source: trunk/Cbc/src/CbcModel.hpp @ 961

Last change on this file since 961 was 961, checked in by forrest, 12 years ago

add multi heuristic

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1// Copyright (C) 2002, International Business Machines
2// Corporation and others.  All Rights Reserved.
3#ifndef CbcModel_H
4#define CbcModel_H
5#include <string>
6#include <vector>
7#include "CoinFinite.hpp"
8#include "CoinMessageHandler.hpp"
9#include "OsiSolverInterface.hpp"
10#include "OsiBranchingObject.hpp"
11#include "OsiCuts.hpp"
12#include "CoinWarmStartBasis.hpp"
13#include "CbcCompareBase.hpp"
14#include "CbcMessage.hpp"
15
16//class OsiSolverInterface;
17
18class CbcCutGenerator;
19class OsiRowCut;
20class OsiBabSolver;
21class OsiRowCutDebugger;
22class CglCutGenerator;
23class CbcCutModifier;
24class CglTreeProbingInfo;
25class CbcHeuristic;
26class OsiObject;
27class CbcTree;
28class CbcStrategy;
29class CbcFeasibilityBase;
30class CbcStatistics;
31class CbcEventHandler ;
32class CglPreProcess;
33# ifdef COIN_HAS_CLP
34class ClpNodeStuff;
35#endif
36// #define CBC_CHECK_BASIS 1
37
38//#############################################################################
39
40/** Simple Branch and bound class
41
42  The initialSolve() method solves the initial LP relaxation of the MIP
43  problem. The branchAndBound() method can then be called to finish using
44  a branch and cut algorithm.
45
46  <h3>Search Tree Traversal</h3>
47
48  Subproblems (aka nodes) requiring additional evaluation are stored using
49  the CbcNode and CbcNodeInfo objects. Ancestry linkage is maintained in the
50  CbcNodeInfo object. Evaluation of a subproblem within branchAndBound()
51  proceeds as follows:
52  <ul>
53    <li> The node representing the most promising parent subproblem is popped
54         from the heap which holds the set of subproblems requiring further
55         evaluation.
56    <li> Using branching instructions stored in the node, and information in
57         its ancestors, the model and solver are adjusted to create the
58         active subproblem.
59    <li> If the parent subproblem will require further evaluation
60         (<i>i.e.</i>, there are branches remaining) its node is pushed back
61         on the heap. Otherwise, the node is deleted.  This may trigger
62         recursive deletion of ancestors.
63    <li> The newly created subproblem is evaluated.
64    <li> If the subproblem requires further evaluation, a node is created.
65         All information needed to recreate the subproblem (branching
66         information, row and column cuts) is placed in the node and the node
67         is added to the set of subproblems awaiting further evaluation.
68  </ul>
69  Note that there is never a node representing the active subproblem; the model
70  and solver represent the active subproblem.
71
72  <h3>Row (Constraint) Cut Handling</h3>
73
74  For a typical subproblem, the sequence of events is as follows:
75  <ul>
76    <li> The subproblem is rebuilt for further evaluation: One result of a
77         call to addCuts() is a traversal of ancestors, leaving a list of all
78         cuts used in the ancestors in #addedCuts_. This list is then scanned
79         to construct a basis that includes only tight cuts. Entries for
80         loose cuts are set to NULL.
81    <li> The subproblem is evaluated: One result of a call to solveWithCuts()
82         is the return of a set of newly generated cuts for the subproblem.
83         #addedCuts_ is also kept up-to-date as old cuts become loose.
84    <li> The subproblem is stored for further processing: A call to
85         CbcNodeInfo::addCuts() adds the newly generated cuts to the
86         CbcNodeInfo object associated with this node.
87  </ul>
88  See CbcCountRowCut for details of the bookkeeping associated with cut
89  management.
90*/
91
92class CbcModel  {
93 
94public:
95
96enum CbcIntParam {
97  /** The maximum number of nodes before terminating */
98  CbcMaxNumNode=0,
99  /** The maximum number of solutions before terminating */
100  CbcMaxNumSol,
101  /** Fathoming discipline
102
103    Controls objective function comparisons for purposes of fathoming by bound
104    or determining monotonic variables.
105
106    If 1, action is taken only when the current objective is strictly worse
107    than the target. Implementation is handled by adding a small tolerance to
108    the target.
109  */
110  CbcFathomDiscipline,
111  /** Adjusts printout
112      1 does different node message with number unsatisfied on last branch
113  */
114  CbcPrinting,
115  /** Just a marker, so that a static sized array can store parameters. */
116  CbcLastIntParam
117};
118
119enum CbcDblParam {
120  /** The maximum amount the value of an integer variable can vary from
121      integer and still be considered feasible. */
122  CbcIntegerTolerance=0,
123  /** The objective is assumed to worsen by this amount for each
124      integer infeasibility. */
125  CbcInfeasibilityWeight,
126  /** The amount by which to tighten the objective function cutoff when
127      a new solution is discovered. */
128  CbcCutoffIncrement,
129  /** Stop when the gap between the objective value of the best known solution
130    and the best bound on the objective of any solution is less than this.
131 
132    This is an absolute value. Conversion from a percentage is left to the
133    client.
134  */
135  CbcAllowableGap,
136  /** Stop when the gap between the objective value of the best known solution
137    and the best bound on the objective of any solution is less than this
138    fraction of of the absolute value of best known solution.
139 
140    Code stops if either this test or CbcAllowableGap test succeeds
141  */
142  CbcAllowableFractionGap,
143  /** \brief The maximum number of seconds before terminating.
144             A double should be adequate! */
145  CbcMaximumSeconds,
146  /// Cutoff - stored for speed
147  CbcCurrentCutoff,
148  /// Optimization direction - stored for speed
149  CbcOptimizationDirection,
150  /// Current objective value
151  CbcCurrentObjectiveValue,
152  /// Current minimization objective value
153  CbcCurrentMinimizationObjectiveValue,
154  /** \brief The time at start of model.
155             So that other pieces of code can access */
156  CbcStartSeconds,
157  /** Just a marker, so that a static sized array can store parameters. */
158  CbcLastDblParam
159};
160
161  //---------------------------------------------------------------------------
162
163public:
164  ///@name Solve methods
165  //@{
166    /** \brief Solve the initial LP relaxation
167
168      Invoke the solver's %initialSolve() method.
169    */
170    void initialSolve(); 
171
172    /** \brief Invoke the branch \& cut algorithm
173
174      The method assumes that initialSolve() has been called to solve the
175      LP relaxation. It processes the root node, then proceeds to explore the
176      branch & cut search tree. The search ends when the tree is exhausted or
177      one of several execution limits is reached.
178      If doStatistics is 1 summary statistics are printed
179      if 2 then also the path to best solution (if found by branching)
180      if 3 then also one line per node
181    */
182     void branchAndBound(int doStatistics=0);
183
184    /** \brief create a clean model from partially fixed problem
185
186      The method creates a new model with given bounds and with no tree.
187    */
188     CbcModel *  cleanModel(const double * lower, const double * upper);
189    /** \brief Invoke the branch \& cut algorithm on partially fixed problem
190
191      The method presolves the given model and does branch and cut. The search
192      ends when the tree is exhausted or maximum nodes is reached.
193
194      If better solution found then it is saved.
195
196      Returns 0 if search completed and solution, 1 if not completed and solution,
197      2 if completed and no solution, 3 if not completed and no solution.
198
199      Normally okay to do cleanModel immediately followed by subBranchandBound
200      (== other form of subBranchAndBound)
201      but may need to get at model for advanced features.
202
203      Deletes model2
204    */
205     int subBranchAndBound(CbcModel * model2,
206                           CbcModel * presolvedModel,
207                           int maximumNodes);
208    /** \brief Invoke the branch \& cut algorithm on partially fixed problem
209
210      The method creates a new model with given bounds, presolves it
211      then proceeds to explore the branch & cut search tree. The search
212      ends when the tree is exhausted or maximum nodes is reached.
213
214      If better solution found then it is saved.
215
216      Returns 0 if search completed and solution, 1 if not completed and solution,
217      2 if completed and no solution, 3 if not completed and no solution.
218
219      This is just subModel immediately followed by other version of
220      subBranchandBound.
221
222    */
223     int subBranchAndBound(const double * lower, const double * upper,
224                            int maximumNodes);
225
226    /** \brief Process root node and return a strengthened model
227
228      The method assumes that initialSolve() has been called to solve the
229      LP relaxation. It processes the root node and then returns a pointer
230      to the strengthened model (or NULL if infeasible)
231    */
232     OsiSolverInterface *  strengthenedModel();
233  /** preProcess problem - replacing solver
234      If makeEquality true then <= cliques converted to ==.
235      Presolve will be done numberPasses times.
236
237      Returns NULL if infeasible
238
239      If makeEquality is 1 add slacks to get cliques,
240      if 2 add slacks to get sos (but only if looks plausible) and keep sos info
241  */
242  CglPreProcess * preProcess( int makeEquality=0, int numberPasses=5,
243                  int tuning=5);
244  /** Does postprocessing - original solver back.
245      User has to delete process */
246  void postProcess(CglPreProcess * process);
247private:
248    /** \brief Evaluate a subproblem using cutting planes and heuristics
249
250      The method invokes a main loop which generates cuts, applies heuristics,
251      and reoptimises using the solver's native %resolve() method.
252      It returns true if the subproblem remains feasible at the end of the
253      evaluation.
254    */
255  bool solveWithCuts(OsiCuts & cuts, int numberTries,CbcNode * node);
256  /** Input one node output N nodes to put on tree and optional solution update
257      This should be able to operate in parallel so is given a solver and is const(ish)
258      However we will need to keep an array of solver_ and bases and more
259      status is 0 for normal, 1 if solution
260      Calling code should always push nodes back on tree
261  */
262  CbcNode ** solveOneNode(int whichSolver,CbcNode * node, 
263                          int & numberNodesOutput, int & status) ;
264  /// Update size of whichGenerator
265  void resizeWhichGenerator(int numberNow, int numberAfter);
266public:
267#ifndef CBC_THREAD
268#define NEW_UPDATE_OBJECT 2
269#else
270#define NEW_UPDATE_OBJECT 2
271#endif
272#if NEW_UPDATE_OBJECT>1
273  /// Adds an update information object
274  void addUpdateInformation(const CbcObjectUpdateData & data);
275#endif
276  /** Do one node - broken out for clarity?
