source: trunk/Cbc/src/CbcModel.hpp @ 940

Last change on this file since 940 was 940, checked in by forrest, 14 years ago

for my experiments

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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
739  /// Set how often to scan global cuts
740  void setHowOftenGlobalScan(int number);
741  /// Get how often to scan global cuts
742  inline int howOftenGlobalScan() const
743  { return howOftenGlobalScan_;}
744  /// Original columns as created by integerPresolve or preprocessing
745  inline int * originalColumns() const
746  { return originalColumns_;}
747  /// Set original columns as created by preprocessing
748  void setOriginalColumns(const int * originalColumns) ;
749
750  /** Set the print frequency.
751 
752    Controls the number of nodes evaluated between status prints.
753    If <tt>number <=0</tt> the print frequency is set to 100 nodes for large
754    problems, 1000 for small problems.
755    Print frequency has very slight overhead if small.
756  */
757  inline void setPrintFrequency(int number)
758  { printFrequency_=number;}
759  /// Get the print frequency
760  inline int printFrequency() const
761  { return printFrequency_;}
762  //@}
763
764  //---------------------------------------------------------------------------
765  ///@name Methods returning info on how the solution process terminated
766  //@{
767    /// Are there a numerical difficulties?
768    bool isAbandoned() const;
769    /// Is optimality proven?
770    bool isProvenOptimal() const;
771    /// Is  infeasiblity proven (or none better than cutoff)?
772    bool isProvenInfeasible() const;
773    /// Was continuous solution unbounded
774    bool isContinuousUnbounded() const;
775    /// Was continuous solution unbounded
776    bool isProvenDualInfeasible() const;
777    /// Node limit reached?
778    bool isNodeLimitReached() const;
779    /// Time limit reached?
780    bool isSecondsLimitReached() const;
781    /// Solution limit reached?
782    bool isSolutionLimitReached() const;
783    /// Get how many iterations it took to solve the problem.
784    inline int getIterationCount() const
785    { return numberIterations_;}
786    /// Get how many Nodes it took to solve the problem.
787    inline int getNodeCount() const
788    { return numberNodes_;}
789    /** Final status of problem
790        Some of these can be found out by is...... functions
791        -1 before branchAndBound
792        0 finished - check isProvenOptimal or isProvenInfeasible to see if solution found
793        (or check value of best solution)
794        1 stopped - on maxnodes, maxsols, maxtime
795        2 difficulties so run was abandoned
796        (5 event user programmed event occurred)
797    */
798    inline int status() const
799    { return status_;}
800    inline void setProblemStatus(int value)
801    { status_=value;}
802    /** Secondary status of problem
803        -1 unset (status_ will also be -1)
804        0 search completed with solution
805        1 linear relaxation not feasible (or worse than cutoff)
806        2 stopped on gap
807        3 stopped on nodes
808        4 stopped on time
809        5 stopped on user event
810        6 stopped on solutions
811        7 linear relaxation unbounded
812    */
813    inline int secondaryStatus() const
814    { return secondaryStatus_;}
815    inline void setSecondaryStatus(int value)
816    { secondaryStatus_=value;}
817    /// Are there numerical difficulties (for initialSolve) ?
818    bool isInitialSolveAbandoned() const ;
819    /// Is optimality proven (for initialSolve) ?
820    bool isInitialSolveProvenOptimal() const ;
821    /// Is primal infeasiblity proven (for initialSolve) ?
822    bool isInitialSolveProvenPrimalInfeasible() const ;
823    /// Is dual infeasiblity proven (for initialSolve) ?
824    bool isInitialSolveProvenDualInfeasible() const ;
825
826  //@}
827
828  //---------------------------------------------------------------------------
829  /**@name Problem information methods
830     
831     These methods call the solver's query routines to return
832     information about the problem referred to by the current object.
833     Querying a problem that has no data associated with it result in
834     zeros for the number of rows and columns, and NULL pointers from
835     the methods that return vectors.
836     
837     Const pointers returned from any data-query method are valid as
838     long as the data is unchanged and the solver is not called.
839  */
840  //@{
841  /// Number of rows in continuous (root) problem.
842  inline int numberRowsAtContinuous() const
843  { return numberRowsAtContinuous_;}
844
845  /// Get number of columns
846  inline int getNumCols() const
847  { return solver_->getNumCols();}
848 
849  /// Get number of rows
850  inline int getNumRows() const
851  { return solver_->getNumRows();}
852 
853  /// Get number of nonzero elements
854  inline CoinBigIndex getNumElements() const
855  { return solver_->getNumElements();}
856
857  /// Number of integers in problem
858  inline int numberIntegers() const
859  { return numberIntegers_;}
860  // Integer variables
861  inline const int * integerVariable() const 
862  { return integerVariable_;}
863  /// Whether or not integer
864  inline char integerType(int i) const
865  { return integerInfo_[i];}
866  /// Whether or not integer
867  inline const char * integerType() const
868  { return integerInfo_;}
869
870  /// Get pointer to array[getNumCols()] of column lower bounds
871  inline const double * getColLower() const
872  { return solver_->getColLower();}
873 
874  /// Get pointer to array[getNumCols()] of column upper bounds
875  inline const double * getColUpper() const
876  { return solver_->getColUpper();}
877 
878  /** Get pointer to array[getNumRows()] of row constraint senses.
879      <ul>
880      <li>'L': <= constraint
881      <li>'E': =  constraint
882      <li>'G': >= constraint
883      <li>'R': ranged constraint
884      <li>'N': free constraint
885      </ul>
886  */
887  inline const char * getRowSense() const
888  { return solver_->getRowSense();}
889 
890  /** Get pointer to array[getNumRows()] of rows right-hand sides
891      <ul>
892      <li> if rowsense()[i] == 'L' then rhs()[i] == rowupper()[i]
893      <li> if rowsense()[i] == 'G' then rhs()[i] == rowlower()[i]
894      <li> if rowsense()[i] == 'R' then rhs()[i] == rowupper()[i]
895      <li> if rowsense()[i] == 'N' then rhs()[i] == 0.0
896      </ul>
897  */
898  inline const double * getRightHandSide() const
899  { return solver_->getRightHandSide();}
900 
901  /** Get pointer to array[getNumRows()] of row ranges.
902      <ul>
903      <li> if rowsense()[i] == 'R' then
904      rowrange()[i] == rowupper()[i] - rowlower()[i]
905      <li> if rowsense()[i] != 'R' then
906      rowrange()[i] is 0.0
907      </ul>
908  */
909  inline const double * getRowRange() const
910  { return solver_->getRowRange();}
911 
912  /// Get pointer to array[getNumRows()] of row lower bounds
913  inline const double * getRowLower() const
914  { return solver_->getRowLower();}
915 
916  /// Get pointer to array[getNumRows()] of row upper bounds
917  inline const double * getRowUpper() const
918  { return solver_->getRowUpper();}
919 
920  /// Get pointer to array[getNumCols()] of objective function coefficients
921  inline const double * getObjCoefficients() const
922  { return solver_->getObjCoefficients();}
923 
924  /// Get objective function sense (1 for min (default), -1 for max)
925  inline double getObjSense() const
926  {
927    //assert (dblParam_[CbcOptimizationDirection]== solver_->getObjSense());
928    return dblParam_[CbcOptimizationDirection];}
929 
930  /// Return true if variable is continuous
931  inline bool isContinuous(int colIndex) const
932  { return solver_->isContinuous(colIndex);}
933 
934  /// Return true if variable is binary
935  inline bool isBinary(int colIndex) const
936  { return solver_->isBinary(colIndex);}
937 
938  /** Return true if column is integer.
