153
154  //CglOddHole generator4;
155  //generator4.setMinimumViolation(0.005);
156  //generator4.setMinimumViolationPer(0.00002);
157  // try larger limit
158  //generator4.setMaximumEntries(200);
159
160  CglClique generator5;
161  generator5.setStarCliqueReport(false);
162  generator5.setRowCliqueReport(false);
163
164  CglMixedIntegerRounding2 mixedGen;
165  CglFlowCover flowGen;
166 
167  // Add in generators
168  int setting = cutsOnlyAtRoot_ ? -99 : -1;
169  int numberGenerators = model.numberCutGenerators();
170  int iGenerator;
171  bool found;
172  found=false;
173  for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
174    CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
175    CglProbing * cgl = dynamic_cast<CglProbing *>(generator);
176    if (cgl) {
177      found=true;
178      break;
179    }
180  }
181  if (!found)
182    model.addCutGenerator(&generator1,setting,"Probing");
183  found=false;
184  for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
185    CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
186    CglGomory * cgl = dynamic_cast<CglGomory *>(generator);
187    if (cgl) {
188      found=true;
189      break;
190    }
191  }
192  if (!found)
193  model.addCutGenerator(&generator2,setting,"Gomory");
194  found=false;
195  for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
196    CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
197    CglKnapsackCover * cgl = dynamic_cast<CglKnapsackCover *>(generator);
198    if (cgl) {
199      found=true;
200      break;
201    }
202  }
203  if (!found)
204    model.addCutGenerator(&generator3,setting,"Knapsack");
205  //model.addCutGenerator(&generator4,setting,"OddHole");
206  found=false;
207  for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
208    CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
209    CglClique * cgl = dynamic_cast<CglClique *>(generator);
210    if (cgl) {
211      found=true;
212      break;
213    }
214  }
215  if (!found)
216    model.addCutGenerator(&generator5,setting,"Clique");
217  found=false;
218  for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
219    CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
220    CglFlowCover * cgl = dynamic_cast<CglFlowCover *>(generator);
221    if (cgl) {
222      found=true;
223      break;
224    }
225  }
226  if (!found)
227    model.addCutGenerator(&flowGen,setting,"FlowCover");
228  found=false;
229  for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
230    CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
231    CglMixedIntegerRounding2 * cgl = dynamic_cast<CglMixedIntegerRounding2 *>(generator);
232    if (cgl) {
233      found=true;
234      break;
235    }
236  }
237  if (!found)
238    model.addCutGenerator(&mixedGen,setting,"MixedIntegerRounding2");
239  // Say we want timings
240  int newNumberGenerators = model.numberCutGenerators();
241  for (iGenerator=numberGenerators;iGenerator<newNumberGenerators;iGenerator++) {
242    CbcCutGenerator * generator = model.cutGenerator(iGenerator);
243    generator->setTiming(true);
244  }
245  if (model.getNumCols()<500)
246    model.setMaximumCutPassesAtRoot(-100); // always do 100 if possible
247  else if (model.getNumCols()<5000)
248    model.setMaximumCutPassesAtRoot(100); // use minimum drop
249  else
250    model.setMaximumCutPassesAtRoot(20);
251}
252// Setup heuristics
253void 
254CbcStrategyDefault::setupHeuristics(CbcModel & model)
255{
256  // Allow rounding heuristic
257
258  CbcRounding heuristic1(model);
259  int numberHeuristics = model.numberHeuristics();
260  int iHeuristic;
261  bool found;
262  found=false;
263  for (iHeuristic=0;iHeuristic<numberHeuristics;iHeuristic++) {
264    CbcHeuristic * heuristic = model.heuristic(iHeuristic);
265    CbcRounding * cgl = dynamic_cast<CbcRounding *>(heuristic);
266    if (cgl) {
267      found=true;