277      also for parallel (when baseModel!=this)
278      Returns 1 if solution found
279      node NULL on return if no branches left
280      newNode NULL if no new node created
281  */
282  int doOneNode(CbcModel * baseModel, CbcNode * & node, CbcNode * & newNode);
283
284  /// Returns true if locked
285  bool isLocked() const;
286  /// Main loop (without threads but when subtrees) 1 if finished, 0 if stopped
287#if 0
288  int whileIterating(bool & locked, threadId, threadInfo,condition_mutex,condition_main,
289                     timeWaiting,threadModel,threadStats,totalTime,cutoff,
290                     eventHandler,saveCompare,lastDepth,lastUnsatisfied,createdNode);
291#else
292  int whileIterating(int numberIterations);
293#endif
294#ifdef CBC_THREAD
295  /**
296     Locks a thread if parallel so that stuff like cut pool
297     can be updated and/or used.
298  */
299  void lockThread();
300  /**
301     Unlocks a thread if parallel to say cut pool stuff not needed
302  */
303  void unlockThread();
304#else
305  inline void lockThread() {}
306  inline void unlockThread() {}
307#endif
308private:
309  /** Move/copy information from one model to another
310      -1 - initialization
311      0 - from base model
312      1 - to base model (and reset)
313      2 - add in final statistics etc (and reset so can do clean destruction)
314  */
315  void moveToModel(CbcModel * baseModel,int mode);
316public:
317    /** \brief Reoptimise an LP relaxation
318   
319      Invoke the solver's %resolve() method.
320      whereFrom -
321      0 - initial continuous
322      1 - resolve on branch (before new cuts)
323      2 - after new cuts
324      3  - obsolete code or something modified problem in unexpected way
325      10 - after strong branching has fixed variables at root
326      11 - after strong branching has fixed variables in tree
327
328      returns 1 feasible, 0 infeasible, -1 feasible but skip cuts
329    */
330    int resolve(CbcNodeInfo * parent, int whereFrom);
331    /// Make given rows (L or G) into global cuts and remove from lp
332    void makeGlobalCuts(int numberRows,const int * which); 
333    /// Make given cut into a global cut
334    void makeGlobalCut(const OsiRowCut * cut); 
335    /// Make given cut into a global cut
336    void makeGlobalCut(const OsiRowCut & cut); 
337  //@}
338
339  /** \name Presolve methods */
340  //@{
341
342  /** Identify cliques and construct corresponding objects.
343
344      Find cliques with size in the range
345      [\p atLeastThisMany, \p lessThanThis] and construct corresponding
346      CbcClique objects.
347      If \p makeEquality is true then a new model may be returned if
348      modifications had to be made, otherwise \c this is returned.
349      If the problem is infeasible #numberObjects_ is set to -1.
350      A client must use deleteObjects() before a second call to findCliques().
351      If priorities exist, clique priority is set to the default.
352  */
353  CbcModel * findCliques(bool makeEquality, int atLeastThisMany,
354                         int lessThanThis, int defaultValue=1000);
355
356  /** Do integer presolve, creating a new (presolved) model.
357
358    Returns the new model, or NULL if feasibility is lost.
359    If weak is true then just does a normal presolve
360 
361    \todo It remains to work out the cleanest way of getting a solution to
362          the original problem at the end. So this is very preliminary.
363   */
364  CbcModel * integerPresolve(bool weak=false);
365
366  /** Do integer presolve, modifying the current model.
367
368      Returns true if the model remains feasible after presolve.
369  */
370  bool integerPresolveThisModel(OsiSolverInterface * originalSolver,bool weak=false);
371
372
373  /// Put back information into the original model after integer presolve.
374  void originalModel(CbcModel * presolvedModel,bool weak);
375
376  /** \brief For variables involved in VUB constraints, see if we can tighten
377             bounds by solving lp's
378
379      Returns false if feasibility is lost.
380      If CglProbing is available, it will be tried as well to see if it can
381      tighten bounds.
382      This routine is just a front end for tightenVubs(int,const int*,double).
383
384      If <tt>type = -1</tt> all variables are processed (could be very slow).
385      If <tt>type = 0</tt> only variables involved in VUBs are processed.
386      If <tt>type = n > 0</tt>, only the n most expensive VUB variables
387      are processed, where it is assumed that x is at its maximum so delta
388      would have to go to 1 (if x not at bound).
389
390      If \p allowMultipleBinary is true, then a VUB constraint is a row with
391      one continuous variable and any number of binary variables.
392
393      If <tt>useCutoff < 1.0e30</tt>, the original objective is installed as a
394      constraint with \p useCutoff as a bound.
395  */
396  bool tightenVubs(int type,bool allowMultipleBinary=false,
397                   double useCutoff=1.0e50);
398 
399  /** \brief For variables involved in VUB constraints, see if we can tighten
400             bounds by solving lp's
401
402    This version is just handed a list of variables to be processed.
403  */
404  bool tightenVubs(int numberVubs, const int * which,
405                   double useCutoff=1.0e50);
406  /**
407    Analyze problem to find a minimum change in the objective function.
408  */
409  void analyzeObjective();
410
411
412  //@}
413
414  /** \name Object manipulation routines
415 
416    See OsiObject for an explanation of `object' in the context of CbcModel.
417  */
418  //@{
419
420  /// Get the number of objects
421  inline int numberObjects() const { return numberObjects_;}
422  /// Set the number of objects
423  inline void setNumberObjects(int number) 
424  {  numberObjects_=number;}
425
426  /// Get the array of objects
427  inline OsiObject ** objects() const { return object_;}
428
429  /// Get the specified object
430  const inline OsiObject * object(int which) const { return object_[which];}
431  /// Get the specified object
432  inline OsiObject * modifiableObject(int which) const { return object_[which];}
433
434  /// Delete all object information (and just back to integers if true)
435  void deleteObjects(bool findIntegers=true);
436
437  /** Add in object information.
438 
439    Objects are cloned; the owner can delete the originals.
440  */
441  void addObjects(int numberObjects, OsiObject ** objects);
442
443  /** Add in object information.
444 
445    Objects are cloned; the owner can delete the originals.
446  */
447  void addObjects(int numberObjects, CbcObject ** objects);
448
449  /// Ensure attached objects point to this model.
450  void synchronizeModel() ;
451
452  /** \brief Identify integer variables and create corresponding objects.
453 
454    Record integer variables and create an CbcSimpleInteger object for each
455    one.
456    If \p startAgain is true, a new scan is forced, overwriting any existing
457    integer variable information.
458    If type > 0 then 1==PseudoCost
459  */
460
461  void findIntegers(bool startAgain,int type=0);
462
463  //@}
464
465  //---------------------------------------------------------------------------
466
467  /**@name Parameter set/get methods
468
469     The set methods return true if the parameter was set to the given value,
470     false if the value of the parameter is out of range.
471
472     The get methods return the value of the parameter.
473
474  */
475  //@{
476  /// Set an integer parameter
477  inline bool setIntParam(CbcIntParam key, int value) {
478    intParam_[key] = value;
479    return true;
480  }
481  /// Set a double parameter
482  inline bool setDblParam(CbcDblParam key, double value) {
483    dblParam_[key] = value;
484    return true;
485  }
486  /// Get an integer parameter
487  inline int getIntParam(CbcIntParam key) const {
488    return intParam_[key];
489  }
490  /// Get a double parameter
491  inline double getDblParam(CbcDblParam key) const {
492    return dblParam_[key];
493  }
494  /*! \brief Set cutoff bound on the objective function.
495
496    When using strict comparison, the bound is adjusted by a tolerance to
497    avoid accidentally cutting off the optimal solution.
498  */
499  void setCutoff(double value) ;
500
501  /// Get the cutoff bound on the objective function - always as minimize
502  inline double getCutoff() const
503  { //double value ;
504    //solver_->getDblParam(OsiDualObjectiveLimit,value) ;
505    //assert( dblParam_[CbcCurrentCutoff]== value * solver_->getObjSense());
506    return dblParam_[CbcCurrentCutoff];
507  }
508
509  /// Set the \link CbcModel::CbcMaxNumNode maximum node limit \endlink
510  inline bool setMaximumNodes( int value)
511  { return setIntParam(CbcMaxNumNode,value); }
512
513  /// Get the \link CbcModel::CbcMaxNumNode maximum node limit \endlink
514  inline int getMaximumNodes() const
515  { return getIntParam(CbcMaxNumNode); }
516
517  /** Set the
518      \link CbcModel::CbcMaxNumSol maximum number of solutions \endlink
519      desired.
520  */
521  inline bool setMaximumSolutions( int value) {
522    return setIntParam(CbcMaxNumSol,value);
523  }
524  /** Get the
525      \link CbcModel::CbcMaxNumSol maximum number of solutions \endlink
526      desired.
527  */
528  inline int getMaximumSolutions() const {
529    return getIntParam(CbcMaxNumSol);
530  }
531  /// Set the printing mode
532  inline bool setPrintingMode( int value)
533  { return setIntParam(CbcPrinting,value); }
534
535  /// Get the printing mode
536  inline int getPrintingMode() const
537  { return getIntParam(CbcPrinting); }
538
539  /** Set the
540      \link CbcModel::CbcMaximumSeconds maximum number of seconds \endlink
541      desired.
542  */
543  inline bool setMaximumSeconds( double value) {
544    return setDblParam(CbcMaximumSeconds,value);
545  }
546  /** Get the
547      \link CbcModel::CbcMaximumSeconds maximum number of seconds \endlink
548      desired.
549  */
550  inline double getMaximumSeconds() const {
551    return getDblParam(CbcMaximumSeconds);
552  }
553  /// Current time since start of branchAndbound
554  double getCurrentSeconds() const ;
555
556  /** Set the
557    \link CbcModel::CbcIntegerTolerance integrality tolerance \endlink
558  */
559  inline bool setIntegerTolerance( double value) {
560    return setDblParam(CbcIntegerTolerance,value);
561  }
562  /** Get the
563    \link CbcModel::CbcIntegerTolerance integrality tolerance \endlink
564  */
565  inline double getIntegerTolerance() const {
566    return getDblParam(CbcIntegerTolerance);
567  }
568
569  /** Set the
570      \link CbcModel::CbcInfeasibilityWeight
571            weight per integer infeasibility \endlink
572  */
573  inline bool setInfeasibilityWeight( double value) {
574    return setDblParam(CbcInfeasibilityWeight,value);
575  }
576  /** Get the
577      \link CbcModel::CbcInfeasibilityWeight
578            weight per integer infeasibility \endlink
579  */
580  inline double getInfeasibilityWeight() const {
581    return getDblParam(CbcInfeasibilityWeight);
582  }
583
584  /** Set the \link CbcModel::CbcAllowableGap allowable gap \endlink
585      between the best known solution and the best possible solution.
586  */
587  inline bool setAllowableGap( double value) {
588    return setDblParam(CbcAllowableGap,value);
589  }
590  /** Get the \link CbcModel::CbcAllowableGap allowable gap \endlink
591      between the best known solution and the best possible solution.
