source: trunk/Cbc/src/CbcModel.hpp @ 934

Last change on this file since 934 was 934, checked in by forrest, 13 years ago

make behavior more consistent between parallel and non parallel

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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  void setBestSolution(const double * solution,int numberColumns,double objectiveValue);
1097 
1098  /// Get number of solutions
1099  inline int getSolutionCount() const
1100  { return numberSolutions_;}
1101 
1102  /// Set number of solutions (so heuristics will be different)
1103  inline void setSolutionCount(int value) 
1104  { numberSolutions_=value;}
1105  /** Current phase (so heuristics etc etc can find out).
1106      0 - initial solve
1107      1 - solve with cuts at root
1108      2 - solve with cuts
1109      3 - other e.g. strong branching
1110      4 - trying to validate a solution
1111      5 - at end of search
1112  */
1113  inline int phase() const
1114  { return phase_;}
1115 
1116  /// Get number of heuristic solutions
1117  inline int getNumberHeuristicSolutions() const { return numberHeuristicSolutions_;}
1118  /// Set number of heuristic solutions
1119  inline void setNumberHeuristicSolutions(int value) { numberHeuristicSolutions_=value;}
1120
1121  /// Set objective function sense (1 for min (default), -1 for max,)
1122  inline void setObjSense(double s) { dblParam_[CbcOptimizationDirection]=s;
1123  solver_->setObjSense(s);}
1124
1125  /// Value of objective at continuous
1126  inline double getContinuousObjective() const
1127  { return originalContinuousObjective_;}
1128  inline void setContinuousObjective(double value)
1129  { originalContinuousObjective_=value;}
1130  /// Number of infeasibilities at continuous
1131  inline int getContinuousInfeasibilities() const
1132  { return continuousInfeasibilities_;}
1133  inline void setContinuousInfeasibilities(int value)
1134  { continuousInfeasibilities_=value;}
1135  /// Value of objective after root node cuts added
1136  inline double rootObjectiveAfterCuts() const
1137  { return continuousObjective_;}
1138  /// Sum of Changes to objective by first solve
1139  inline double sumChangeObjective() const
1140  { return sumChangeObjective1_;}
1141  /** Number of times global cuts violated.  When global cut pool then this
1142      should be kept for each cut and type of cut */
1143  inline int numberGlobalViolations() const
1144  { return numberGlobalViolations_;}
1145  inline void clearNumberGlobalViolations()
1146  { numberGlobalViolations_=0;}
1147  /// Whether to force a resolve after takeOffCuts
1148  inline bool resolveAfterTakeOffCuts() const
1149  { return resolveAfterTakeOffCuts_;}
1150  inline void setResolveAfterTakeOffCuts(bool yesNo)
1151  { resolveAfterTakeOffCuts_=yesNo;}
1152  /// Maximum number of rows
1153  inline int maximumRows() const
1154  { return maximumRows_;}
1155  /// Work basis for temporary use
1156  inline CoinWarmStartBasis & workingBasis()
1157  { return workingBasis_;}
1158  /// Get number of threads
1159  inline int getNumberThreads() const
1160  { return numberThreads_;}
1161  /// Set number of threads
1162  inline void setNumberThreads(int value) 
1163  { numberThreads_=value;}
1164  /// Get thread mode
1165  inline int getThreadMode() const
1166  { return threadMode_;}
1167  /** Set thread mode
1168      always use numberThreads for branching
1169      1 set then use numberThreads in root mini branch and bound
1170      2 set then use numberThreads for root cuts
1171      default is 0
1172  */
1173  inline void setThreadMode(int value) 
1174  { threadMode_=value;}
1175  /// Get number of "iterations" to stop after
1176  inline int getStopNumberIterations() const
1177  { return stopNumberIterations_;}
1178  /// Set number of "iterations" to stop after
1179  inline void setStopNumberIterations(int value) 
1180  { stopNumberIterations_=value;}
1181  //@}
1182
1183  /** \name Node selection */
1184  //@{
1185  // Comparison functions (which may be overridden by inheritance)
1186  inline CbcCompareBase * nodeComparison() const
1187  { return nodeCompare_;}
1188  void setNodeComparison(CbcCompareBase * compare);
1189  void setNodeComparison(CbcCompareBase & compare);
1190  //@}
1191
1192  /** \name Problem feasibility checking */
1193  //@{
1194  // Feasibility functions (which may be overridden by inheritance)
1195  inline CbcFeasibilityBase * problemFeasibility() const
1196  { return problemFeasibility_;}
1197  void setProblemFeasibility(CbcFeasibilityBase * feasibility);
1198  void setProblemFeasibility(CbcFeasibilityBase & feasibility);
1199  //@}
1200
1201  /** \name Tree methods and subtree methods */
1202  //@{
1203  /// Tree method e.g. heap (which may be overridden by inheritance)
1204  inline CbcTree * tree() const
1205  { return tree_;}