268      break;
269    }
270  }
271  if (!found)
272    model.addHeuristic(&heuristic1);
273}
274// Do printing stuff
275void 
276CbcStrategyDefault::setupPrinting(CbcModel & model,int modelLogLevel)
277{
278  if (!modelLogLevel) {
279    model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
280    model.messageHandler()->setLogLevel(0);
281    model.solver()->messageHandler()->setLogLevel(0);
282  } else if (modelLogLevel==1) {
283    model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
284    model.messageHandler()->setLogLevel(1);
285    model.solver()->messageHandler()->setLogLevel(0);
286  } else {
287    model.messageHandler()->setLogLevel(2);
288    model.solver()->messageHandler()->setLogLevel(1);
289    model.setPrintFrequency(50);
290  }
291}
292// Other stuff e.g. strong branching
293void 
294CbcStrategyDefault::setupOther(CbcModel & model)
295{
296  // See if preprocessing wanted
297  if (desiredPreProcess_) {
298    delete process_;
299    // solver_ should have been cloned outside
300    CglPreProcess * process = new CglPreProcess();
301    // Pass in models message handler
302    process->passInMessageHandler(model.messageHandler());
303    OsiSolverInterface * solver = model.solver();
304    int logLevel = model.messageHandler()->logLevel();
305#ifdef COIN_HAS_CLP
306    OsiClpSolverInterface * clpSolver = dynamic_cast< OsiClpSolverInterface*> (solver);
307    ClpSimplex * lpSolver=NULL;
308    if (clpSolver) {
309      if (clpSolver->messageHandler()->logLevel())
310        clpSolver->messageHandler()->setLogLevel(1);
311      if (logLevel>-1)
312        clpSolver->messageHandler()->setLogLevel(CoinMin(logLevel,clpSolver->messageHandler()->logLevel()));
313      lpSolver = clpSolver->getModelPtr();
314      /// If user left factorization frequency then compute
315      lpSolver->defaultFactorizationFrequency();
316    }
317#endif
318    // Tell solver we are in Branch and Cut
319    solver->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo) ;
320    // Default set of cut generators
321    CglProbing generator1;
322    generator1.setUsingObjective(true);
323    generator1.setMaxPass(3);
324    generator1.setMaxProbeRoot(solver->getNumCols());
325    generator1.setMaxElements(100);
326    generator1.setMaxLookRoot(50);
327    generator1.setRowCuts(3);
328    //generator1.messageHandler()->setLogLevel(logLevel);
329    // Not needed with pass in process->messageHandler()->setLogLevel(logLevel);
330    // Add in generators
331    process->addCutGenerator(&generator1);
332    int translate[]={9999,0,3,2,-1,-2};
333    OsiSolverInterface * solver2 = 
334      process->preProcessNonDefault(*solver,
335                                    translate[desiredPreProcess_],preProcessPasses_);
336    // Tell solver we are not in Branch and Cut
337    solver->setHintParam(OsiDoInBranchAndCut,false,OsiHintDo) ;
338    if (solver2)
339      solver2->setHintParam(OsiDoInBranchAndCut,false,OsiHintDo) ;
340    bool feasible=true;
341    if (!solver2) {
342      feasible = false;
343      //printf("Pre-processing says infeasible\n");
344      delete process;
345      preProcessState_=-1;
346      process_=NULL;
347    } else {
348      // now tighten bounds
349#ifdef COIN_HAS_CLP
350      if (clpSolver) {
351        // model has changed
352        solver = model.solver();
353        OsiClpSolverInterface * clpSolver = dynamic_cast< OsiClpSolverInterface*> (solver);
354        ClpSimplex * lpSolver = clpSolver->getModelPtr();
355        if (lpSolver->tightenPrimalBounds()==0) {
356          lpSolver->dual();
357        } else {
358          feasible = false;
359        }
360      }
361#endif
362      if (feasible) {
363        preProcessState_=1;
364        process_=process;
365        /* Note that original solver will be kept (with false)
366           and that final solver will also be kept.