592  */
593  inline double getAllowableGap() const {
594    return getDblParam(CbcAllowableGap);
595  }
596
597  /** Set the \link CbcModel::CbcAllowableFractionGap fraction allowable gap \endlink
598      between the best known solution and the best possible solution.
599  */
600  inline bool setAllowableFractionGap( double value) {
601    return setDblParam(CbcAllowableFractionGap,value);
602  }
603  /** Get the \link CbcModel::CbcAllowableFractionGap fraction allowable gap \endlink
604      between the best known solution and the best possible solution.
605  */
606  inline double getAllowableFractionGap() const {
607    return getDblParam(CbcAllowableFractionGap);
608  }
609  /** Set the \link CbcModel::CbcAllowableFractionGap percentage allowable gap \endlink
610      between the best known solution and the best possible solution.
611  */
612  inline bool setAllowablePercentageGap( double value) {
613    return setDblParam(CbcAllowableFractionGap,value*0.01);
614  }
615  /** Get the \link CbcModel::CbcAllowableFractionGap percentage allowable gap \endlink
616      between the best known solution and the best possible solution.
617  */
618  inline double getAllowablePercentageGap() const {
619    return 100.0*getDblParam(CbcAllowableFractionGap);
620  }
621  /** Set the
622      \link CbcModel::CbcCutoffIncrement  \endlink
623      desired.
624  */
625  inline bool setCutoffIncrement( double value) {
626    return setDblParam(CbcCutoffIncrement,value);
627  }
628  /** Get the
629      \link CbcModel::CbcCutoffIncrement  \endlink
630      desired.
631  */
632  inline double getCutoffIncrement() const {
633    return getDblParam(CbcCutoffIncrement);
634  }
635
636  /** Pass in target solution and optional priorities.
637      If priorities then >0 means only branch if incorrect
638      while <0 means branch even if correct. +1 or -1 are
639      highest priority */
640  void setHotstartSolution(const double * solution, const int * priorities=NULL) ;
641 
642  /// Set the minimum drop to continue cuts
643  inline void setMinimumDrop(double value)
644  {minimumDrop_=value;}
645  /// Get the minimum drop to continue cuts
646  inline double getMinimumDrop() const
647  { return minimumDrop_;}
648
649  /** Set the maximum number of cut passes at root node (default 20)
650      Minimum drop can also be used for fine tuning */
651  inline void setMaximumCutPassesAtRoot(int value)
652  {maximumCutPassesAtRoot_=value;}
653  /** Get the maximum number of cut passes at root node */
654  inline int getMaximumCutPassesAtRoot() const
655  { return maximumCutPassesAtRoot_;}
656
657  /** Set the maximum number of cut passes at other nodes (default 10)
658      Minimum drop can also be used for fine tuning */
659  inline void setMaximumCutPasses(int value)
660  {maximumCutPasses_=value;}
661  /** Get the maximum number of cut passes at other nodes (default 10) */
662  inline int getMaximumCutPasses() const
663  { return maximumCutPasses_;}
664  /** Get current cut pass number in this round of cuts.
665      (1 is first pass) */
666  inline int getCurrentPassNumber() const
667  { return currentPassNumber_;}
668
669  /** Set the maximum number of candidates to be evaluated for strong
670    branching.
671
672    A value of 0 disables strong branching.
673  */
674  void setNumberStrong(int number);
675  /** Get the maximum number of candidates to be evaluated for strong
676    branching.
677  */
678  inline int numberStrong() const
679  { return numberStrong_;}
680  /** Set global preferred way to branch
681      -1 down, +1 up, 0 no preference */
682  inline void setPreferredWay(int value)
683  {preferredWay_=value;}
684  /** Get the preferred way to branch (default 0) */
685  inline int getPreferredWay() const
686  { return preferredWay_;}
687  /** Set size of mini - tree.  If > 1 then does total enumeration of
688      tree given by this best variables to branch on
689  */
690  inline void setSizeMiniTree(int value)
691  { sizeMiniTree_=value;}
692  inline int sizeMiniTree() const
693  { return sizeMiniTree_;}
694
695  /** Set the number of branches before pseudo costs believed
696      in dynamic strong branching.
697
698    A value of 0 disables dynamic strong branching.
699  */
700  void setNumberBeforeTrust(int number);
701  /** get the number of branches before pseudo costs believed
702      in dynamic strong branching. */
703  inline int numberBeforeTrust() const
704  { return numberBeforeTrust_;}
705  /** Set the number of variables for which to compute penalties
706      in dynamic strong branching.
707
708    A value of 0 disables penalties.
709  */
710  void setNumberPenalties(int number);
711  /** get the number of variables for which to compute penalties
712      in dynamic strong branching. */
713  inline int numberPenalties() const
714  { return numberPenalties_;}
715  /// Number of analyze iterations to do
716  inline void setNumberAnalyzeIterations(int number)
717  { numberAnalyzeIterations_=number;}
718  inline int numberAnalyzeIterations() const
719  { return numberAnalyzeIterations_;}
720  /** Get scale factor to make penalties match strong.
721      Should/will be computed */
722  inline double penaltyScaleFactor() const
723  { return penaltyScaleFactor_;}
724  /** Set scale factor to make penalties match strong.
725      Should/will be computed */
726  void setPenaltyScaleFactor(double value);
727  /** Problem type as set by user or found by analysis.  This will be extended
728      0 - not known
729      1 - Set partitioning <=
730      2 - Set partitioning ==
731      3 - Set covering
732      4 - all +- 1 or all +1 and odd
733  */
734  void inline setProblemType(int number)
735  { problemType_=number;}
736  inline int problemType() const
737  { return problemType_;}
738  /// Current depth
739  inline int currentDepth() const
740  { return currentDepth_;}
741
742  /// Set how often to scan global cuts
743  void setHowOftenGlobalScan(int number);
744  /// Get how often to scan global cuts
745  inline int howOftenGlobalScan() const
746  { return howOftenGlobalScan_;}
747  /// Original columns as created by integerPresolve or preprocessing
748  inline int * originalColumns() const
749  { return originalColumns_;}
750  /// Set original columns as created by preprocessing
751  void setOriginalColumns(const int * originalColumns) ;
752
753  /** Set the print frequency.
754 
755    Controls the number of nodes evaluated between status prints.
756    If <tt>number <=0</tt> the print frequency is set to 100 nodes for large
757    problems, 1000 for small problems.
758    Print frequency has very slight overhead if small.
759  */
760  inline void setPrintFrequency(int number)
761  { printFrequency_=number;}
762  /// Get the print frequency
763  inline int printFrequency() const
764  { return printFrequency_;}
765  //@}
766
767  //---------------------------------------------------------------------------
768  ///@name Methods returning info on how the solution process terminated
769  //@{
770    /// Are there a numerical difficulties?
771    bool isAbandoned() const;
772    /// Is optimality proven?
773    bool isProvenOptimal() const;
774    /// Is  infeasiblity proven (or none better than cutoff)?
775    bool isProvenInfeasible() const;
776    /// Was continuous solution unbounded
777    bool isContinuousUnbounded() const;
778    /// Was continuous solution unbounded
779    bool isProvenDualInfeasible() const;
780    /// Node limit reached?
781    bool isNodeLimitReached() const;
782    /// Time limit reached?
783    bool isSecondsLimitReached() const;
784    /// Solution limit reached?
785    bool isSolutionLimitReached() const;
786    /// Get how many iterations it took to solve the problem.
787    inline int getIterationCount() const
788    { return numberIterations_;}
789    /// Increment how many iterations it took to solve the problem.
790    inline void incrementIterationCount(int value)
791    { numberIterations_ += value;}
792    /// Get how many Nodes it took to solve the problem.
793    inline int getNodeCount() const
794    { return numberNodes_;}
795    /// Increment how many nodes it took to solve the problem.
796    inline void incrementNodeCount(int value)
797    { numberNodes_ += value;}
798    /** Final status of problem
799        Some of these can be found out by is...... functions
800        -1 before branchAndBound
801        0 finished - check isProvenOptimal or isProvenInfeasible to see if solution found
802        (or check value of best solution)
803        1 stopped - on maxnodes, maxsols, maxtime
804        2 difficulties so run was abandoned
805        (5 event user programmed event occurred)
806    */
807    inline int status() const
808    { return status_;}
809    inline void setProblemStatus(int value)
810    { status_=value;}
811    /** Secondary status of problem
812        -1 unset (status_ will also be -1)
813        0 search completed with solution
814        1 linear relaxation not feasible (or worse than cutoff)
815        2 stopped on gap
816        3 stopped on nodes
817        4 stopped on time
818        5 stopped on user event
819        6 stopped on solutions
820        7 linear relaxation unbounded
821    */
822    inline int secondaryStatus() const
823    { return secondaryStatus_;}
824    inline void setSecondaryStatus(int value)
825    { secondaryStatus_=value;}
826    /// Are there numerical difficulties (for initialSolve) ?
827    bool isInitialSolveAbandoned() const ;
828    /// Is optimality proven (for initialSolve) ?
829    bool isInitialSolveProvenOptimal() const ;
830    /// Is primal infeasiblity proven (for initialSolve) ?
831    bool isInitialSolveProvenPrimalInfeasible() const ;
832    /// Is dual infeasiblity proven (for initialSolve) ?
833    bool isInitialSolveProvenDualInfeasible() const ;
834
835  //@}
836
837  //---------------------------------------------------------------------------
838  /**@name Problem information methods
839     
840     These methods call the solver's query routines to return
841     information about the problem referred to by the current object.
842     Querying a problem that has no data associated with it result in
843     zeros for the number of rows and columns, and NULL pointers from
844     the methods that return vectors.
845     
846     Const pointers returned from any data-query method are valid as
847     long as the data is unchanged and the solver is not called.
848  */
849  //@{
850  /// Number of rows in continuous (root) problem.
851  inline int numberRowsAtContinuous() const
852  { return numberRowsAtContinuous_;}
853
854  /// Get number of columns
855  inline int getNumCols() const
856  { return solver_->getNumCols();}
857 
858  /// Get number of rows
859  inline int getNumRows() const
860  { return solver_->getNumRows();}
861 
862  /// Get number of nonzero elements
863  inline CoinBigIndex getNumElements() const
864  { return solver_->getNumElements();}
865
866  /// Number of integers in problem
867  inline int numberIntegers() const
868  { return numberIntegers_;}
869  // Integer variables
870  inline const int * integerVariable() const 
871  { return integerVariable_;}
872  /// Whether or not integer
873  inline char integerType(int i) const
874  { return integerInfo_[i];}
875  /// Whether or not integer
876  inline const char * integerType() const
877  { return integerInfo_;}
878
879  /// Get pointer to array[getNumCols()] of column lower bounds
880  inline const double * getColLower() const
881  { return solver_->getColLower();}
882 
883  /// Get pointer to array[getNumCols()] of column upper bounds
884  inline const double * getColUpper() const
885  { return solver_->getColUpper();}
886 
887  /** Get pointer to array[getNumRows()] of row constraint senses.
