source: branches/devel/Cbc/src/CbcStrategy.cpp @ 489

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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(CoinMax(2,model.messageHandler()->logLevel()));
288    model.solver()->messageHandler()->setLogLevel(CoinMax(1,model.solver()->messageHandler()->logLevel()));
289    model.setPrintFrequency(CoinMin(50,model.printFrequency()));
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          OsiObject ** oldObjects = model.objects();
385          // Do sets and priorities
386          OsiObject ** objects = new OsiObject * [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              CbcSimpleInteger * obj =
425                dynamic_cast <CbcSimpleInteger *>(model.modifiableObject(iObject)) ;
426              if (obj) {
427                obj->resetSequenceEtc(n,fake);
428              } else {
429                // redo ids etc
430                CbcObject * obj =
431                  dynamic_cast <CbcObject *>(model.modifiableObject(iObject)) ;
432                assert (obj);
433                obj->redoSequenceEtc(&model,n,fake);
434              }
435            }
436            delete [] fake;
437          }
438        }
439      } else {
440        //printf("Pre-processing says infeasible\n");
441        delete process;
442        preProcessState_=-1;
443        process_=NULL;
444      }
445    }
446  }
447  model.setNumberStrong(numberStrong_);
448  model.setNumberBeforeTrust(numberBeforeTrust_);
449}
450// Create C++ lines to get to current state
451void 
452CbcStrategyDefault::generateCpp( FILE * fp) 
453{
454  fprintf(fp,"0#include \"CbcStrategy.hpp\"\n");
455  fprintf(fp,"3  CbcStrategyDefault strategy(%s,%d,%d,%d);\n",
456          cutsOnlyAtRoot_ ? "true" : "false",
457          numberStrong_,
458          numberBeforeTrust_,
459          printLevel_);
460  fprintf(fp,"3  strategy.setupPreProcessing(%d,%d);\n",
461          desiredPreProcess_,preProcessPasses_);
462}
463// Default Constructor
464CbcStrategyDefaultSubTree::CbcStrategyDefaultSubTree(CbcModel * parent ,
465                                                     bool cutsOnlyAtRoot,
466                                       int numberStrong,
467                                       int numberBeforeTrust,
468                                       int printLevel)
469  :CbcStrategy(),
470   parentModel_(parent),
471   cutsOnlyAtRoot_(cutsOnlyAtRoot),
472   numberStrong_(numberStrong),
473   numberBeforeTrust_(numberBeforeTrust),
474   printLevel_(printLevel)
475{
476}
477
478
479// Destructor
480CbcStrategyDefaultSubTree::~CbcStrategyDefaultSubTree ()
481{
482}
483
484// Clone
485CbcStrategy *
486CbcStrategyDefaultSubTree::clone() const
487{
488  return new CbcStrategyDefaultSubTree(*this);
489}
490
491// Copy constructor
492CbcStrategyDefaultSubTree::CbcStrategyDefaultSubTree(const CbcStrategyDefaultSubTree & rhs)
493:
494  CbcStrategy(rhs),
495  parentModel_(rhs.parentModel_),
496  cutsOnlyAtRoot_(rhs.cutsOnlyAtRoot_),
497  numberStrong_(rhs.numberStrong_),
498  numberBeforeTrust_(rhs.numberBeforeTrust_),
499  printLevel_(rhs.printLevel_)
500{
501  setNested(rhs.getNested());
502}
503
504// Setup cut generators
505void 
506CbcStrategyDefaultSubTree::setupCutGenerators(CbcModel & model)
507{
508  // Set up some cut generators and defaults
509  // Probing first as gets tight bounds on continuous
510
511  CglProbing generator1;
512  generator1.setUsingObjective(true);
513  generator1.setMaxPass(1);
514  // Number of unsatisfied variables to look at
515  generator1.setMaxProbe(10);
516  // How far to follow the consequences
517  generator1.setMaxLook(10);
518  // Only look at rows with fewer than this number of elements
519  generator1.setMaxElements(200);
520  //generator1.setRowCuts(3);
521
522  CglGomory generator2;
523  // try larger limit
524  generator2.setLimit(300);
525
526  CglKnapsackCover generator3;
527
528  //CglOddHole generator4;
529  //generator4.setMinimumViolation(0.005);
530  //generator4.setMinimumViolationPer(0.00002);
531  // try larger limit
532  //generator4.setMaximumEntries(200);
533
534  CglClique generator5;
535  generator5.setStarCliqueReport(false);
536  generator5.setRowCliqueReport(false);
537
538  CglMixedIntegerRounding2 mixedGen;
539  CglFlowCover flowGen;
540 
541  // Add in generators
542  int setting = cutsOnlyAtRoot_ ? -99 : -1;
543  int numberGenerators = model.numberCutGenerators();
544  int numberParentGenerators = parentModel_->numberCutGenerators();
545  int iGenerator;
546  bool found;
547  found=false;
548  int howOften=0;
549  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
550    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
551    CglProbing * cgl = dynamic_cast<CglProbing *>(generator);
552    if (cgl) {
553      found=true;
554      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
555      break;
556    }
557  }
558  if (found&&howOften>=0) {
559    found=false;
560    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
561      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
562      CglProbing * cgl = dynamic_cast<CglProbing *>(generator);
563      if (cgl) {
564        found=true;
565        break;
566      }
567    }
568    if (!found)
569      model.addCutGenerator(&generator1,setting,"Probing");
570  }
571  found=false;
572  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
573    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
574    CglGomory * cgl = dynamic_cast<CglGomory *>(generator);
575    if (cgl) {
576      found=true;
577      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
578      break;
579    }
580  }
581  if (found&&howOften>=0) {
582    found=false;