367           This is for post-processing
368        */
369        OsiSolverInterface * solver3 = solver2->clone();
370        model.assignSolver(solver3,false);
371        if (process_->numberSOS()) {
372          int numberSOS = process_->numberSOS();
373          int numberIntegers = model.numberIntegers();
374          /* model may not have created objects
375             If none then create
376             NOTE - put back to original column numbers as
377             CbcModel will pack down ALL as it doesn't know where from
378          */
379          bool someObjects = model.numberObjects()>0;
380          if (!numberIntegers||!model.numberObjects()) {
381            model.findIntegers(true);
382            numberIntegers = model.numberIntegers();
383          }
384          CbcObject ** oldObjects = model.objects();
385          // Do sets and priorities
386          CbcObject ** objects = new CbcObject * [numberSOS];
387          // set old objects to have low priority
388          int numberOldObjects = model.numberObjects();
389          int numberColumns = model.getNumCols();
390          for (int iObj = 0;iObj<numberOldObjects;iObj++) {
391            int oldPriority = oldObjects[iObj]->priority();
392            oldObjects[iObj]->setPriority(numberColumns+oldPriority);
393          }
394          const int * starts = process_->startSOS();
395          const int * which = process_->whichSOS();
396          const int * type = process_->typeSOS();
397          const double * weight = process_->weightSOS();
398          int iSOS;
399          for (iSOS =0;iSOS<numberSOS;iSOS++) {
400            int iStart = starts[iSOS];
401            int n=starts[iSOS+1]-iStart;
402            objects[iSOS] = new CbcSOS(&model,n,which+iStart,weight+iStart,
403                                       iSOS,type[iSOS]);
404            // branch on long sets first
405            objects[iSOS]->setPriority(numberColumns-n);
406          }
407          model.addObjects(numberSOS,objects);
408          for (iSOS=0;iSOS<numberSOS;iSOS++)
409            delete objects[iSOS];
410          delete [] objects;
411          if (!someObjects) {
412            // put back old column numbers
413            const int * originalColumns = process_->originalColumns();
414            // use reverse lookup to fake it
415            int n=originalColumns[numberColumns-1]+1;
416            int * fake = new int[n];
417            int i;
418            for ( i=0;i<n;i++)
419              fake[i]=-1;
420            for (i=0;i<numberColumns;i++)
421              fake[originalColumns[i]]=i;
422            for (int iObject=0;iObject<model.numberObjects();iObject++) {
423              // redo ids etc
424              model.modifiableObject(iObject)->redoSequenceEtc(&model,n,fake);
425            }
426            delete [] fake;
427          }
428        }
429      } else {
430        //printf("Pre-processing says infeasible\n");
431        delete process;
432        preProcessState_=-1;
433        process_=NULL;
434      }
435    }
436  }
437  model.setNumberStrong(numberStrong_);
438  model.setNumberBeforeTrust(numberBeforeTrust_);
439}
440// Create C++ lines to get to current state
441void 
442CbcStrategyDefault::generateCpp( FILE * fp) 
443{
444  fprintf(fp,"0#include \"CbcStrategy.hpp\"\n");
445  fprintf(fp,"3  CbcStrategyDefault strategy(%s,%d,%d,%d);\n",
446          cutsOnlyAtRoot_ ? "true" : "false",
447          numberStrong_,
448          numberBeforeTrust_,
449          printLevel_);
450  fprintf(fp,"3  strategy.setupPreProcessing(%d,%d);\n",
451          desiredPreProcess_,preProcessPasses_);
452}
453// Default Constructor
454CbcStrategyDefaultSubTree::CbcStrategyDefaultSubTree(CbcModel * parent ,
455                                                     bool cutsOnlyAtRoot,
456                                       int numberStrong,
457                                       int numberBeforeTrust,
458                                       int printLevel)
459  :CbcStrategy(),
460   parentModel_(parent),
461   cutsOnlyAtRoot_(cutsOnlyAtRoot),
462   numberStrong_(numberStrong),
463   numberBeforeTrust_(numberBeforeTrust),
464   printLevel_(printLevel)
465{
466}
467
468
469// Destructor
470CbcStrategyDefaultSubTree::~CbcStrategyDefaultSubTree ()
471{
472}
473
474// Clone