888      <ul>
889      <li>'L': <= constraint
890      <li>'E': =  constraint
891      <li>'G': >= constraint
892      <li>'R': ranged constraint
893      <li>'N': free constraint
894      </ul>
895  */
896  inline const char * getRowSense() const
897  { return solver_->getRowSense();}
898 
899  /** Get pointer to array[getNumRows()] of rows right-hand sides
900      <ul>
901      <li> if rowsense()[i] == 'L' then rhs()[i] == rowupper()[i]
902      <li> if rowsense()[i] == 'G' then rhs()[i] == rowlower()[i]
903      <li> if rowsense()[i] == 'R' then rhs()[i] == rowupper()[i]
904      <li> if rowsense()[i] == 'N' then rhs()[i] == 0.0
905      </ul>
906  */
907  inline const double * getRightHandSide() const
908  { return solver_->getRightHandSide();}
909 
910  /** Get pointer to array[getNumRows()] of row ranges.
911      <ul>
912      <li> if rowsense()[i] == 'R' then
913      rowrange()[i] == rowupper()[i] - rowlower()[i]
914      <li> if rowsense()[i] != 'R' then
915      rowrange()[i] is 0.0
916      </ul>
917  */
918  inline const double * getRowRange() const
919  { return solver_->getRowRange();}
920 
921  /// Get pointer to array[getNumRows()] of row lower bounds
922  inline const double * getRowLower() const
923  { return solver_->getRowLower();}
924 
925  /// Get pointer to array[getNumRows()] of row upper bounds
926  inline const double * getRowUpper() const
927  { return solver_->getRowUpper();}
928 
929  /// Get pointer to array[getNumCols()] of objective function coefficients
930  inline const double * getObjCoefficients() const
931  { return solver_->getObjCoefficients();}
932 
933  /// Get objective function sense (1 for min (default), -1 for max)
934  inline double getObjSense() const
935  {
936    //assert (dblParam_[CbcOptimizationDirection]== solver_->getObjSense());
937    return dblParam_[CbcOptimizationDirection];}
938 
939  /// Return true if variable is continuous
940  inline bool isContinuous(int colIndex) const
941  { return solver_->isContinuous(colIndex);}
942 
943  /// Return true if variable is binary
944  inline bool isBinary(int colIndex) const
945  { return solver_->isBinary(colIndex);}
946 
947  /** Return true if column is integer.
948      Note: This function returns true if the the column
949      is binary or a general integer.
950  */
951  inline bool isInteger(int colIndex) const
952  { return solver_->isInteger(colIndex);}
953 
954  /// Return true if variable is general integer
955  inline bool isIntegerNonBinary(int colIndex) const
956  { return solver_->isIntegerNonBinary(colIndex);}
957 
958  /// Return true if variable is binary and not fixed at either bound
959  inline bool isFreeBinary(int colIndex) const
960  { return solver_->isFreeBinary(colIndex) ;}
961 
962  /// Get pointer to row-wise copy of matrix
963  inline const CoinPackedMatrix * getMatrixByRow() const
964  { return solver_->getMatrixByRow();}
965 
966  /// Get pointer to column-wise copy of matrix
967  inline const CoinPackedMatrix * getMatrixByCol() const
968  { return solver_->getMatrixByCol();}
969 
970  /// Get solver's value for infinity
971  inline double getInfinity() const
972  { return solver_->getInfinity();}
973  /// Get pointer to array[getNumCols()] (for speed) of column lower bounds
974  inline const double * getCbcColLower() const
975  { return cbcColLower_;}
976  /// Get pointer to array[getNumCols()] (for speed) of column upper bounds
977  inline const double * getCbcColUpper() const
978  { return cbcColUpper_;}
979  /// Get pointer to array[getNumRows()] (for speed) of row lower bounds
980  inline const double * getCbcRowLower() const
981  { return cbcRowLower_;}
982  /// Get pointer to array[getNumRows()] (for speed) of row upper bounds
983  inline const double * getCbcRowUpper() const
984  { return cbcRowUpper_;}
985  /// Get pointer to array[getNumCols()] (for speed) of primal solution vector
986  inline const double * getCbcColSolution() const
987  { return cbcColSolution_;}
988  /// Get pointer to array[getNumRows()] (for speed) of dual prices
989  inline const double * getCbcRowPrice() const
990  { return cbcRowPrice_;}
991  /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
992  inline const double * getCbcReducedCost() const
993  { return cbcReducedCost_;}
994  /// Get pointer to array[getNumRows()] (for speed) of row activity levels.
995  inline const double * getCbcRowActivity() const
996  { return cbcRowActivity_;}
997  //@}
998 
999 
1000  /**@name Methods related to querying the solution */
1001  //@{
1002  /// Holds solution at continuous (after cuts if branchAndBound called)
1003  inline double * continuousSolution() const
1004  { return continuousSolution_;}
1005  /** Array marked whenever a solution is found if non-zero.
1006      Code marks if heuristic returns better so heuristic
1007      need only mark if it wants to on solutions which
1008      are worse than current */
1009  inline int * usedInSolution() const
1010  { return usedInSolution_;}
1011  /// Increases usedInSolution for nonzeros
1012  void incrementUsed(const double * solution);
1013  /// Record a new incumbent solution and update objectiveValue
1014  void setBestSolution(CBC_Message how,
1015                       double & objectiveValue, const double *solution,
1016                       int fixVariables=0);
1017  /// Just update objectiveValue
1018  void setBestObjectiveValue( double objectiveValue);
1019
1020  /** Call this to really test if a valid solution can be feasible
1021      Solution is number columns in size.
1022      If fixVariables true then bounds of continuous solver updated.
1023      Returns objective value (worse than cutoff if not feasible)
1024      Previously computed objective value is now passed in (in case user does not do solve)
1025 */
1026  double checkSolution(double cutoff, double * solution,
1027                       int fixVariables, double originalObjValue);
1028  /** Test the current solution for feasiblility.
1029
1030    Scan all objects for indications of infeasibility. This is broken down
1031    into simple integer infeasibility (\p numberIntegerInfeasibilities)
1032    and all other reports of infeasibility (\p numberObjectInfeasibilities).
1033  */
1034  bool feasibleSolution(int & numberIntegerInfeasibilities,
1035                        int & numberObjectInfeasibilities) const;
1036
1037  /** Solution to the most recent lp relaxation.
1038
1039    The solver's solution to the most recent lp relaxation.
1040  */
1041   
1042  inline double * currentSolution() const
1043  { return currentSolution_;}
1044  /** For testing infeasibilities - will point to
1045      currentSolution_ or solver-->getColSolution()
1046  */
1047  inline const double * testSolution() const
1048  { return testSolution_;}
1049  inline void setTestSolution(const double * solution)
1050  { testSolution_ = solution;}
1051  /// Make sure region there and optionally copy solution
1052  void reserveCurrentSolution(const double * solution=NULL);
1053
1054  /// Get pointer to array[getNumCols()] of primal solution vector
1055  inline const double * getColSolution() const
1056  { return solver_->getColSolution();}
1057 
1058  /// Get pointer to array[getNumRows()] of dual prices
1059  inline const double * getRowPrice() const
1060  { return solver_->getRowPrice();}
1061 
1062  /// Get a pointer to array[getNumCols()] of reduced costs
1063  inline const double * getReducedCost() const
1064  { return solver_->getReducedCost();}
1065 
1066  /// Get pointer to array[getNumRows()] of row activity levels.
1067  inline const double * getRowActivity() const
1068  { return solver_->getRowActivity();}
1069 
1070  /// Get current objective function value
1071  inline double getCurrentObjValue() const
1072  { return dblParam_[CbcCurrentObjectiveValue]; }
1073  /// Get current minimization objective function value
1074  inline double getCurrentMinimizationObjValue() const
1075  { return dblParam_[CbcCurrentMinimizationObjectiveValue];}
1076 
1077  /// Get best objective function value as minimization
1078  inline double getMinimizationObjValue() const
1079  { return bestObjective_;}
1080  /// Set best objective function value as minimization
1081  inline void setMinimizationObjValue(double value) 
1082  { bestObjective_=value;}
1083 
1084  /// Get best objective function value
1085  inline double getObjValue() const
1086  { return bestObjective_ * solver_->getObjSense() ; } 
1087  /** Get best possible objective function value.
1088      This is better of best possible left on tree
1089      and best solution found.
1090      If called from within branch and cut may be optimistic.
1091  */
1092  double getBestPossibleObjValue() const;
1093  /// Set best objective function value
1094  inline void setObjValue(double value) 
1095  { bestObjective_=value * solver_->getObjSense() ;}
1096 
1097  /** The best solution to the integer programming problem.
1098
1099    The best solution to the integer programming problem found during
1100    the search. If no solution is found, the method returns null.
1101  */
1102
1103  inline double * bestSolution() const
1104  { return bestSolution_;}
1105  /** User callable setBestSolution.
1106      If check false does not check valid
1107      If true then sees if feasible and warns if objective value
1108      worse than given (so just set to COIN_DBL_MAX if you don't care).
1109      If check true then does not save solution if not feasible
1110  */
1111  void setBestSolution(const double * solution,int numberColumns,
1112                       double objectiveValue,bool check=false);
1113 
1114  /// Get number of solutions
1115  inline int getSolutionCount() const
1116  { return numberSolutions_;}
1117 
1118  /// Set number of solutions (so heuristics will be different)
1119  inline void setSolutionCount(int value) 
1120  { numberSolutions_=value;}
1121  /** Current phase (so heuristics etc etc can find out).