939      Note: This function returns true if the the column
940      is binary or a general integer.
941  */
942  inline bool isInteger(int colIndex) const
943  { return solver_->isInteger(colIndex);}
944 
945  /// Return true if variable is general integer
946  inline bool isIntegerNonBinary(int colIndex) const
947  { return solver_->isIntegerNonBinary(colIndex);}
948 
949  /// Return true if variable is binary and not fixed at either bound
950  inline bool isFreeBinary(int colIndex) const
951  { return solver_->isFreeBinary(colIndex) ;}
952 
953  /// Get pointer to row-wise copy of matrix
954  inline const CoinPackedMatrix * getMatrixByRow() const
955  { return solver_->getMatrixByRow();}
956 
957  /// Get pointer to column-wise copy of matrix
958  inline const CoinPackedMatrix * getMatrixByCol() const
959  { return solver_->getMatrixByCol();}
960 
961  /// Get solver's value for infinity
962  inline double getInfinity() const
963  { return solver_->getInfinity();}
964  /// Get pointer to array[getNumCols()] (for speed) of column lower bounds
965  inline const double * getCbcColLower() const
966  { return cbcColLower_;}
967  /// Get pointer to array[getNumCols()] (for speed) of column upper bounds
968  inline const double * getCbcColUpper() const
969  { return cbcColUpper_;}
970  /// Get pointer to array[getNumRows()] (for speed) of row lower bounds
971  inline const double * getCbcRowLower() const
972  { return cbcRowLower_;}
973  /// Get pointer to array[getNumRows()] (for speed) of row upper bounds
974  inline const double * getCbcRowUpper() const
975  { return cbcRowUpper_;}
976  /// Get pointer to array[getNumCols()] (for speed) of primal solution vector
977  inline const double * getCbcColSolution() const
978  { return cbcColSolution_;}
979  /// Get pointer to array[getNumRows()] (for speed) of dual prices
980  inline const double * getCbcRowPrice() const
981  { return cbcRowPrice_;}
982  /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
983  inline const double * getCbcReducedCost() const
984  { return cbcReducedCost_;}
985  /// Get pointer to array[getNumRows()] (for speed) of row activity levels.
986  inline const double * getCbcRowActivity() const
987  { return cbcRowActivity_;}
988  //@}
989 
990 
991  /**@name Methods related to querying the solution */
992  //@{
993  /// Holds solution at continuous (after cuts if branchAndBound called)
994  inline double * continuousSolution() const
995  { return continuousSolution_;}
996  /** Array marked whenever a solution is found if non-zero.
997      Code marks if heuristic returns better so heuristic
998      need only mark if it wants to on solutions which
999      are worse than current */
1000  inline int * usedInSolution() const
1001  { return usedInSolution_;}
1002  /// Increases usedInSolution for nonzeros
1003  void incrementUsed(const double * solution);
1004  /// Record a new incumbent solution and update objectiveValue
1005  void setBestSolution(CBC_Message how,
1006                       double & objectiveValue, const double *solution,
1007                       int fixVariables=0);
1008  /// Just update objectiveValue
1009  void setBestObjectiveValue( double objectiveValue);
1010
1011  /** Call this to really test if a valid solution can be feasible
1012      Solution is number columns in size.
1013      If fixVariables true then bounds of continuous solver updated.
1014      Returns objective value (worse than cutoff if not feasible)
1015      Previously computed objective value is now passed in (in case user does not do solve)
1016 */
1017  double checkSolution(double cutoff, double * solution,
1018                       int fixVariables, double originalObjValue);
1019  /** Test the current solution for feasiblility.
1020
1021    Scan all objects for indications of infeasibility. This is broken down
1022    into simple integer infeasibility (\p numberIntegerInfeasibilities)
1023    and all other reports of infeasibility (\p numberObjectInfeasibilities).
1024  */
1025  bool feasibleSolution(int & numberIntegerInfeasibilities,
1026                        int & numberObjectInfeasibilities) const;
1027
1028  /** Solution to the most recent lp relaxation.
1029
1030    The solver's solution to the most recent lp relaxation.
1031  */
1032   
1033  inline double * currentSolution() const
1034  { return currentSolution_;}
1035  /** For testing infeasibilities - will point to
1036      currentSolution_ or solver-->getColSolution()
1037  */
1038  inline const double * testSolution() const
1039  { return testSolution_;}
1040  inline void setTestSolution(const double * solution)
1041  { testSolution_ = solution;}
1042  /// Make sure region there and optionally copy solution
1043  void reserveCurrentSolution(const double * solution=NULL);
1044
1045  /// Get pointer to array[getNumCols()] of primal solution vector
1046  inline const double * getColSolution() const
1047  { return solver_->getColSolution();}
1048 
1049  /// Get pointer to array[getNumRows()] of dual prices
1050  inline const double * getRowPrice() const
1051  { return solver_->getRowPrice();}
1052 
1053  /// Get a pointer to array[getNumCols()] of reduced costs
1054  inline const double * getReducedCost() const
1055  { return solver_->getReducedCost();}
1056 
1057  /// Get pointer to array[getNumRows()] of row activity levels.
1058  inline const double * getRowActivity() const
1059  { return solver_->getRowActivity();}
1060 
1061  /// Get current objective function value
1062  inline double getCurrentObjValue() const
1063  { return dblParam_[CbcCurrentObjectiveValue]; }
1064  /// Get current minimization objective function value
1065  inline double getCurrentMinimizationObjValue() const
1066  { return dblParam_[CbcCurrentMinimizationObjectiveValue];}
1067 
1068  /// Get best objective function value as minimization
1069  inline double getMinimizationObjValue() const
1070  { return bestObjective_;}
1071  /// Set best objective function value as minimization
1072  inline void setMinimizationObjValue(double value) 
1073  { bestObjective_=value;}
1074 
1075  /// Get best objective function value
1076  inline double getObjValue() const
1077  { return bestObjective_ * solver_->getObjSense() ; } 
1078  /** Get best possible objective function value.
1079      This is better of best possible left on tree
1080      and best solution found.
1081      If called from within branch and cut may be optimistic.
1082  */
1083  double getBestPossibleObjValue() const;
1084  /// Set best objective function value
1085  inline void setObjValue(double value) 
1086  { bestObjective_=value * solver_->getObjSense() ;}
1087 
1088  /** The best solution to the integer programming problem.
1089
1090    The best solution to the integer programming problem found during
1091    the search. If no solution is found, the method returns null.
1092  */
1093
1094  inline double * bestSolution() const
1095  { return bestSolution_;}
1096  /** User callable setBestSolution.
1097      If check false does not check valid
1098      If true then sees if feasible and warns if objective value
1099      worse than given (so just set to COIN_DBL_MAX if you don't care).
1100      If check true then does not save solution if not feasible
1101  */
1102  void setBestSolution(const double * solution,int numberColumns,
1103                       double objectiveValue,bool check=false);
1104 
1105  /// Get number of solutions
1106  inline int getSolutionCount() const
1107  { return numberSolutions_;}
1108 
1109  /// Set number of solutions (so heuristics will be different)
1110  inline void setSolutionCount(int value) 
1111  { numberSolutions_=value;}
1112  /** Current phase (so heuristics etc etc can find out).