475CbcStrategy *
476CbcStrategyDefaultSubTree::clone() const
477{
478  return new CbcStrategyDefaultSubTree(*this);
479}
480
481// Copy constructor
482CbcStrategyDefaultSubTree::CbcStrategyDefaultSubTree(const CbcStrategyDefaultSubTree & rhs)
483:
484  CbcStrategy(rhs),
485  parentModel_(rhs.parentModel_),
486  cutsOnlyAtRoot_(rhs.cutsOnlyAtRoot_),
487  numberStrong_(rhs.numberStrong_),
488  numberBeforeTrust_(rhs.numberBeforeTrust_),
489  printLevel_(rhs.printLevel_)
490{
491  setNested(rhs.getNested());
492}
493
494// Setup cut generators
495void 
496CbcStrategyDefaultSubTree::setupCutGenerators(CbcModel & model)
497{
498  // Set up some cut generators and defaults
499  // Probing first as gets tight bounds on continuous
500
501  CglProbing generator1;
502  generator1.setUsingObjective(true);
503  generator1.setMaxPass(1);
504  // Number of unsatisfied variables to look at
505  generator1.setMaxProbe(10);
506  // How far to follow the consequences
507  generator1.setMaxLook(10);
508  // Only look at rows with fewer than this number of elements
509  generator1.setMaxElements(200);
510  //generator1.setRowCuts(3);
511
512  CglGomory generator2;
513  // try larger limit
514  generator2.setLimit(300);
515
516  CglKnapsackCover generator3;
517
518  //CglOddHole generator4;
519  //generator4.setMinimumViolation(0.005);
520  //generator4.setMinimumViolationPer(0.00002);
521  // try larger limit
522  //generator4.setMaximumEntries(200);
523
524  CglClique generator5;
525  generator5.setStarCliqueReport(false);
526  generator5.setRowCliqueReport(false);
527
528  CglMixedIntegerRounding2 mixedGen;
529  CglFlowCover flowGen;
530 
531  // Add in generators
532  int setting = cutsOnlyAtRoot_ ? -99 : -1;
533  int numberGenerators = model.numberCutGenerators();
534  int numberParentGenerators = parentModel_->numberCutGenerators();
535  int iGenerator;
536  bool found;
537  found=false;
538  int howOften=0;
539  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
540    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
541    CglProbing * cgl = dynamic_cast<CglProbing *>(generator);
542    if (cgl) {
543      found=true;
544      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
545      break;
546    }
547  }
548  if (found&&howOften>=0) {
549    found=false;
550    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
551      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
552      CglProbing * cgl = dynamic_cast<CglProbing *>(generator);
553      if (cgl) {
554        found=true;
555        break;
556      }
557    }
558    if (!found)
559      model.addCutGenerator(&generator1,setting,"Probing");
560  }
561  found=false;
562  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
563    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
564    CglGomory * cgl = dynamic_cast<CglGomory *>(generator);
565    if (cgl) {
566      found=true;
567      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
568      break;
569    }
570  }
571  if (found&&howOften>=0) {
572    found=false;
573    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
574      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
575      CglGomory * cgl = dynamic_cast<CglGomory *>(generator);
576      if (cgl) {
577        found=true;
578        break;
579      }
580    }
581    if (!found)
582      model.addCutGenerator(&generator2,setting,"Gomory");
583  }
584  found=false;
585  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
586    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
587    CglKnapsackCover * cgl = dynamic_cast<CglKnapsackCover *>(generator);
588    if (cgl) {
589      found=true;
590      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
591      break;
592    }
593  }
594  if (found&&howOften>=0) {
595    found=false;
596    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
597      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
598      CglKnapsackCover * cgl = dynamic_cast<CglKnapsackCover *>(generator);
599      if (cgl) {
600        found=true;
601        break;
602      }
603    }
604    if (!found)
605      model.addCutGenerator(&generator3,setting,"Knapsack");
606  }
607  found=false;
608  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
609    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