1122      0 - initial solve
1123      1 - solve with cuts at root
1124      2 - solve with cuts
1125      3 - other e.g. strong branching
1126      4 - trying to validate a solution
1127      5 - at end of search
1128  */
1129  inline int phase() const
1130  { return phase_;}
1131 
1132  /// Get number of heuristic solutions
1133  inline int getNumberHeuristicSolutions() const { return numberHeuristicSolutions_;}
1134  /// Set number of heuristic solutions
1135  inline void setNumberHeuristicSolutions(int value) { numberHeuristicSolutions_=value;}
1136
1137  /// Set objective function sense (1 for min (default), -1 for max,)
1138  inline void setObjSense(double s) { dblParam_[CbcOptimizationDirection]=s;
1139  solver_->setObjSense(s);}
1140
1141  /// Value of objective at continuous
1142  inline double getContinuousObjective() const
1143  { return originalContinuousObjective_;}
1144  inline void setContinuousObjective(double value)
1145  { originalContinuousObjective_=value;}
1146  /// Number of infeasibilities at continuous
1147  inline int getContinuousInfeasibilities() const
1148  { return continuousInfeasibilities_;}
1149  inline void setContinuousInfeasibilities(int value)
1150  { continuousInfeasibilities_=value;}
1151  /// Value of objective after root node cuts added
1152  inline double rootObjectiveAfterCuts() const
1153  { return continuousObjective_;}
1154  /// Sum of Changes to objective by first solve
1155  inline double sumChangeObjective() const
1156  { return sumChangeObjective1_;}
1157  /** Number of times global cuts violated.  When global cut pool then this
1158      should be kept for each cut and type of cut */
1159  inline int numberGlobalViolations() const
1160  { return numberGlobalViolations_;}
1161  inline void clearNumberGlobalViolations()
1162  { numberGlobalViolations_=0;}
1163  /// Whether to force a resolve after takeOffCuts
1164  inline bool resolveAfterTakeOffCuts() const
1165  { return resolveAfterTakeOffCuts_;}
1166  inline void setResolveAfterTakeOffCuts(bool yesNo)
1167  { resolveAfterTakeOffCuts_=yesNo;}
1168  /// Maximum number of rows
1169  inline int maximumRows() const
1170  { return maximumRows_;}
1171  /// Work basis for temporary use
1172  inline CoinWarmStartBasis & workingBasis()
1173  { return workingBasis_;}
1174  /// Get number of threads
1175  inline int getNumberThreads() const
1176  { return numberThreads_;}
1177  /// Set number of threads
1178  inline void setNumberThreads(int value) 
1179  { numberThreads_=value;}
1180  /// Get thread mode
1181  inline int getThreadMode() const
1182  { return threadMode_;}
1183  /** Set thread mode
1184      always use numberThreads for branching
1185      1 set then use numberThreads in root mini branch and bound
1186      2 set then use numberThreads for root cuts
1187      default is 0
1188  */
1189  inline void setThreadMode(int value) 
1190  { threadMode_=value;}
1191  /// Get number of "iterations" to stop after
1192  inline int getStopNumberIterations() const
1193  { return stopNumberIterations_;}
1194  /// Set number of "iterations" to stop after
1195  inline void setStopNumberIterations(int value) 
1196  { stopNumberIterations_=value;}
1197  //@}
1198
1199  /** \name Node selection */
1200  //@{
1201  // Comparison functions (which may be overridden by inheritance)
1202  inline CbcCompareBase * nodeComparison() const
1203  { return nodeCompare_;}
1204  void setNodeComparison(CbcCompareBase * compare);
1205  void setNodeComparison(CbcCompareBase & compare);
1206  //@}
1207
1208  /** \name Problem feasibility checking */
1209  //@{
1210  // Feasibility functions (which may be overridden by inheritance)
1211  inline CbcFeasibilityBase * problemFeasibility() const
1212  { return problemFeasibility_;}
1213  void setProblemFeasibility(CbcFeasibilityBase * feasibility);
1214  void setProblemFeasibility(CbcFeasibilityBase & feasibility);
1215  //@}
1216
1217  /** \name Tree methods and subtree methods */
1218  //@{
1219  /// Tree method e.g. heap (which may be overridden by inheritance)
1220  inline CbcTree * tree() const
1221  { return tree_;}
1222  /// For modifying tree handling (original is cloned)
1223  void passInTreeHandler(CbcTree & tree);
1224  /** For passing in an CbcModel to do a sub Tree (with derived tree handlers).
1225      Passed in model must exist for duration of branch and bound
1226  */
1227  void passInSubTreeModel(CbcModel & model);
1228  /** For retrieving a copy of subtree model with given OsiSolver.
1229      If no subtree model will use self (up to user to reset cutoff etc).
1230      If solver NULL uses current
1231  */
1232  CbcModel * subTreeModel(OsiSolverInterface * solver=NULL) const;
1233  /// Returns number of times any subtree stopped on nodes, time etc
1234  inline int numberStoppedSubTrees() const
1235  { return numberStoppedSubTrees_;}
1236  /// Says a sub tree was stopped
1237  inline void incrementSubTreeStopped()
1238  { numberStoppedSubTrees_++;}
1239  /** Whether to automatically do presolve before branch and bound (subTrees).
1240      0 - no
1241      1 - ordinary presolve
1242      2 - integer presolve (dodgy)
1243  */
1244  inline int typePresolve() const
1245  { return presolve_;}
1246  inline void setTypePresolve(int value)
1247  { presolve_=value;}
1248 
1249  //@}
1250
1251  /** \name Branching Decisions
1252 
1253    See the CbcBranchDecision class for additional information.
1254  */
1255  //@{
1256
1257  /// Get the current branching decision method.
1258  inline CbcBranchDecision * branchingMethod() const
1259  { return branchingMethod_;}
1260  /// Set the branching decision method.
1261  inline void setBranchingMethod(CbcBranchDecision * method)
1262  { delete branchingMethod_; branchingMethod_ = method->clone();}
1263  /** Set the branching method
1264 
1265    \overload
1266  */
1267  inline void setBranchingMethod(CbcBranchDecision & method)
1268  { delete branchingMethod_; branchingMethod_ = method.clone();}
1269  /// Get the current cut modifier method
1270  inline CbcCutModifier * cutModifier() const
1271  { return cutModifier_;}
1272  /// Set the cut modifier method
1273  void setCutModifier(CbcCutModifier * modifier);
1274  /** Set the cut modifier method
1275 
1276    \overload
1277  */
1278  void setCutModifier(CbcCutModifier & modifier);
1279  //@}
1280
1281  /** \name Row (constraint) and Column (variable) cut generation */
1282  //@{
1283
1284  /** State of search
1285      0 - no solution
1286      1 - only heuristic solutions
1287      2 - branched to a solution
1288      3 - no solution but many nodes
1289  */
1290  inline int stateOfSearch() const
1291  { return stateOfSearch_;}
1292  inline void setStateOfSearch(int state)
1293  { stateOfSearch_=state;}
1294  /// Strategy worked out - mainly at root node for use by CbcNode
1295  inline int searchStrategy() const
1296  { return searchStrategy_;}
1297  /// Set strategy worked out - mainly at root node for use by CbcNode
1298  inline void setSearchStrategy(int value)
1299  { searchStrategy_ = value; }
1300
1301  /// Get the number of cut generators
1302  inline int numberCutGenerators() const
1303  { return numberCutGenerators_;}
1304  /// Get the list of cut generators
1305  inline CbcCutGenerator ** cutGenerators() const
1306  { return generator_;}
1307  ///Get the specified cut generator
1308  inline CbcCutGenerator * cutGenerator(int i) const
1309  { return generator_[i];}
1310  ///Get the specified cut generator before any changes
1311  inline CbcCutGenerator * virginCutGenerator(int i) const
1312  { return virginGenerator_[i];}
1313  /** Add one generator - up to user to delete generators.
1314      howoften affects how generator is used. 0 or 1 means always,
1315      >1 means every that number of nodes.  Negative values have same
1316      meaning as positive but they may be switched off (-> -100) by code if
1317      not many cuts generated at continuous.  -99 is just done at root.
1318      Name is just for printout.
1319      If depth >0 overrides how often generator is called (if howOften==-1 or >0).
1320  */
1321  void addCutGenerator(CglCutGenerator * generator,
1322                       int howOften=1, const char * name=NULL,
1323                       bool normal=true, bool atSolution=false, 
1324                       bool infeasible=false,int howOftenInSub=-100,
1325                       int whatDepth=-1, int whatDepthInSub=-1);
1326//@}
1327  /** \name Strategy and sub models
1328 
1329    See the CbcStrategy class for additional information.
1330  */
1331  //@{
1332
1333  /// Get the current strategy
1334  inline CbcStrategy * strategy() const
1335  { return strategy_;}
1336  /// Set the strategy. Clones
1337  void setStrategy(CbcStrategy & strategy);
1338  /// Get the current parent model
1339  inline CbcModel * parentModel() const
1340  { return parentModel_;}
1341  /// Set the parent model
1342  inline void setParentModel(CbcModel & parentModel)
1343  { parentModel_ = &parentModel;}
1344  //@}
1345
1346
1347  /** \name Heuristics and priorities */
1348  //@{
1349  /*! \brief Add one heuristic - up to user to delete
1350
1351    The name is just used for print messages.
1352  */
1353  void addHeuristic(CbcHeuristic * generator, const char *name = NULL,
1354                    int before=-1);
1355  ///Get the specified heuristic
1356  inline CbcHeuristic * heuristic(int i) const
1357  { return heuristic_[i];}
1358  /// Get the number of heuristics
1359  inline int numberHeuristics() const
1360  { return numberHeuristics_;}
1361  /// Pointer to heuristic solver which found last solution (or NULL)
1362  inline CbcHeuristic * lastHeuristic() const
1363  { return lastHeuristic_;}
1364  /// set last heuristic which found a solution
1365  inline void setLastHeuristic(CbcHeuristic * last)
1366  { lastHeuristic_=last;}
1367
1368  /** Pass in branching priorities.
1369 
1370      If ifClique then priorities are on cliques otherwise priorities are
1371      on integer variables. 
1372      Other type (if exists set to default)
1373      1 is highest priority. (well actually -INT_MAX is but that's ugly)
1374      If hotstart > 0 then branches are created to force
1375      the variable to the value given by best solution.  This enables a
1376      sort of hot start.  The node choice should be greatest depth
1377      and hotstart should normally be switched off after a solution.
1378
1379      If ifNotSimpleIntegers true then appended to normal integers
1380
1381      This is now deprecated except for simple usage.  If user
1382      creates Cbcobjects then set priority in them
1383
1384      \internal Added for Kurt Spielberg.
1385  */
1386  void passInPriorities(const int * priorities, bool ifNotSimpleIntegers);
1387
1388  /// Returns priority level for an object (or 1000 if no priorities exist)
1389  inline int priority(int sequence) const
1390  { return object_[sequence]->priority();}
1391
1392  /*! \brief Set an event handler
1393 
1394    A clone of the handler passed as a parameter is stored in CbcModel.
1395  */
1396  void passInEventHandler(const CbcEventHandler *eventHandler) ;
1397
1398  /*! \brief Retrieve a pointer to the event handler */
1399  inline CbcEventHandler* getEventHandler() const
1400  { return (eventHandler_) ; } 
1401
1402  //@}
1403   
1404  /**@name Setting/Accessing application data */
1405  //@{
1406    /** Set application data.
1407
1408        This is a pointer that the application can store into and
1409        retrieve from the solver interface.
1410        This field is available for the application to optionally
1411        define and use.