1113      0 - initial solve
1114      1 - solve with cuts at root
1115      2 - solve with cuts
1116      3 - other e.g. strong branching
1117      4 - trying to validate a solution
1118      5 - at end of search
1119  */
1120  inline int phase() const
1121  { return phase_;}
1122 
1123  /// Get number of heuristic solutions
1124  inline int getNumberHeuristicSolutions() const { return numberHeuristicSolutions_;}
1125  /// Set number of heuristic solutions
1126  inline void setNumberHeuristicSolutions(int value) { numberHeuristicSolutions_=value;}
1127
1128  /// Set objective function sense (1 for min (default), -1 for max,)
1129  inline void setObjSense(double s) { dblParam_[CbcOptimizationDirection]=s;
1130  solver_->setObjSense(s);}
1131
1132  /// Value of objective at continuous
1133  inline double getContinuousObjective() const
1134  { return originalContinuousObjective_;}
1135  inline void setContinuousObjective(double value)
1136  { originalContinuousObjective_=value;}
1137  /// Number of infeasibilities at continuous
1138  inline int getContinuousInfeasibilities() const
1139  { return continuousInfeasibilities_;}
1140  inline void setContinuousInfeasibilities(int value)
1141  { continuousInfeasibilities_=value;}
1142  /// Value of objective after root node cuts added
1143  inline double rootObjectiveAfterCuts() const
1144  { return continuousObjective_;}
1145  /// Sum of Changes to objective by first solve
1146  inline double sumChangeObjective() const
1147  { return sumChangeObjective1_;}
1148  /** Number of times global cuts violated.  When global cut pool then this
1149      should be kept for each cut and type of cut */
1150  inline int numberGlobalViolations() const
1151  { return numberGlobalViolations_;}
1152  inline void clearNumberGlobalViolations()
1153  { numberGlobalViolations_=0;}
1154  /// Whether to force a resolve after takeOffCuts
1155  inline bool resolveAfterTakeOffCuts() const
1156  { return resolveAfterTakeOffCuts_;}
1157  inline void setResolveAfterTakeOffCuts(bool yesNo)
1158  { resolveAfterTakeOffCuts_=yesNo;}
1159  /// Maximum number of rows
1160  inline int maximumRows() const
1161  { return maximumRows_;}
1162  /// Work basis for temporary use
1163  inline CoinWarmStartBasis & workingBasis()
1164  { return workingBasis_;}
1165  /// Get number of threads
1166  inline int getNumberThreads() const
1167  { return numberThreads_;}
1168  /// Set number of threads
1169  inline void setNumberThreads(int value) 
1170  { numberThreads_=value;}
1171  /// Get thread mode
1172  inline int getThreadMode() const
1173  { return threadMode_;}
1174  /** Set thread mode
1175      always use numberThreads for branching
1176      1 set then use numberThreads in root mini branch and bound
1177      2 set then use numberThreads for root cuts
1178      default is 0
1179  */
1180  inline void setThreadMode(int value) 
1181  { threadMode_=value;}
1182  /// Get number of "iterations" to stop after
1183  inline int getStopNumberIterations() const
1184  { return stopNumberIterations_;}
1185  /// Set number of "iterations" to stop after
1186  inline void setStopNumberIterations(int value) 
1187  { stopNumberIterations_=value;}
1188  //@}
1189
1190  /** \name Node selection */
1191  //@{
1192  // Comparison functions (which may be overridden by inheritance)
1193  inline CbcCompareBase * nodeComparison() const
1194  { return nodeCompare_;}
1195  void setNodeComparison(CbcCompareBase * compare);
1196  void setNodeComparison(CbcCompareBase & compare);
1197  //@}
1198
1199  /** \name Problem feasibility checking */
1200  //@{
1201  // Feasibility functions (which may be overridden by inheritance)
1202  inline CbcFeasibilityBase * problemFeasibility() const
1203  { return problemFeasibility_;}
1204  void setProblemFeasibility(CbcFeasibilityBase * feasibility);
1205  void setProblemFeasibility(CbcFeasibilityBase & feasibility);
1206  //@}
1207
1208  /** \name Tree methods and subtree methods */
1209  //@{
1210  /// Tree method e.g. heap (which may be overridden by inheritance)
1211  inline CbcTree * tree() const
1212  { return tree_;}
1213  /// For modifying tree handling (original is cloned)
1214  void passInTreeHandler(CbcTree & tree);
1215  /** For passing in an CbcModel to do a sub Tree (with derived tree handlers).
1216      Passed in model must exist for duration of branch and bound
1217  */
1218  void passInSubTreeModel(CbcModel & model);
1219  /** For retrieving a copy of subtree model with given OsiSolver.
1220      If no subtree model will use self (up to user to reset cutoff etc).
1221      If solver NULL uses current
1222  */
1223  CbcModel * subTreeModel(OsiSolverInterface * solver=NULL) const;
1224  /// Returns number of times any subtree stopped on nodes, time etc
1225  inline int numberStoppedSubTrees() const
1226  { return numberStoppedSubTrees_;}
1227  /// Says a sub tree was stopped
1228  inline void incrementSubTreeStopped()
1229  { numberStoppedSubTrees_++;}
1230  /** Whether to automatically do presolve before branch and bound (subTrees).
1231      0 - no
1232      1 - ordinary presolve
1233      2 - integer presolve (dodgy)
1234  */
1235  inline int typePresolve() const
1236  { return presolve_;}
1237  inline void setTypePresolve(int value)
1238  { presolve_=value;}
1239 
1240  //@}
1241
1242  /** \name Branching Decisions
1243 
1244    See the CbcBranchDecision class for additional information.
1245  */
1246  //@{
1247
1248  /// Get the current branching decision method.
1249  inline CbcBranchDecision * branchingMethod() const
1250  { return branchingMethod_;}
1251  /// Set the branching decision method.
1252  inline void setBranchingMethod(CbcBranchDecision * method)
1253  { delete branchingMethod_; branchingMethod_ = method->clone();}
1254  /** Set the branching method
1255 
1256    \overload
1257  */
1258  inline void setBranchingMethod(CbcBranchDecision & method)
1259  { delete branchingMethod_; branchingMethod_ = method.clone();}
1260  /// Get the current cut modifier method
1261  inline CbcCutModifier * cutModifier() const
1262  { return cutModifier_;}
1263  /// Set the cut modifier method
1264  void setCutModifier(CbcCutModifier * modifier);
1265  /** Set the cut modifier method
1266 
1267    \overload
1268  */
1269  void setCutModifier(CbcCutModifier & modifier);
1270  //@}
1271
1272  /** \name Row (constraint) and Column (variable) cut generation */
1273  //@{
1274
1275  /** State of search
1276      0 - no solution
1277      1 - only heuristic solutions
1278      2 - branched to a solution
1279      3 - no solution but many nodes
1280  */
1281  inline int stateOfSearch() const
1282  { return stateOfSearch_;}
1283  inline void setStateOfSearch(int state)
1284  { stateOfSearch_=state;}
1285  /// Strategy worked out - mainly at root node for use by CbcNode
1286  inline int searchStrategy() const
1287  { return searchStrategy_;}
1288  /// Set strategy worked out - mainly at root node for use by CbcNode
1289  inline void setSearchStrategy(int value)
1290  { searchStrategy_ = value; }
1291
1292  /// Get the number of cut generators
1293  inline int numberCutGenerators() const
1294  { return numberCutGenerators_;}
1295  /// Get the list of cut generators
1296  inline CbcCutGenerator ** cutGenerators() const
1297  { return generator_;}
1298  ///Get the specified cut generator
1299  inline CbcCutGenerator * cutGenerator(int i) const
1300  { return generator_[i];}
1301  ///Get the specified cut generator before any changes
1302  inline CbcCutGenerator * virginCutGenerator(int i) const
1303  { return virginGenerator_[i];}
1304  /** Add one generator - up to user to delete generators.