610    CglClique * cgl = dynamic_cast<CglClique *>(generator);
611    if (cgl) {
612      found=true;
613      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
614      break;
615    }
616  }
617  if (found&&howOften>=0) {
618    found=false;
619    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
620      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
621      CglClique * cgl = dynamic_cast<CglClique *>(generator);
622      if (cgl) {
623        found=true;
624        break;
625      }
626    }
627    if (!found)
628      model.addCutGenerator(&generator5,setting,"Clique");
629  }
630  found=false;
631  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
632    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
633    CglFlowCover * cgl = dynamic_cast<CglFlowCover *>(generator);
634    if (cgl) {
635      found=true;
636      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
637      break;
638    }
639  }
640  if (found&&howOften>=0) {
641    found=false;
642    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
643      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
644      CglFlowCover * cgl = dynamic_cast<CglFlowCover *>(generator);
645      if (cgl) {
646        found=true;
647        break;
648      }
649    }
650    if (!found)
651      model.addCutGenerator(&flowGen,setting,"FlowCover");
652    found=false;
653  }
654  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
655    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
656    CglMixedIntegerRounding2 * cgl = dynamic_cast<CglMixedIntegerRounding2 *>(generator);
657    if (cgl) {
658      found=true;
659      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
660      break;
661    }
662  }
663  if (found&&howOften>=0) {
664    found=false;
665    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
666      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
667      CglMixedIntegerRounding2 * cgl = dynamic_cast<CglMixedIntegerRounding2 *>(generator);
668      if (cgl) {
669        found=true;
670        break;
671      }
672    }
673    if (!found)
674      model.addCutGenerator(&mixedGen,setting,"MixedIntegerRounding2");
675  }
676#if 0
677  // Say we want timings
678  int newNumberGenerators = model.numberCutGenerators();
679  for (iGenerator=numberGenerators;iGenerator<newNumberGenerators;iGenerator++) {
680    CbcCutGenerator * generator = model.cutGenerator(iGenerator);
681    generator->setTiming(true);
682  }
683#endif
684  if (model.getNumCols()<500)
685    model.setMaximumCutPassesAtRoot(-100); // always do 100 if possible
686  else if (model.getNumCols()<5000)
687    model.setMaximumCutPassesAtRoot(100); // use minimum drop
688  else
689    model.setMaximumCutPassesAtRoot(20);
690}
691// Setup heuristics
692void 
693CbcStrategyDefaultSubTree::setupHeuristics(CbcModel & model)
694{
695  // Allow rounding heuristic
696
697  CbcRounding heuristic1(model);
698  int numberHeuristics = model.numberHeuristics();
699  int iHeuristic;
700  bool found;
701  found=false;
702  for (iHeuristic=0;iHeuristic<numberHeuristics;iHeuristic++) {
703    CbcHeuristic * heuristic = model.heuristic(iHeuristic);
704    CbcRounding * cgl = dynamic_cast<CbcRounding *>(heuristic);
705    if (cgl) {
706      found=true;
707      break;
708    }
709  }
710  if (!found)
711    model.addHeuristic(&heuristic1);
712}
713// Do printing stuff
714void 
715CbcStrategyDefaultSubTree::setupPrinting(CbcModel & model,int modelLogLevel)
716{
717  if (!modelLogLevel) {
718    model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
719    model.messageHandler()->setLogLevel(0);
720    model.solver()->messageHandler()->setLogLevel(0);
721  } else if (modelLogLevel==1) {
722    model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
723    model.messageHandler()->setLogLevel(1);
724    model.solver()->messageHandler()->setLogLevel(0);
725  } else {
726    model.messageHandler()->setLogLevel(2);
727    model.solver()->messageHandler()->setLogLevel(1);
728    model.setPrintFrequency(50);
729  }
730}
731// Other stuff e.g. strong branching
732void 
733CbcStrategyDefaultSubTree::setupOther(CbcModel & model)
734{
735  model.setNumberStrong(numberStrong_);
736  model.setNumberBeforeTrust(numberBeforeTrust_);
737}
738
739
740 
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