1412    */
1413    void setApplicationData (void * appData);
1414
1415    /// Get application data
1416    void * getApplicationData() const;
1417  /**
1418      For advanced applications you may wish to modify the behavior of Cbc
1419      e.g. if the solver is a NLP solver then you may not have an exact
1420      optimum solution at each step.  Information could be built into
1421      OsiSolverInterface but this is an alternative so that that interface
1422      does not have to be changed.  If something similar is useful to
1423      enough solvers then it could be migrated
1424      You can also pass in by using solver->setAuxiliaryInfo.
1425      You should do that if solver is odd - if solver is normal simplex
1426      then use this.
1427      NOTE - characteristics are not cloned
1428  */
1429  void passInSolverCharacteristics(OsiBabSolver * solverCharacteristics);
1430  /// Get solver characteristics
1431  inline const OsiBabSolver * solverCharacteristics() const
1432  { return solverCharacteristics_;}
1433  //@}
1434 
1435  //---------------------------------------------------------------------------
1436
1437  /**@name Message handling */
1438  //@{
1439  /// Pass in Message handler (not deleted at end)
1440  void passInMessageHandler(CoinMessageHandler * handler);
1441  /// Set language
1442  void newLanguage(CoinMessages::Language language);
1443  inline void setLanguage(CoinMessages::Language language)
1444  {newLanguage(language);}
1445  /// Return handler
1446  inline CoinMessageHandler * messageHandler() const
1447  {return handler_;}
1448  /// Return messages
1449  inline CoinMessages & messages() 
1450  {return messages_;}
1451  /// Return pointer to messages
1452  inline CoinMessages * messagesPointer() 
1453  {return &messages_;}
1454  /// Set log level
1455  void setLogLevel(int value);
1456  /// Get log level
1457  inline int logLevel() const
1458  { return handler_->logLevel();}
1459  //@}
1460  //---------------------------------------------------------------------------
1461  ///@name Specialized
1462  //@{
1463
1464  /**
1465      Set special options
1466      0 bit (1) - check if cuts valid (if on debugger list)
1467      1 bit (2) - use current basis to check integer solution (rather than all slack)
1468      2 bit (4) - don't check integer solution (by solving LP)
1469      3 bit (8) - fast analyze
1470      4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
1471      5 bit (32) - keep names
1472      6 bit (64) - try for dominated columns
1473      7 bit (128) - SOS type 1 but all declared integer
1474      8 bit (256) - Set to say solution just found, unset by doing cuts
1475      9 bit (512) - Try reduced model after 100 nodes
1476      10 bit (1024) - Switch on some heuristics even if seems unlikely
1477  */
1478  /// Set special options
1479  inline void setSpecialOptions(int value)
1480  { specialOptions_=value;}
1481  /// Get special options
1482  inline int specialOptions() const
1483  { return specialOptions_;}
1484  /// Says if normal solver i.e. has well defined CoinPackedMatrix
1485  inline bool normalSolver() const
1486  { return (specialOptions_&16)==0;}
1487  /// Now we may not own objects - just point to solver's objects
1488  inline bool ownObjects() const
1489  { return ownObjects_;}
1490  /// Pointer to a mutex
1491  inline void * mutex()
1492  { return mutex_;}
1493  /// Split up nodes
1494  int splitModel(int numberModels, CbcModel ** model,
1495                  int numberNodes);
1496  /// Start threads
1497  void startSplitModel(int numberIterations);
1498  /// Merge models
1499  void mergeModels(int numberModel, CbcModel ** model,
1500                   int numberNodes);
1501  //@}
1502  //---------------------------------------------------------------------------
1503
1504  ///@name Constructors and destructors etc
1505  //@{
1506    /// Default Constructor
1507    CbcModel(); 
1508   
1509    /// Constructor from solver
1510    CbcModel(const OsiSolverInterface &);
1511 
1512    /** Assign a solver to the model (model assumes ownership)
1513
1514      On return, \p solver will be NULL.
1515      If deleteSolver then current solver deleted (if model owned)
1516
1517      \note Parameter settings in the outgoing solver are not inherited by
1518            the incoming solver.
1519    */
1520    void assignSolver(OsiSolverInterface *&solver,bool deleteSolver=true);
1521
1522    /** \brief Set ownership of solver
1523
1524      A parameter of false tells CbcModel it does not own the solver and
1525      should not delete it. Once you claim ownership of the solver, you're
1526      responsible for eventually deleting it. Note that CbcModel clones
1527      solvers with abandon.  Unless you have a deep understanding of the
1528      workings of CbcModel, the only time you want to claim ownership is when
1529      you're about to delete the CbcModel object but want the solver to
1530      continue to exist (as, for example, when branchAndBound has finished
1531      and you want to hang on to the answer).
1532    */
1533    inline void setModelOwnsSolver (bool ourSolver)
1534  { ownership_ = ourSolver ? (ownership_ |0x80000000) : (ownership_ & (~0x80000000)) ; } 
1535
1536    /*! \brief Get ownership of solver
1537   
1538      A return value of true means that CbcModel owns the solver and will
1539      take responsibility for deleting it when that becomes necessary.
1540    */
1541  inline bool modelOwnsSolver () { return ((ownership_&0x80000000)!=0) ; } 
1542 
1543    /** Copy constructor .
1544      If noTree is true then tree and cuts are not copied
1545    */ 
1546    CbcModel(const CbcModel & rhs, bool noTree=false);
1547 
1548    /// Assignment operator
1549    CbcModel & operator=(const CbcModel& rhs);
1550 
1551    /// Destructor
1552     ~CbcModel ();
1553
1554    /// Returns solver - has current state
1555    inline OsiSolverInterface * solver() const
1556    { return solver_;}
1557
1558    /// Returns current solver - sets new one
1559    inline OsiSolverInterface * swapSolver(OsiSolverInterface * solver) 
1560    { OsiSolverInterface * returnSolver = solver_; solver_ = solver; return returnSolver;}
1561
1562    /// Returns solver with continuous state
1563    inline OsiSolverInterface * continuousSolver() const
1564    { return continuousSolver_;}
1565
1566    /// Create solver with continuous state
1567    inline void createContinuousSolver()
1568    { continuousSolver_ = solver_->clone();}
1569    /// Clear solver with continuous state
1570    inline void clearContinuousSolver()
1571    { delete continuousSolver_; continuousSolver_ = NULL;}
1572
1573  /// A copy of the solver, taken at constructor or by saveReferenceSolver
1574  inline OsiSolverInterface * referenceSolver() const
1575  { return referenceSolver_;}
1576
1577  /// Save a copy of the current solver so can be reset to
1578  void saveReferenceSolver();
1579
1580  /** Uses a copy of reference solver to be current solver.
1581      Because of possible mismatches all exotic integer information is loat
1582      (apart from normal information in OsiSolverInterface)
1583      so SOS etc and priorities will have to be redone
1584  */
1585  void resetToReferenceSolver();
1586
1587  /// Clears out as much as possible (except solver)
1588  void gutsOfDestructor();
1589  /** Clears out enough to reset CbcModel as if no branch and bound done
1590   */
1591  void gutsOfDestructor2();
1592  /** Clears out enough to reset CbcModel cutoff etc
1593   */
1594  void resetModel();
1595  /** Most of copy constructor
1596      mode - 0 copy but don't delete before
1597             1 copy and delete before
1598             2 copy and delete before (but use virgin generators)
1599  */
1600  void gutsOfCopy(const CbcModel & rhs,int mode=0);
1601  /// Move status, nodes etc etc across
1602  void moveInfo(const CbcModel & rhs);
1603  //@}
1604
1605  ///@semi-private i.e. users should not use
1606  //@{
1607    /// Get how many Nodes it took to solve the problem.
1608    int getNodeCount2() const
1609    { return numberNodes2_;}
1610  /// Set pointers for speed
1611  void setPointers(const OsiSolverInterface * solver);
1612  /** Perform reduced cost fixing
1613
1614    Fixes integer variables at their current value based on reduced cost
1615    penalties.  Returns number fixed
1616  */
1617  int reducedCostFix() ;
1618  /// Encapsulates solver resolve
1619  int resolve(OsiSolverInterface * solver);
1620
1621  /** Encapsulates choosing a variable -
1622      anyAction -2, infeasible (-1 round again), 0 done
1623  */
1624  int chooseBranch(CbcNode * newNode, int numberPassesLeft,
1625                   CbcNode * oldNode, OsiCuts & cuts,
1626                   bool & resolved, CoinWarmStartBasis *lastws,
1627                   const double * lowerBefore,const double * upperBefore,
1628                   OsiSolverBranch * & branches);
1629  int chooseBranch(CbcNode * newNode, int numberPassesLeft, bool & resolved);
1630
1631  /** Return an empty basis object of the specified size
1632
1633    A useful utility when constructing a basis for a subproblem from scratch.
1634    The object returned will be of the requested capacity and appropriate for
1635    the solver attached to the model.
1636  */
1637  CoinWarmStartBasis *getEmptyBasis(int ns = 0, int na = 0) const ;
1638
1639  /** Remove inactive cuts from the model
1640
1641    An OsiSolverInterface is expected to maintain a valid basis, but not a
1642    valid solution, when loose cuts are deleted. Restoring a valid solution
1643    requires calling the solver to reoptimise. If it's certain the solution
1644    will not be required, set allowResolve to false to suppress
1645    reoptimisation.
1646    If saveCuts then slack cuts will be saved
1647    On input current cuts are cuts and newCuts
1648    on exit current cuts will be correct
1649  */
1650  void takeOffCuts(OsiCuts &cuts, 
1651                   bool allowResolve,OsiCuts * saveCuts,
1652                   int numberNewCuts=0, const OsiRowCut ** newCuts=NULL) ;
1653
1654  /** Determine and install the active cuts that need to be added for
1655    the current subproblem
1656
1657    The whole truth is a bit more complicated. The first action is a call to
1658    addCuts1(). addCuts() then sorts through the list, installs the tight
1659    cuts in the model, and does bookkeeping (adjusts reference counts).
1660    The basis returned from addCuts1() is adjusted accordingly.
1661   
1662    If it turns out that the node should really be fathomed by bound,
1663    addCuts() simply treats all the cuts as loose as it does the bookkeeping.
1664
1665    canFix true if extra information being passed
1666  */
1667  int addCuts(CbcNode * node, CoinWarmStartBasis *&lastws,bool canFix);
1668
1669  /** Traverse the tree from node to root and prep the model
1670
1671    addCuts1() begins the job of prepping the model to match the current
1672    subproblem. The model is stripped of all cuts, and the search tree is
1673    traversed from node to root to determine the changes required. Appropriate
1674    bounds changes are installed, a list of cuts is collected but not
1675    installed, and an appropriate basis (minus the cuts, but big enough to
1676    accommodate them) is constructed.