1305      howoften affects how generator is used. 0 or 1 means always,
1306      >1 means every that number of nodes.  Negative values have same
1307      meaning as positive but they may be switched off (-> -100) by code if
1308      not many cuts generated at continuous.  -99 is just done at root.
1309      Name is just for printout.
1310      If depth >0 overrides how often generator is called (if howOften==-1 or >0).
1311  */
1312  void addCutGenerator(CglCutGenerator * generator,
1313                       int howOften=1, const char * name=NULL,
1314                       bool normal=true, bool atSolution=false, 
1315                       bool infeasible=false,int howOftenInSub=-100,
1316                       int whatDepth=-1, int whatDepthInSub=-1);
1317//@}
1318  /** \name Strategy and sub models
1319 
1320    See the CbcStrategy class for additional information.
1321  */
1322  //@{
1323
1324  /// Get the current strategy
1325  inline CbcStrategy * strategy() const
1326  { return strategy_;}
1327  /// Set the strategy. Clones
1328  void setStrategy(CbcStrategy & strategy);
1329  /// Get the current parent model
1330  inline CbcModel * parentModel() const
1331  { return parentModel_;}
1332  /// Set the parent model
1333  inline void setParentModel(CbcModel & parentModel)
1334  { parentModel_ = &parentModel;}
1335  //@}
1336
1337
1338  /** \name Heuristics and priorities */
1339  //@{
1340  /*! \brief Add one heuristic - up to user to delete
1341
1342    The name is just used for print messages.
1343  */
1344  void addHeuristic(CbcHeuristic * generator, const char *name = NULL,
1345                    int before=-1);
1346  ///Get the specified heuristic
1347  inline CbcHeuristic * heuristic(int i) const
1348  { return heuristic_[i];}
1349  /// Get the number of heuristics
1350  inline int numberHeuristics() const
1351  { return numberHeuristics_;}
1352  /// Pointer to heuristic solver which found last solution (or NULL)
1353  inline CbcHeuristic * lastHeuristic() const
1354  { return lastHeuristic_;}
1355  /// set last heuristic which found a solution
1356  inline void setLastHeuristic(CbcHeuristic * last)
1357  { lastHeuristic_=last;}
1358
1359  /** Pass in branching priorities.
1360 
1361      If ifClique then priorities are on cliques otherwise priorities are
1362      on integer variables. 
1363      Other type (if exists set to default)
1364      1 is highest priority. (well actually -INT_MAX is but that's ugly)
1365      If hotstart > 0 then branches are created to force
1366      the variable to the value given by best solution.  This enables a
1367      sort of hot start.  The node choice should be greatest depth
1368      and hotstart should normally be switched off after a solution.
1369
1370      If ifNotSimpleIntegers true then appended to normal integers
1371
1372      This is now deprecated except for simple usage.  If user
1373      creates Cbcobjects then set priority in them
1374
1375      \internal Added for Kurt Spielberg.
1376  */
1377  void passInPriorities(const int * priorities, bool ifNotSimpleIntegers);
1378
1379  /// Returns priority level for an object (or 1000 if no priorities exist)
1380  inline int priority(int sequence) const
1381  { return object_[sequence]->priority();}
1382
1383  /*! \brief Set an event handler
1384 
1385    A clone of the handler passed as a parameter is stored in CbcModel.
1386  */
1387  void passInEventHandler(const CbcEventHandler *eventHandler) ;
1388
1389  /*! \brief Retrieve a pointer to the event handler */
1390  inline CbcEventHandler* getEventHandler() const
1391  { return (eventHandler_) ; } 
1392
1393  //@}
1394   
1395  /**@name Setting/Accessing application data */
1396  //@{
1397    /** Set application data.
1398
1399        This is a pointer that the application can store into and
1400        retrieve from the solver interface.
1401        This field is available for the application to optionally
1402        define and use.
1403    */
1404    void setApplicationData (void * appData);
1405
1406    /// Get application data
1407    void * getApplicationData() const;
1408  /**
1409      For advanced applications you may wish to modify the behavior of Cbc
1410      e.g. if the solver is a NLP solver then you may not have an exact
1411      optimum solution at each step.  Information could be built into
1412      OsiSolverInterface but this is an alternative so that that interface
1413      does not have to be changed.  If something similar is useful to
1414      enough solvers then it could be migrated
1415      You can also pass in by using solver->setAuxiliaryInfo.
1416      You should do that if solver is odd - if solver is normal simplex
1417      then use this.
1418      NOTE - characteristics are not cloned
1419  */
1420  void passInSolverCharacteristics(OsiBabSolver * solverCharacteristics);
1421  /// Get solver characteristics
1422  inline const OsiBabSolver * solverCharacteristics() const
1423  { return solverCharacteristics_;}
1424  //@}
1425 
1426  //---------------------------------------------------------------------------
1427
1428  /**@name Message handling */
1429  //@{
1430  /// Pass in Message handler (not deleted at end)
1431  void passInMessageHandler(CoinMessageHandler * handler);
1432  /// Set language
1433  void newLanguage(CoinMessages::Language language);
1434  inline void setLanguage(CoinMessages::Language language)
1435  {newLanguage(language);}
1436  /// Return handler
1437  inline CoinMessageHandler * messageHandler() const
1438  {return handler_;}
1439  /// Return messages
1440  inline CoinMessages & messages() 
1441  {return messages_;}
1442  /// Return pointer to messages
1443  inline CoinMessages * messagesPointer() 
1444  {return &messages_;}
1445  /// Set log level
1446  void setLogLevel(int value);
1447  /// Get log level
1448  inline int logLevel() const
1449  { return handler_->logLevel();}
1450  //@}
1451  //---------------------------------------------------------------------------
1452  ///@name Specialized
1453  //@{
1454
1455  /**
1456      Set special options
1457      0 bit (1) - check if cuts valid (if on debugger list)
1458      1 bit (2) - use current basis to check integer solution (rather than all slack)
1459      2 bit (4) - don't check integer solution (by solving LP)
1460      3 bit (8) - fast analyze
1461      4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
1462      5 bit (32) - keep names
1463      6 bit (64) - try for dominated columns
1464      7 bit (128) - SOS type 1 but all declared integer
1465      8 bit (256) - Set to say solution just found, unset by doing cuts
1466      9 bit (512) - Try reduced model after 100 nodes
1467      10 bit (1024) - Switch on some heuristics even if seems unlikely
1468  */
1469  /// Set special options
1470  inline void setSpecialOptions(int value)
1471  { specialOptions_=value;}
1472  /// Get special options
1473  inline int specialOptions() const
1474  { return specialOptions_;}
1475  /// Says if normal solver i.e. has well defined CoinPackedMatrix
1476  inline bool normalSolver() const
1477  { return (specialOptions_&16)==0;}
1478  /// Now we may not own objects - just point to solver's objects
1479  inline bool ownObjects() const
1480  { return ownObjects_;}
1481  /// Pointer to a mutex
1482  inline void * mutex()
1483  { return mutex_;}
1484  /// Split up nodes
1485  int splitModel(int numberModels, CbcModel ** model,
1486                  int numberNodes);
1487  /// Start threads
1488  void startSplitModel(int numberIterations);
1489  /// Merge models
1490  void mergeModels(int numberModel, CbcModel ** model,
1491                   int numberNodes);
1492  //@}
1493  //---------------------------------------------------------------------------
1494
1495  ///@name Constructors and destructors etc
1496  //@{
1497    /// Default Constructor
1498    CbcModel(); 
1499   
1500    /// Constructor from solver
1501    CbcModel(const OsiSolverInterface &);
1502 
1503    /** Assign a solver to the model (model assumes ownership)
1504
1505      On return, \p solver will be NULL.
1506      If deleteSolver then current solver deleted (if model owned)
1507
1508      \note Parameter settings in the outgoing solver are not inherited by
1509            the incoming solver.