583    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
584      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
585      CglGomory * cgl = dynamic_cast<CglGomory *>(generator);
586      if (cgl) {
587        found=true;
588        break;
589      }
590    }
591    if (!found)
592      model.addCutGenerator(&generator2,setting,"Gomory");
593  }
594  found=false;
595  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
596    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
597    CglKnapsackCover * cgl = dynamic_cast<CglKnapsackCover *>(generator);
598    if (cgl) {
599      found=true;
600      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
601      break;
602    }
603  }
604  if (found&&howOften>=0) {
605    found=false;
606    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
607      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
608      CglKnapsackCover * cgl = dynamic_cast<CglKnapsackCover *>(generator);
609      if (cgl) {
610        found=true;
611        break;
612      }
613    }
614    if (!found)
615      model.addCutGenerator(&generator3,setting,"Knapsack");
616  }
617  found=false;
618  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
619    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
620    CglClique * cgl = dynamic_cast<CglClique *>(generator);
621    if (cgl) {
622      found=true;
623      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
624      break;
625    }
626  }
627  if (found&&howOften>=0) {
628    found=false;
629    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
630      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
631      CglClique * cgl = dynamic_cast<CglClique *>(generator);
632      if (cgl) {
633        found=true;
634        break;
635      }
636    }
637    if (!found)
638      model.addCutGenerator(&generator5,setting,"Clique");
639  }
640  found=false;
641  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
642    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
643    CglFlowCover * cgl = dynamic_cast<CglFlowCover *>(generator);
644    if (cgl) {
645      found=true;
646      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
647      break;
648    }
649  }
650  if (found&&howOften>=0) {
651    found=false;
652    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
653      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
654      CglFlowCover * cgl = dynamic_cast<CglFlowCover *>(generator);
655      if (cgl) {
656        found=true;
657        break;
658      }
659    }
660    if (!found)
661      model.addCutGenerator(&flowGen,setting,"FlowCover");
662    found=false;
663  }
664  for (iGenerator=0;iGenerator<numberParentGenerators;iGenerator++) {
665    CglCutGenerator * generator = parentModel_->cutGenerator(iGenerator)->generator();
666    CglMixedIntegerRounding2 * cgl = dynamic_cast<CglMixedIntegerRounding2 *>(generator);
667    if (cgl) {
668      found=true;
669      howOften = parentModel_->cutGenerator(iGenerator)->howOften();
670      break;
671    }
672  }
673  if (found&&howOften>=0) {
674    found=false;
675    for (iGenerator=0;iGenerator<numberGenerators;iGenerator++) {
676      CglCutGenerator * generator = model.cutGenerator(iGenerator)->generator();
677      CglMixedIntegerRounding2 * cgl = dynamic_cast<CglMixedIntegerRounding2 *>(generator);
678      if (cgl) {
679        found=true;
680        break;
681      }
682    }
683    if (!found)
684      model.addCutGenerator(&mixedGen,setting,"MixedIntegerRounding2");
685  }
686#if 0
687  // Say we want timings
688  int newNumberGenerators = model.numberCutGenerators();
689  for (iGenerator=numberGenerators;iGenerator<newNumberGenerators;iGenerator++) {
690    CbcCutGenerator * generator = model.cutGenerator(iGenerator);
691    generator->setTiming(true);
692  }
693#endif
694  if (model.getNumCols()<500)
695    model.setMaximumCutPassesAtRoot(-100); // always do 100 if possible
696  else if (model.getNumCols()<5000)
697    model.setMaximumCutPassesAtRoot(100); // use minimum drop
698  else
699    model.setMaximumCutPassesAtRoot(20);
700}
701// Setup heuristics
702void 
703CbcStrategyDefaultSubTree::setupHeuristics(CbcModel & model)
704{
705  // Allow rounding heuristic
706
707  CbcRounding heuristic1(model);
708  int numberHeuristics = model.numberHeuristics();
709  int iHeuristic;
710  bool found;
711  found=false;
712  for (iHeuristic=0;iHeuristic<numberHeuristics;iHeuristic++) {
713    CbcHeuristic * heuristic = model.heuristic(iHeuristic);
714    CbcRounding * cgl = dynamic_cast<CbcRounding *>(heuristic);
715    if (cgl) {
716      found=true;
717      break;
718    }
719  }
720  if (!found)
721    model.addHeuristic(&heuristic1);
722}
723// Do printing stuff
724void 
725CbcStrategyDefaultSubTree::setupPrinting(CbcModel & model,int modelLogLevel)
726{
727  if (!modelLogLevel) {
728    model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
729    model.messageHandler()->setLogLevel(0);
730    model.solver()->messageHandler()->setLogLevel(0);
731  } else if (modelLogLevel==1) {
732    model.solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry);
733    model.messageHandler()->setLogLevel(1);
734    model.solver()->messageHandler()->setLogLevel(0);
735  } else {
736    model.messageHandler()->setLogLevel(2);
737    model.solver()->messageHandler()->setLogLevel(1);
738    model.setPrintFrequency(50);
739  }
740}
741// Other stuff e.g. strong branching
742void 
743CbcStrategyDefaultSubTree::setupOther(CbcModel & model)
744{
745  model.setNumberStrong(numberStrong_);
746  model.setNumberBeforeTrust(numberBeforeTrust_);
747}
748
749
750 
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