1677
1678    \todo addCuts1() is called in contexts where it's known in advance that
1679          all that's desired is to determine a list of cuts and do the
1680          bookkeeping (adjust the reference counts). The work of installing
1681          bounds and building a basis goes to waste.
1682  */
1683  void addCuts1(CbcNode * node, CoinWarmStartBasis *&lastws);
1684  /** Returns bounds just before where - initially original bounds.
1685      Also sets downstream nodes (lower if force 1, upper if 2)
1686  */
1687  void previousBounds (CbcNode * node, CbcNodeInfo * where,int iColumn,
1688                       double & lower, double & upper,int force);
1689  /** Set objective value in a node.  This is separated out so that
1690     odd solvers can use.  It may look at extra information in
1691     solverCharacteriscs_ and will also use bound from parent node
1692  */
1693  void setObjectiveValue(CbcNode * thisNode, const CbcNode * parentNode) const;
1694
1695  /** If numberBeforeTrust >0 then we are going to use CbcBranchDynamic.
1696      Scan and convert CbcSimpleInteger objects
1697  */
1698  void convertToDynamic();
1699  /// Set numberBeforeTrust in all objects
1700  void synchronizeNumberBeforeTrust();
1701  /// Zap integer information in problem (may leave object info)
1702  void zapIntegerInformation(bool leaveObjects=true);
1703  /// Use cliques for pseudocost information - return nonzero if infeasible
1704  int cliquePseudoCosts(int doStatistics);
1705  /// Fill in useful estimates
1706  void pseudoShadow(double * down, double * up);
1707  /** Return pseudo costs
1708      If not all integers or not pseudo costs - returns all zero
1709      Length of arrays are numberIntegers() and entries
1710      correspond to integerVariable()[i]
1711      User must allocate arrays before call
1712  */
1713  void fillPseudoCosts(double * downCosts, double * upCosts,
1714                       int * numberDown=NULL, int * numberUp=NULL,
1715                       int * numberDownInfeasible=NULL,
1716                       int * numberUpInfeasible=NULL) const;
1717  /** Do heuristics at root.
1718      0 - don't delete
1719      1 - delete
1720      2 - just delete - don't even use
1721  */
1722  void doHeuristicsAtRoot(int deleteHeuristicsAfterwards=0);
1723  /// Get the hotstart solution
1724  inline const double * hotstartSolution() const
1725  { return hotstartSolution_;}
1726  /// Get the hotstart priorities
1727  inline const int * hotstartPriorities() const
1728  { return hotstartPriorities_;}
1729
1730  /// Return the list of cuts initially collected for this subproblem
1731  inline CbcCountRowCut ** addedCuts() const
1732  { return addedCuts_;}
1733  /// Number of entries in the list returned by #addedCuts()
1734  inline int currentNumberCuts() const
1735  { return currentNumberCuts_;}
1736  /// Global cuts
1737  inline OsiCuts * globalCuts() 
1738  { return &globalCuts_;}
1739  /// Copy and set a pointer to a row cut which will be added instead of normal branching.
1740  void setNextRowCut(const OsiRowCut & cut);
1741  /// Get a pointer to current node (be careful)
1742  inline CbcNode * currentNode() const
1743  { return currentNode_;}
1744  /// Get a pointer to probing info
1745  inline CglTreeProbingInfo * probingInfo() const
1746  { return probingInfo_;}
1747  /// Set the number of iterations done in strong branching.
1748  inline void setNumberStrongIterations(int number)
1749  { numberStrongIterations_ = number;}
1750  /// Get the number of iterations done in strong branching.
1751  inline int numberStrongIterations() const
1752  { return numberStrongIterations_;}
1753# ifdef COIN_HAS_CLP
1754  /// Set depth for fast nodes
1755  inline void setFastNodeDepth(int value) 
1756  { fastNodeDepth_ = value;}
1757  /// Get depth for fast nodes
1758  inline int fastNodeDepth() const
1759  { return fastNodeDepth_;}
1760  inline void incrementExtra(int nodes, int iterations)
1761  { numberExtraNodes_ += nodes; numberExtraIterations_ += iterations;}
1762#endif
1763  /// Increment strong info
1764  void incrementStrongInfo(int numberTimes, int numberIterations,
1765                           int numberFixed, bool ifInfeasible);
1766  /// Says whether all dynamic integers
1767  inline bool allDynamic () const { return ((ownership_&0x40000000)!=0) ; } 
1768  /// Create C++ lines to get to current state
1769  void generateCpp( FILE * fp,int options);
1770  /// Generate an OsiBranchingInformation object
1771  OsiBranchingInformation usefulInformation() const;
1772  /** Warm start object produced by heuristic or strong branching
1773
1774      If get a valid integer solution outside branch and bound then it can take
1775      a reasonable time to solve LP which produces clean solution.  If this object has
1776      any size then it will be used in solve.
1777  */
1778  inline void setBestSolutionBasis(const CoinWarmStartBasis & bestSolutionBasis)
1779  { bestSolutionBasis_ = bestSolutionBasis;}
1780  //@}
1781
1782//---------------------------------------------------------------------------
1783
1784private:
1785  ///@name Private member data
1786  //@{
1787
1788  /// The solver associated with this model.
1789  OsiSolverInterface * solver_;
1790
1791  /** Ownership of objects and other stuff
1792
1793      0x80000000 model owns solver
1794      0x40000000 all variables CbcDynamicPseudoCost
1795  */
1796  unsigned int ownership_ ;
1797
1798  /// A copy of the solver, taken at the continuous (root) node.
1799  OsiSolverInterface * continuousSolver_;
1800
1801  /// A copy of the solver, taken at constructor or by saveReferenceSolver
1802  OsiSolverInterface * referenceSolver_;
1803
1804   /// Message handler
1805  CoinMessageHandler * handler_;
1806
1807  /** Flag to say if handler_ is the default handler.
1808 
1809    The default handler is deleted when the model is deleted. Other
1810    handlers (supplied by the client) will not be deleted.
1811  */
1812  bool defaultHandler_;
1813
1814  /// Cbc messages
1815  CoinMessages messages_;
1816
1817  /// Array for integer parameters
1818  int intParam_[CbcLastIntParam];
1819
1820  /// Array for double parameters
1821  double dblParam_[CbcLastDblParam];
1822
1823  /** Pointer to an empty warm start object
1824
1825    It turns out to be useful to have this available as a base from
1826    which to build custom warm start objects. This is typed as CoinWarmStart
1827    rather than CoinWarmStartBasis to allow for the possibility that a
1828    client might want to apply a solver that doesn't use a basis-based warm
1829    start. See getEmptyBasis for an example of how this field can be used.
1830  */
1831  mutable CoinWarmStart *emptyWarmStart_ ;
1832
1833  /// Best objective
1834  double bestObjective_;
1835  /// Best possible objective
1836  double bestPossibleObjective_;
1837  /// Sum of Changes to objective by first solve
1838  double sumChangeObjective1_;
1839  /// Sum of Changes to objective by subsequent solves
1840  double sumChangeObjective2_;
1841
1842  /// Array holding the incumbent (best) solution.
1843  double * bestSolution_;
1844
1845  /** Array holding the current solution.
1846
1847    This array is used more as a temporary.
1848  */
1849  double * currentSolution_;
1850  /** For testing infeasibilities - will point to
1851      currentSolution_ or solver-->getColSolution()
1852  */
1853  mutable const double * testSolution_;
1854  /** Warm start object produced by heuristic or strong branching
1855
1856      If get a valid integer solution outside branch and bound then it can take
1857      a reasonable time to solve LP which produces clean solution.  If this object has
1858      any size then it will be used in solve.
1859  */
1860  CoinWarmStartBasis bestSolutionBasis_ ;
1861  /// Global cuts
1862  OsiCuts globalCuts_;
1863
1864  /// Minimum degradation in objective value to continue cut generation
1865  double minimumDrop_;
1866  /// Number of solutions
1867  int numberSolutions_;
1868  /** State of search
1869      0 - no solution
1870      1 - only heuristic solutions
1871      2 - branched to a solution
1872      3 - no solution but many nodes
1873  */
1874  int stateOfSearch_;
1875  /// Hotstart solution
1876  double * hotstartSolution_;
1877  /// Hotstart priorities
1878  int * hotstartPriorities_;
1879  /// Number of heuristic solutions
1880  int numberHeuristicSolutions_;
1881  /// Cumulative number of nodes
1882  int numberNodes_;
1883  /** Cumulative number of nodes for statistics.
1884      Must fix to match up
1885  */
1886  int numberNodes2_;
1887  /// Cumulative number of iterations
1888  int numberIterations_;
1889  /// Status of problem - 0 finished, 1 stopped, 2 difficulties
1890  int status_;
1891  /** Secondary status of problem
1892      -1 unset (status_ will also be -1)
1893      0 search completed with solution
1894      1 linear relaxation not feasible (or worse than cutoff)
1895      2 stopped on gap
1896      3 stopped on nodes
1897      4 stopped on time
1898      5 stopped on user event
1899      6 stopped on solutions
1900   */
1901  int secondaryStatus_;
1902  /// Number of integers in problem
1903  int numberIntegers_;
1904  /// Number of rows at continuous
1905  int numberRowsAtContinuous_;
1906  /// Maximum number of cuts
1907  int maximumNumberCuts_;
1908  /** Current phase (so heuristics etc etc can find out).
1909      0 - initial solve
1910      1 - solve with cuts at root
1911      2 - solve with cuts
1912      3 - other e.g. strong branching
1913      4 - trying to validate a solution
1914      5 - at end of search
1915  */
1916  int phase_;
1917
1918  /// Number of entries in #addedCuts_
1919  int currentNumberCuts_;
1920
1921  /** Current limit on search tree depth
1922
1923    The allocated size of #walkback_. Increased as needed.
1924  */
1925  int maximumDepth_;
1926  /** Array used to assemble the path between a node and the search tree root
1927
1928    The array is resized when necessary. #maximumDepth_  is the current
1929    allocated size.
1930  */
1931  CbcNodeInfo ** walkback_;
1932
1933  /** The list of cuts initially collected for this subproblem
1934
1935    When the subproblem at this node is rebuilt, a set of cuts is collected
1936    for inclusion in the constraint system. If any of these cuts are
1937    subsequently removed because they have become loose, the corresponding
1938    entry is set to NULL.
1939  */
1940  CbcCountRowCut ** addedCuts_;
1941
1942  /** A pointer to a row cut which will be added instead of normal branching.