1510    */
1511    void assignSolver(OsiSolverInterface *&solver,bool deleteSolver=true);
1512
1513    /** \brief Set ownership of solver
1514
1515      A parameter of false tells CbcModel it does not own the solver and
1516      should not delete it. Once you claim ownership of the solver, you're
1517      responsible for eventually deleting it. Note that CbcModel clones
1518      solvers with abandon.  Unless you have a deep understanding of the
1519      workings of CbcModel, the only time you want to claim ownership is when
1520      you're about to delete the CbcModel object but want the solver to
1521      continue to exist (as, for example, when branchAndBound has finished
1522      and you want to hang on to the answer).
1523    */
1524    inline void setModelOwnsSolver (bool ourSolver)
1525  { ownership_ = ourSolver ? (ownership_ |0x80000000) : (ownership_ & (~0x80000000)) ; } 
1526
1527    /*! \brief Get ownership of solver
1528   
1529      A return value of true means that CbcModel owns the solver and will
1530      take responsibility for deleting it when that becomes necessary.
1531    */
1532  inline bool modelOwnsSolver () { return ((ownership_&0x80000000)!=0) ; } 
1533 
1534    /** Copy constructor .
1535      If noTree is true then tree and cuts are not copied
1536    */ 
1537    CbcModel(const CbcModel & rhs, bool noTree=false);
1538 
1539    /// Assignment operator
1540    CbcModel & operator=(const CbcModel& rhs);
1541 
1542    /// Destructor
1543     ~CbcModel ();
1544
1545    /// Returns solver - has current state
1546    inline OsiSolverInterface * solver() const
1547    { return solver_;}
1548
1549    /// Returns current solver - sets new one
1550    inline OsiSolverInterface * swapSolver(OsiSolverInterface * solver) 
1551    { OsiSolverInterface * returnSolver = solver_; solver_ = solver; return returnSolver;}
1552
1553    /// Returns solver with continuous state
1554    inline OsiSolverInterface * continuousSolver() const
1555    { return continuousSolver_;}
1556
1557    /// Create solver with continuous state
1558    inline void createContinuousSolver()
1559    { continuousSolver_ = solver_->clone();}
1560    /// Clear solver with continuous state
1561    inline void clearContinuousSolver()
1562    { delete continuousSolver_; continuousSolver_ = NULL;}
1563
1564  /// A copy of the solver, taken at constructor or by saveReferenceSolver
1565  inline OsiSolverInterface * referenceSolver() const
1566  { return referenceSolver_;}
1567
1568  /// Save a copy of the current solver so can be reset to
1569  void saveReferenceSolver();
1570
1571  /** Uses a copy of reference solver to be current solver.
1572      Because of possible mismatches all exotic integer information is loat
1573      (apart from normal information in OsiSolverInterface)
1574      so SOS etc and priorities will have to be redone
1575  */
1576  void resetToReferenceSolver();
1577
1578  /// Clears out as much as possible (except solver)
1579  void gutsOfDestructor();
1580  /** Clears out enough to reset CbcModel as if no branch and bound done
1581   */
1582  void gutsOfDestructor2();
1583  /** Clears out enough to reset CbcModel cutoff etc
1584   */
1585  void resetModel();
1586  /** Most of copy constructor
1587      mode - 0 copy but don't delete before
1588             1 copy and delete before
1589             2 copy and delete before (but use virgin generators)
1590  */
1591  void gutsOfCopy(const CbcModel & rhs,int mode=0);
1592  /// Move status, nodes etc etc across
1593  void moveInfo(const CbcModel & rhs);
1594  //@}
1595
1596  ///@semi-private i.e. users should not use
1597  //@{
1598    /// Get how many Nodes it took to solve the problem.
1599    int getNodeCount2() const
1600    { return numberNodes2_;}
1601  /// Set pointers for speed
1602  void setPointers(const OsiSolverInterface * solver);
1603  /** Perform reduced cost fixing
1604
1605    Fixes integer variables at their current value based on reduced cost
1606    penalties.  Returns number fixed
1607  */
1608  int reducedCostFix() ;
1609  /// Encapsulates solver resolve
1610  int resolve(OsiSolverInterface * solver);
1611
1612  /** Encapsulates choosing a variable -
1613      anyAction -2, infeasible (-1 round again), 0 done
1614  */
1615  int chooseBranch(CbcNode * newNode, int numberPassesLeft,
1616                   CbcNode * oldNode, OsiCuts & cuts,
1617                   bool & resolved, CoinWarmStartBasis *lastws,
1618                   const double * lowerBefore,const double * upperBefore,
1619                   OsiSolverBranch * & branches);
1620  int chooseBranch(CbcNode * newNode, int numberPassesLeft, bool & resolved);
1621
1622  /** Return an empty basis object of the specified size
1623
1624    A useful utility when constructing a basis for a subproblem from scratch.
1625    The object returned will be of the requested capacity and appropriate for
1626    the solver attached to the model.
1627  */
1628  CoinWarmStartBasis *getEmptyBasis(int ns = 0, int na = 0) const ;
1629
1630  /** Remove inactive cuts from the model
1631
1632    An OsiSolverInterface is expected to maintain a valid basis, but not a
1633    valid solution, when loose cuts are deleted. Restoring a valid solution
1634    requires calling the solver to reoptimise. If it's certain the solution
1635    will not be required, set allowResolve to false to suppress
1636    reoptimisation.
1637    If saveCuts then slack cuts will be saved
1638    On input current cuts are cuts and newCuts
1639    on exit current cuts will be correct
1640  */
1641  void takeOffCuts(OsiCuts &cuts, 
1642                   bool allowResolve,OsiCuts * saveCuts,
1643                   int numberNewCuts=0, const OsiRowCut ** newCuts=NULL) ;
1644
1645  /** Determine and install the active cuts that need to be added for
1646    the current subproblem
1647
1648    The whole truth is a bit more complicated. The first action is a call to
1649    addCuts1(). addCuts() then sorts through the list, installs the tight
1650    cuts in the model, and does bookkeeping (adjusts reference counts).
1651    The basis returned from addCuts1() is adjusted accordingly.
1652   
1653    If it turns out that the node should really be fathomed by bound,
1654    addCuts() simply treats all the cuts as loose as it does the bookkeeping.