1943      After use it should be set to NULL.
1944  */
1945  OsiRowCut * nextRowCut_;
1946
1947  /// Current node so can be used elsewhere
1948  CbcNode * currentNode_;
1949
1950  /// Indices of integer variables
1951  int * integerVariable_;
1952  /// Whether of not integer
1953  char * integerInfo_;
1954  /// Holds solution at continuous (after cuts)
1955  double * continuousSolution_;
1956  /// Array marked whenever a solution is found if non-zero
1957  int * usedInSolution_;
1958  /**
1959      0 bit (1) - check if cuts valid (if on debugger list)
1960      1 bit (2) - use current basis to check integer solution (rather than all slack)
1961      2 bit (4) - don't check integer solution
1962      3 bit (8) - Strong is doing well - keep on
1963  */
1964  int specialOptions_;
1965  /// User node comparison function
1966  CbcCompareBase * nodeCompare_;
1967  /// User feasibility function (see CbcFeasibleBase.hpp)
1968  CbcFeasibilityBase * problemFeasibility_;
1969  /// Tree
1970  CbcTree * tree_;
1971  /// A pointer to model to be used for subtrees
1972  CbcModel * subTreeModel_;
1973  /// Number of times any subtree stopped on nodes, time etc
1974  int numberStoppedSubTrees_;
1975  /// Variable selection function
1976  CbcBranchDecision * branchingMethod_;
1977  /// Cut modifier function
1978  CbcCutModifier * cutModifier_;
1979  /// Strategy
1980  CbcStrategy * strategy_;
1981  /// Parent model
1982  CbcModel * parentModel_;
1983  /** Whether to automatically do presolve before branch and bound.
1984      0 - no
1985      1 - ordinary presolve
1986      2 - integer presolve (dodgy)
1987  */
1988  /// Pointer to array[getNumCols()] (for speed) of column lower bounds
1989  const double * cbcColLower_;
1990  /// Pointer to array[getNumCols()] (for speed) of column upper bounds
1991  const double * cbcColUpper_;
1992  /// Pointer to array[getNumRows()] (for speed) of row lower bounds
1993  const double * cbcRowLower_;
1994  /// Pointer to array[getNumRows()] (for speed) of row upper bounds
1995  const double * cbcRowUpper_;
1996  /// Pointer to array[getNumCols()] (for speed) of primal solution vector
1997  const double * cbcColSolution_;
1998  /// Pointer to array[getNumRows()] (for speed) of dual prices
1999  const double * cbcRowPrice_;
2000  /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
2001  const double * cbcReducedCost_;
2002  /// Pointer to array[getNumRows()] (for speed) of row activity levels.
2003  const double * cbcRowActivity_;
2004  /// Pointer to user-defined data structure
2005  void * appData_;
2006  /// Pointer to a mutex
2007  void * mutex_;
2008  /// Presolve for CbcTreeLocal
2009  int presolve_;
2010  /** Maximum number of candidates to consider for strong branching.
2011    To disable strong branching, set this to 0.
2012  */
2013  int numberStrong_;
2014  /** \brief The number of branches before pseudo costs believed
2015             in dynamic strong branching.
2016     
2017    A value of 0 is  off.
2018  */
2019  int numberBeforeTrust_;
2020  /** \brief The number of variables for which to compute penalties
2021             in dynamic strong branching.
2022  */
2023  int numberPenalties_;
2024  /// For threads - stop after this many "iterations"
2025  int stopNumberIterations_;
2026  /** Scale factor to make penalties match strong.
2027      Should/will be computed */
2028  double penaltyScaleFactor_;
2029  /// Number of analyze iterations to do
2030  int numberAnalyzeIterations_;
2031  /// Arrays with analysis results
2032  double * analyzeResults_;
2033  /// Number of nodes infeasible by normal branching (before cuts)
2034  int numberInfeasibleNodes_;
2035  /** Problem type as set by user or found by analysis.  This will be extended
2036      0 - not known
2037      1 - Set partitioning <=
2038      2 - Set partitioning ==
2039      3 - Set covering
2040  */
2041  int problemType_;
2042  /// Print frequency
2043  int printFrequency_;
2044  /// Number of cut generators
2045  int numberCutGenerators_;
2046  // Cut generators
2047  CbcCutGenerator ** generator_;
2048  // Cut generators before any changes
2049  CbcCutGenerator ** virginGenerator_;
2050  /// Number of heuristics
2051  int numberHeuristics_;
2052  /// Heuristic solvers
2053  CbcHeuristic ** heuristic_;
2054  /// Pointer to heuristic solver which found last solution (or NULL)
2055  CbcHeuristic * lastHeuristic_;
2056# ifdef COIN_HAS_CLP
2057  /// Depth for fast nodes
2058  int fastNodeDepth_;
2059#endif
2060  /*! Pointer to the event handler */
2061# ifdef CBC_ONLY_CLP
2062  ClpEventHandler *eventHandler_ ;
2063# else
2064  CbcEventHandler *eventHandler_ ;
2065# endif
2066
2067  /// Total number of objects
2068  int numberObjects_;
2069
2070  /** \brief Integer and Clique and ... information
2071
2072    \note The code assumes that the first objects on the list will be
2073          SimpleInteger objects for each integer variable, followed by
2074          Clique objects. Portions of the code that understand Clique objects
2075          will fail if they do not immediately follow the SimpleIntegers.
2076          Large chunks of the code will fail if the first objects are not
2077          SimpleInteger. As of 2003.08, SimpleIntegers and Cliques are the only
2078          objects.
2079  */
2080  OsiObject ** object_;
2081  /// Now we may not own objects - just point to solver's objects
2082  bool ownObjects_;
2083 
2084  /// Original columns as created by integerPresolve or preprocessing
2085  int * originalColumns_;
2086  /// How often to scan global cuts
2087  int howOftenGlobalScan_;
2088  /** Number of times global cuts violated.  When global cut pool then this
2089      should be kept for each cut and type of cut */
2090  int numberGlobalViolations_;
2091  /// Number of extra iterations in fast lp
2092  int numberExtraIterations_;
2093  /// Number of extra nodes in fast lp
2094  int numberExtraNodes_;
2095  /** Value of objective at continuous
2096      (Well actually after initial round of cuts)
2097  */
2098  double continuousObjective_;
2099  /** Value of objective before root node cuts added
2100  */
2101  double originalContinuousObjective_;
2102  /// Number of infeasibilities at continuous
2103  int continuousInfeasibilities_;
2104  /// Maximum number of cut passes at root
2105  int maximumCutPassesAtRoot_;
2106  /// Maximum number of cut passes
2107  int maximumCutPasses_;
2108  /// Preferred way of branching
2109  int preferredWay_;
2110  /// Current cut pass number
2111  int currentPassNumber_;
2112  /// Maximum number of cuts (for whichGenerator_)
2113  int maximumWhich_;
2114  /// Maximum number of rows
2115  int maximumRows_;
2116  /// Current depth
2117  int currentDepth_;
2118  /// Work basis for temporary use
2119  CoinWarmStartBasis workingBasis_;
2120  /// Which cut generator generated this cut
2121  int * whichGenerator_;
2122  /// Maximum number of statistics
2123  int maximumStatistics_;
2124  /// statistics
2125  CbcStatistics ** statistics_;
2126  /// Maximum depth reached
2127  int maximumDepthActual_;
2128  /// Number of reduced cost fixings
2129  double numberDJFixed_;
2130  /// Probing info
2131  CglTreeProbingInfo * probingInfo_;
2132  /// Number of fixed by analyze at root
2133  int numberFixedAtRoot_;
2134  /// Number fixed by analyze so far
2135  int numberFixedNow_;
2136  /// Whether stopping on gap
2137  bool stoppedOnGap_;
2138  /// Whether event happened
2139  bool eventHappened_;
2140  /// Number of long strong goes
2141  int numberLongStrong_;
2142  /// Number of old active cuts
2143  int numberOldActiveCuts_;
2144  /// Number of new cuts
2145  int numberNewCuts_;
2146  /// Size of mini - tree
2147  int sizeMiniTree_;
2148  /// Strategy worked out - mainly at root node
2149  int searchStrategy_;
2150  /// Number of iterations in strong branching
2151  int numberStrongIterations_;
2152  /** 0 - number times strong branching done, 1 - number fixed, 2 - number infeasible */
2153  int strongInfo_[3];
2154  /**
2155      For advanced applications you may wish to modify the behavior of Cbc
2156      e.g. if the solver is a NLP solver then you may not have an exact
2157      optimum solution at each step.  This gives characteristics - just for one BAB.
2158      For actually saving/restoring a solution you need the actual solver one.
2159  */
2160  OsiBabSolver * solverCharacteristics_;
2161  /// Whether to force a resolve after takeOffCuts
2162  bool resolveAfterTakeOffCuts_;
2163#if NEW_UPDATE_OBJECT>1
2164  /// Number of outstanding update information items
2165  int numberUpdateItems_;
2166  /// Maximum number of outstanding update information items
2167  int maximumNumberUpdateItems_;
2168  /// Update items
2169  CbcObjectUpdateData * updateItems_;
2170#endif
2171  /**
2172     Parallel
2173     0 - off
2174     1 - testing
2175     2-99 threads
2176     other special meanings
2177  */
2178  int numberThreads_;
2179  /** thread mode
2180      always use numberThreads for branching
2181      1 set then use numberThreads in root mini branch and bound
2182      2 set then use numberThreads for root cuts
2183      default is 0
2184  */
2185  int threadMode_;
2186 //@}
2187};
2188/// So we can use osiObject or CbcObject during transition
2189void getIntegerInformation(const OsiObject * object, double & originalLower,
2190                           double & originalUpper) ;
2191// So we can call from other programs
2192// Real main program
2193class OsiClpSolverInterface;
2194int CbcMain (int argc, const char *argv[],OsiClpSolverInterface & solver,CbcModel ** babSolver);
2195int CbcMain (int argc, const char *argv[],CbcModel & babSolver);
2196// four ways of calling
2197int callCbc(const char * input2, OsiClpSolverInterface& solver1); 
2198int callCbc(const char * input2);
2199int callCbc(const std::string input2, OsiClpSolverInterface& solver1); 
2200int callCbc(const std::string input2) ;
2201// When we want to load up CbcModel with options first
2202void CbcMain0 (CbcModel & babSolver);
2203int CbcMain1 (int argc, const char *argv[],CbcModel & babSolver);
2204// two ways of calling
2205int callCbc(const char * input2, CbcModel & babSolver); 
2206int callCbc(const std::string input2, CbcModel & babSolver); 
2207// And when CbcMain0 already called to initialize
2208int callCbc1(const char * input2, CbcModel & babSolver); 
2209int callCbc1(const std::string input2, CbcModel & babSolver); 
2210// And when CbcMain0 already called to initialize (with call back) (see CbcMain1 for whereFrom)
2211int callCbc1(const char * input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom)); 
2212int callCbc1(const std::string input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom)); 
2213int CbcMain1 (int argc, const char *argv[],CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2214// For uniform setting of cut and heuristic options
2215void setCutAndHeuristicOptions(CbcModel & model);
2216#endif
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