1655
1656    canFix true if extra information being passed
1657  */
1658  int addCuts(CbcNode * node, CoinWarmStartBasis *&lastws,bool canFix);
1659
1660  /** Traverse the tree from node to root and prep the model
1661
1662    addCuts1() begins the job of prepping the model to match the current
1663    subproblem. The model is stripped of all cuts, and the search tree is
1664    traversed from node to root to determine the changes required. Appropriate
1665    bounds changes are installed, a list of cuts is collected but not
1666    installed, and an appropriate basis (minus the cuts, but big enough to
1667    accommodate them) is constructed.
1668
1669    \todo addCuts1() is called in contexts where it's known in advance that
1670          all that's desired is to determine a list of cuts and do the
1671          bookkeeping (adjust the reference counts). The work of installing
1672          bounds and building a basis goes to waste.
1673  */
1674  void addCuts1(CbcNode * node, CoinWarmStartBasis *&lastws);
1675  /** Returns bounds just before where - initially original bounds.
1676      Also sets downstream nodes (lower if force 1, upper if 2)
1677  */
1678  void previousBounds (CbcNode * node, CbcNodeInfo * where,int iColumn,
1679                       double & lower, double & upper,int force);
1680  /** Set objective value in a node.  This is separated out so that
1681     odd solvers can use.  It may look at extra information in
1682     solverCharacteriscs_ and will also use bound from parent node
1683  */
1684  void setObjectiveValue(CbcNode * thisNode, const CbcNode * parentNode) const;
1685
1686  /** If numberBeforeTrust >0 then we are going to use CbcBranchDynamic.
1687      Scan and convert CbcSimpleInteger objects
1688  */
1689  void convertToDynamic();
1690  /// Set numberBeforeTrust in all objects
1691  void synchronizeNumberBeforeTrust();
1692  /// Zap integer information in problem (may leave object info)
1693  void zapIntegerInformation(bool leaveObjects=true);
1694  /// Use cliques for pseudocost information - return nonzero if infeasible
1695  int cliquePseudoCosts(int doStatistics);
1696  /// Fill in useful estimates
1697  void pseudoShadow(double * down, double * up);
1698  /** Return pseudo costs
1699      If not all integers or not pseudo costs - returns all zero
1700      Length of arrays are numberIntegers() and entries
1701      correspond to integerVariable()[i]
1702      User must allocate arrays before call
1703  */
1704  void fillPseudoCosts(double * downCosts, double * upCosts,
1705                       int * numberDown=NULL, int * numberUp=NULL,
1706                       int * numberDownInfeasible=NULL,
1707                       int * numberUpInfeasible=NULL) const;
1708  /** Do heuristics at root.
1709      0 - don't delete
1710      1 - delete
1711      2 - just delete - don't even use
1712  */
1713  void doHeuristicsAtRoot(int deleteHeuristicsAfterwards=0);
1714  /// Get the hotstart solution
1715  inline const double * hotstartSolution() const
1716  { return hotstartSolution_;}
1717  /// Get the hotstart priorities
1718  inline const int * hotstartPriorities() const
1719  { return hotstartPriorities_;}
1720
1721  /// Return the list of cuts initially collected for this subproblem
1722  inline CbcCountRowCut ** addedCuts() const
1723  { return addedCuts_;}
1724  /// Number of entries in the list returned by #addedCuts()
1725  inline int currentNumberCuts() const
1726  { return currentNumberCuts_;}
1727  /// Global cuts
1728  inline OsiCuts * globalCuts() 
1729  { return &globalCuts_;}
1730  /// Copy and set a pointer to a row cut which will be added instead of normal branching.
1731  void setNextRowCut(const OsiRowCut & cut);
1732  /// Get a pointer to current node (be careful)
1733  inline CbcNode * currentNode() const
1734  { return currentNode_;}
1735  /// Get a pointer to probing info
1736  inline CglTreeProbingInfo * probingInfo() const
1737  { return probingInfo_;}
1738  /// Set the number of iterations done in strong branching.
1739  inline void setNumberStrongIterations(int number)
1740  { numberStrongIterations_ = number;}
1741  /// Get the number of iterations done in strong branching.
1742  inline int numberStrongIterations() const
1743  { return numberStrongIterations_;}
1744# ifdef COIN_HAS_CLP
1745  /// Set depth for fast nodes
1746  inline void setFastNodeDepth(int value) 
1747  { fastNodeDepth_ = value;}
1748  /// Get depth for fast nodes
1749  inline int fastNodeDepth() const
1750  { return fastNodeDepth_;}
1751  inline void incrementExtra(int nodes, int iterations)
1752  { numberExtraNodes_ += nodes; numberExtraIterations_ += iterations;}
1753#endif
1754  /// Increment strong info
1755  void incrementStrongInfo(int numberTimes, int numberIterations,
1756                           int numberFixed, bool ifInfeasible);
1757  /// Says whether all dynamic integers
1758  inline bool allDynamic () const { return ((ownership_&0x40000000)!=0) ; } 
1759  /// Create C++ lines to get to current state
1760  void generateCpp( FILE * fp,int options);
1761  /// Generate an OsiBranchingInformation object
1762  OsiBranchingInformation usefulInformation() const;
1763  /** Warm start object produced by heuristic or strong branching
1764
1765      If get a valid integer solution outside branch and bound then it can take
1766      a reasonable time to solve LP which produces clean solution.  If this object has
1767      any size then it will be used in solve.
1768  */
1769  inline void setBestSolutionBasis(const CoinWarmStartBasis & bestSolutionBasis)
1770  { bestSolutionBasis_ = bestSolutionBasis;}
1771  //@}
1772
1773//---------------------------------------------------------------------------
1774
1775private:
1776  ///@name Private member data
1777  //@{
1778
1779  /// The solver associated with this model.
1780  OsiSolverInterface * solver_;
1781
1782  /** Ownership of objects and other stuff
1783
1784      0x80000000 model owns solver
1785      0x40000000 all variables CbcDynamicPseudoCost
1786  */
1787  unsigned int ownership_ ;
1788
1789  /// A copy of the solver, taken at the continuous (root) node.
1790  OsiSolverInterface * continuousSolver_;
1791
1792  /// A copy of the solver, taken at constructor or by saveReferenceSolver
1793  OsiSolverInterface * referenceSolver_;
1794
1795   /// Message handler
1796  CoinMessageHandler * handler_;
1797
1798  /** Flag to say if handler_ is the default handler.
1799 
1800    The default handler is deleted when the model is deleted. Other
1801    handlers (supplied by the client) will not be deleted.
1802  */
1803  bool defaultHandler_;
1804
1805  /// Cbc messages
1806  CoinMessages messages_;
1807
1808  /// Array for integer parameters
1809  int intParam_[CbcLastIntParam];
1810
1811  /// Array for double parameters
1812  double dblParam_[CbcLastDblParam];
1813
1814  /** Pointer to an empty warm start object
1815
1816    It turns out to be useful to have this available as a base from
1817    which to build custom warm start objects. This is typed as CoinWarmStart
1818    rather than CoinWarmStartBasis to allow for the possibility that a
1819    client might want to apply a solver that doesn't use a basis-based warm
1820    start. See getEmptyBasis for an example of how this field can be used.
1821  */
1822  mutable CoinWarmStart *emptyWarmStart_ ;
1823
1824  /// Best objective
1825  double bestObjective_;
1826  /// Best possible objective
1827  double bestPossibleObjective_;
1828  /// Sum of Changes to objective by first solve
1829  double sumChangeObjective1_;
1830  /// Sum of Changes to objective by subsequent solves
1831  double sumChangeObjective2_;
1832
1833  /// Array holding the incumbent (best) solution.
1834  double * bestSolution_;
1835
1836  /** Array holding the current solution.
1837
1838    This array is used more as a temporary.
1839  */
1840  double * currentSolution_;
1841  /** For testing infeasibilities - will point to
1842      currentSolution_ or solver-->getColSolution()
1843  */
1844  mutable const double * testSolution_;
1845  /** Warm start object produced by heuristic or strong branching
1846
1847      If get a valid integer solution outside branch and bound then it can take
1848      a reasonable time to solve LP which produces clean solution.  If this object has
1849      any size then it will be used in solve.
1850  */
1851  CoinWarmStartBasis bestSolutionBasis_ ;
1852  /// Global cuts
1853  OsiCuts globalCuts_;
1854
1855  /// Minimum degradation in objective value to continue cut generation
1856  double minimumDrop_;
1857  /// Number of solutions
1858  int numberSolutions_;
1859  /** State of search
1860      0 - no solution
1861      1 - only heuristic solutions
1862      2 - branched to a solution
1863      3 - no solution but many nodes
1864  */
1865  int stateOfSearch_;
1866  /// Hotstart solution
1867  double * hotstartSolution_;
1868  /// Hotstart priorities
1869  int * hotstartPriorities_;
1870  /// Number of heuristic solutions
1871  int numberHeuristicSolutions_;
1872  /// Cumulative number of nodes
1873  int numberNodes_;
1874  /** Cumulative number of nodes for statistics.
1875      Must fix to match up
1876  */
1877  int numberNodes2_;
1878  /// Cumulative number of iterations
1879  int numberIterations_;
1880  /// Status of problem - 0 finished, 1 stopped, 2 difficulties
1881  int status_;
1882  /** Secondary status of problem
1883      -1 unset (status_ will also be -1)
1884      0 search completed with solution
1885      1 linear relaxation not feasible (or worse than cutoff)
1886      2 stopped on gap
1887      3 stopped on nodes
1888      4 stopped on time
1889      5 stopped on user event
1890      6 stopped on solutions
1891   */
1892  int secondaryStatus_;
1893  /// Number of integers in problem
1894  int numberIntegers_;
1895  /// Number of rows at continuous
1896  int numberRowsAtContinuous_;
1897  /// Maximum number of cuts
1898  int maximumNumberCuts_;
1899  /** Current phase (so heuristics etc etc can find out).
1900      0 - initial solve
1901      1 - solve with cuts at root
1902      2 - solve with cuts
1903      3 - other e.g. strong branching
1904      4 - trying to validate a solution
1905      5 - at end of search
1906  */
1907  int phase_;
1908
1909  /// Number of entries in #addedCuts_
1910  int currentNumberCuts_;
1911
1912  /** Current limit on search tree depth
1913
1914    The allocated size of #walkback_. Increased as needed.
1915  */
1916  int maximumDepth_;
1917  /** Array used to assemble the path between a node and the search tree root
1918
1919    The array is resized when necessary. #maximumDepth_  is the current
1920    allocated size.
1921  */
1922  CbcNodeInfo ** walkback_;
1923
1924  /** The list of cuts initially collected for this subproblem
1925
1926    When the subproblem at this node is rebuilt, a set of cuts is collected
1927    for inclusion in the constraint system. If any of these cuts are
1928    subsequently removed because they have become loose, the corresponding
1929    entry is set to NULL.
1930  */
1931  CbcCountRowCut ** addedCuts_;
1932
1933  /** A pointer to a row cut which will be added instead of normal branching.
1934      After use it should be set to NULL.
1935  */
1936  OsiRowCut * nextRowCut_;
1937
1938  /// Current node so can be used elsewhere
1939  CbcNode * currentNode_;
1940
1941  /// Indices of integer variables
1942  int * integerVariable_;
1943  /// Whether of not integer
1944  char * integerInfo_;
1945  /// Holds solution at continuous (after cuts)
1946  double * continuousSolution_;
1947  /// Array marked whenever a solution is found if non-zero
1948  int * usedInSolution_;
1949  /**
1950      0 bit (1) - check if cuts valid (if on debugger list)
1951      1 bit (2) - use current basis to check integer solution (rather than all slack)
1952      2 bit (4) - don't check integer solution
1953      3 bit (8) - Strong is doing well - keep on
1954  */
1955  int specialOptions_;
1956  /// User node comparison function
1957  CbcCompareBase * nodeCompare_;
1958  /// User feasibility function (see CbcFeasibleBase.hpp)
1959  CbcFeasibilityBase * problemFeasibility_;
1960  /// Tree
1961  CbcTree * tree_;
1962  /// A pointer to model to be used for subtrees
1963  CbcModel * subTreeModel_;
1964  /// Number of times any subtree stopped on nodes, time etc
1965  int numberStoppedSubTrees_;
1966  /// Variable selection function
1967  CbcBranchDecision * branchingMethod_;
1968  /// Cut modifier function
1969  CbcCutModifier * cutModifier_;
1970  /// Strategy
1971  CbcStrategy * strategy_;
1972  /// Parent model
1973  CbcModel * parentModel_;
1974  /** Whether to automatically do presolve before branch and bound.
1975      0 - no
1976      1 - ordinary presolve
1977      2 - integer presolve (dodgy)
1978  */
1979  /// Pointer to array[getNumCols()] (for speed) of column lower bounds
1980  const double * cbcColLower_;
1981  /// Pointer to array[getNumCols()] (for speed) of column upper bounds
1982  const double * cbcColUpper_;
1983  /// Pointer to array[getNumRows()] (for speed) of row lower bounds
1984  const double * cbcRowLower_;
1985  /// Pointer to array[getNumRows()] (for speed) of row upper bounds
1986  const double * cbcRowUpper_;
1987  /// Pointer to array[getNumCols()] (for speed) of primal solution vector
1988  const double * cbcColSolution_;
1989  /// Pointer to array[getNumRows()] (for speed) of dual prices
1990  const double * cbcRowPrice_;
1991  /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
1992  const double * cbcReducedCost_;
1993  /// Pointer to array[getNumRows()] (for speed) of row activity levels.
1994  const double * cbcRowActivity_;
1995  /// Pointer to user-defined data structure
1996  void * appData_;
1997  /// Pointer to a mutex
1998  void * mutex_;
1999  /// Presolve for CbcTreeLocal
2000  int presolve_;
2001  /** Maximum number of candidates to consider for strong branching.
2002    To disable strong branching, set this to 0.
2003  */
2004  int numberStrong_;
2005  /** \brief The number of branches before pseudo costs believed
2006             in dynamic strong branching.
2007     
2008    A value of 0 is  off.
2009  */
2010  int numberBeforeTrust_;
2011  /** \brief The number of variables for which to compute penalties
2012             in dynamic strong branching.
2013  */
2014  int numberPenalties_;
2015  /// For threads - stop after this many "iterations"
2016  int stopNumberIterations_;
2017  /** Scale factor to make penalties match strong.
2018      Should/will be computed */
2019  double penaltyScaleFactor_;
2020  /// Number of analyze iterations to do
2021  int numberAnalyzeIterations_;
2022  /// Arrays with analysis results
2023  double * analyzeResults_;
2024  /// Number of nodes infeasible by normal branching (before cuts)
2025  int numberInfeasibleNodes_;
2026  /** Problem type as set by user or found by analysis.  This will be extended
2027      0 - not known
2028      1 - Set partitioning <=
2029      2 - Set partitioning ==
2030      3 - Set covering
2031  */
2032  int problemType_;
2033  /// Print frequency
2034  int printFrequency_;
2035  /// Number of cut generators
2036  int numberCutGenerators_;
2037  // Cut generators
2038  CbcCutGenerator ** generator_;
2039  // Cut generators before any changes
2040  CbcCutGenerator ** virginGenerator_;
2041  /// Number of heuristics
2042  int numberHeuristics_;
2043  /// Heuristic solvers
2044  CbcHeuristic ** heuristic_;
2045  /// Pointer to heuristic solver which found last solution (or NULL)
2046  CbcHeuristic * lastHeuristic_;
2047# ifdef COIN_HAS_CLP
2048  /// Depth for fast nodes
2049  int fastNodeDepth_;
2050#endif
2051  /*! Pointer to the event handler */
2052# ifdef CBC_ONLY_CLP
2053  ClpEventHandler *eventHandler_ ;
2054# else
2055  CbcEventHandler *eventHandler_ ;
2056# endif
2057
2058  /// Total number of objects
2059  int numberObjects_;
2060
2061  /** \brief Integer and Clique and ... information
2062
2063    \note The code assumes that the first objects on the list will be
2064          SimpleInteger objects for each integer variable, followed by
2065          Clique objects. Portions of the code that understand Clique objects
2066          will fail if they do not immediately follow the SimpleIntegers.
2067          Large chunks of the code will fail if the first objects are not
2068          SimpleInteger. As of 2003.08, SimpleIntegers and Cliques are the only
2069          objects.
2070  */
2071  OsiObject ** object_;
2072  /// Now we may not own objects - just point to solver's objects
2073  bool ownObjects_;
2074 
2075  /// Original columns as created by integerPresolve or preprocessing
2076  int * originalColumns_;
2077  /// How often to scan global cuts
2078  int howOftenGlobalScan_;
2079  /** Number of times global cuts violated.  When global cut pool then this
2080      should be kept for each cut and type of cut */
2081  int numberGlobalViolations_;
2082  /// Number of extra iterations in fast lp
2083  int numberExtraIterations_;
2084  /// Number of extra nodes in fast lp
2085  int numberExtraNodes_;
2086  /** Value of objective at continuous
2087      (Well actually after initial round of cuts)
2088  */
2089  double continuousObjective_;
2090  /** Value of objective before root node cuts added
2091  */
2092  double originalContinuousObjective_;
2093  /// Number of infeasibilities at continuous
2094  int continuousInfeasibilities_;
2095  /// Maximum number of cut passes at root
2096  int maximumCutPassesAtRoot_;
2097  /// Maximum number of cut passes
2098  int maximumCutPasses_;
2099  /// Preferred way of branching
2100  int preferredWay_;
2101  /// Current cut pass number
2102  int currentPassNumber_;
2103  /// Maximum number of cuts (for whichGenerator_)
2104  int maximumWhich_;
2105  /// Maximum number of rows
2106  int maximumRows_;
2107  /// Work basis for temporary use
2108  CoinWarmStartBasis workingBasis_;
2109  /// Which cut generator generated this cut
2110  int * whichGenerator_;
2111  /// Maximum number of statistics
2112  int maximumStatistics_;
2113  /// statistics
2114  CbcStatistics ** statistics_;
2115  /// Maximum depth reached
2116  int maximumDepthActual_;
2117  /// Number of reduced cost fixings
2118  double numberDJFixed_;
2119  /// Probing info
2120  CglTreeProbingInfo * probingInfo_;
2121  /// Number of fixed by analyze at root
2122  int numberFixedAtRoot_;
2123  /// Number fixed by analyze so far
2124  int numberFixedNow_;
2125  /// Whether stopping on gap
2126  bool stoppedOnGap_;
2127  /// Whether event happened
2128  bool eventHappened_;
2129  /// Number of long strong goes
2130  int numberLongStrong_;
2131  /// Number of old active cuts
2132  int numberOldActiveCuts_;
2133  /// Number of new cuts
2134  int numberNewCuts_;
2135  /// Size of mini - tree
2136  int sizeMiniTree_;
2137  /// Strategy worked out - mainly at root node
2138  int searchStrategy_;
2139  /// Number of iterations in strong branching
2140  int numberStrongIterations_;
2141  /** 0 - number times strong branching done, 1 - number fixed, 2 - number infeasible */
2142  int strongInfo_[3];
2143  /**
2144      For advanced applications you may wish to modify the behavior of Cbc
2145      e.g. if the solver is a NLP solver then you may not have an exact
2146      optimum solution at each step.  This gives characteristics - just for one BAB.
2147      For actually saving/restoring a solution you need the actual solver one.
2148  */
2149  OsiBabSolver * solverCharacteristics_;
2150  /// Whether to force a resolve after takeOffCuts
2151  bool resolveAfterTakeOffCuts_;
2152#if NEW_UPDATE_OBJECT>1
2153  /// Number of outstanding update information items
2154  int numberUpdateItems_;
2155  /// Maximum number of outstanding update information items
2156  int maximumNumberUpdateItems_;
2157  /// Update items
2158  CbcObjectUpdateData * updateItems_;
2159#endif
2160  /**
2161     Parallel
2162     0 - off
2163     1 - testing
2164     2-99 threads
2165     other special meanings
2166  */
2167  int numberThreads_;
2168  /** thread mode
2169      always use numberThreads for branching
2170      1 set then use numberThreads in root mini branch and bound
2171      2 set then use numberThreads for root cuts
2172      default is 0
2173  */
2174  int threadMode_;
2175 //@}
2176};
2177/// So we can use osiObject or CbcObject during transition
2178void getIntegerInformation(const OsiObject * object, double & originalLower,
2179                           double & originalUpper) ;
2180// So we can call from other programs
2181// Real main program
2182class OsiClpSolverInterface;
2183int CbcMain (int argc, const char *argv[],OsiClpSolverInterface & solver,CbcModel ** babSolver);
2184int CbcMain (int argc, const char *argv[],CbcModel & babSolver);
2185// four ways of calling
2186int callCbc(const char * input2, OsiClpSolverInterface& solver1); 
2187int callCbc(const char * input2);
2188int callCbc(const std::string input2, OsiClpSolverInterface& solver1); 
2189int callCbc(const std::string input2) ;
2190// When we want to load up CbcModel with options first
2191void CbcMain0 (CbcModel & babSolver);
2192int CbcMain1 (int argc, const char *argv[],CbcModel & babSolver);
2193// two ways of calling
2194int callCbc(const char * input2, CbcModel & babSolver); 
2195int callCbc(const std::string input2, CbcModel & babSolver); 
2196// And when CbcMain0 already called to initialize
2197int callCbc1(const char * input2, CbcModel & babSolver); 
2198int callCbc1(const std::string input2, CbcModel & babSolver); 
2199// And when CbcMain0 already called to initialize (with call back) (see CbcMain1 for whereFrom)
2200int callCbc1(const char * input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom)); 
2201int callCbc1(const std::string input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom)); 
2202int CbcMain1 (int argc, const char *argv[],CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2203// For uniform setting of cut and heuristic options
2204void setCutAndHeuristicOptions(CbcModel & model);
2205#endif
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