1206  /// For modifying tree handling (original is cloned)
1207  void passInTreeHandler(CbcTree & tree);
1208  /** For passing in an CbcModel to do a sub Tree (with derived tree handlers).
1209      Passed in model must exist for duration of branch and bound
1210  */
1211  void passInSubTreeModel(CbcModel & model);
1212  /** For retrieving a copy of subtree model with given OsiSolver.
1213      If no subtree model will use self (up to user to reset cutoff etc).
1214      If solver NULL uses current
1215  */
1216  CbcModel * subTreeModel(OsiSolverInterface * solver=NULL) const;
1217  /// Returns number of times any subtree stopped on nodes, time etc
1218  inline int numberStoppedSubTrees() const
1219  { return numberStoppedSubTrees_;}
1220  /// Says a sub tree was stopped
1221  inline void incrementSubTreeStopped()
1222  { numberStoppedSubTrees_++;}
1223  /** Whether to automatically do presolve before branch and bound (subTrees).
1224      0 - no
1225      1 - ordinary presolve
1226      2 - integer presolve (dodgy)
1227  */
1228  inline int typePresolve() const
1229  { return presolve_;}
1230  inline void setTypePresolve(int value)
1231  { presolve_=value;}
1232 
1233  //@}
1234
1235  /** \name Branching Decisions
1236 
1237    See the CbcBranchDecision class for additional information.
1238  */
1239  //@{
1240
1241  /// Get the current branching decision method.
1242  inline CbcBranchDecision * branchingMethod() const
1243  { return branchingMethod_;}
1244  /// Set the branching decision method.
1245  inline void setBranchingMethod(CbcBranchDecision * method)
1246  { delete branchingMethod_; branchingMethod_ = method->clone();}
1247  /** Set the branching method
1248 
1249    \overload
1250  */
1251  inline void setBranchingMethod(CbcBranchDecision & method)
1252  { delete branchingMethod_; branchingMethod_ = method.clone();}
1253  /// Get the current cut modifier method
1254  inline CbcCutModifier * cutModifier() const
1255  { return cutModifier_;}
1256  /// Set the cut modifier method
1257  void setCutModifier(CbcCutModifier * modifier);
1258  /** Set the cut modifier method
1259 
1260    \overload
1261  */
1262  void setCutModifier(CbcCutModifier & modifier);
1263  //@}
1264
1265  /** \name Row (constraint) and Column (variable) cut generation */
1266  //@{
1267
1268  /** State of search
1269      0 - no solution
1270      1 - only heuristic solutions
1271      2 - branched to a solution
1272      3 - no solution but many nodes
1273  */
1274  inline int stateOfSearch() const
1275  { return stateOfSearch_;}
1276  inline void setStateOfSearch(int state)
1277  { stateOfSearch_=state;}
1278  /// Strategy worked out - mainly at root node for use by CbcNode
1279  inline int searchStrategy() const
1280  { return searchStrategy_;}
1281  /// Set strategy worked out - mainly at root node for use by CbcNode
1282  inline void setSearchStrategy(int value)
1283  { searchStrategy_ = value; }
1284
1285  /// Get the number of cut generators
1286  inline int numberCutGenerators() const
1287  { return numberCutGenerators_;}
1288  /// Get the list of cut generators
1289  inline CbcCutGenerator ** cutGenerators() const
1290  { return generator_;}
1291  ///Get the specified cut generator
1292  inline CbcCutGenerator * cutGenerator(int i) const
1293  { return generator_[i];}
1294  ///Get the specified cut generator before any changes
1295  inline CbcCutGenerator * virginCutGenerator(int i) const
1296  { return virginGenerator_[i];}
1297  /** Add one generator - up to user to delete generators.
1298      howoften affects how generator is used. 0 or 1 means always,
1299      >1 means every that number of nodes.  Negative values have same
1300      meaning as positive but they may be switched off (-> -100) by code if
1301      not many cuts generated at continuous.  -99 is just done at root.
1302      Name is just for printout.
1303      If depth >0 overrides how often generator is called (if howOften==-1 or >0).
1304  */
1305  void addCutGenerator(CglCutGenerator * generator,
1306                       int howOften=1, const char * name=NULL,
1307                       bool normal=true, bool atSolution=false, 
1308                       bool infeasible=false,int howOftenInSub=-100,
1309                       int whatDepth=-1, int whatDepthInSub=-1);
1310//@}
1311  /** \name Strategy and sub models
1312 
1313    See the CbcStrategy class for additional information.
1314  */
1315  //@{
1316
1317  /// Get the current strategy
1318  inline CbcStrategy * strategy() const
1319  { return strategy_;}
1320  /// Set the strategy. Clones
1321  void setStrategy(CbcStrategy & strategy);
1322  /// Get the current parent model
1323  inline CbcModel * parentModel() const
1324  { return parentModel_;}
1325  /// Set the parent model
1326  inline void setParentModel(CbcModel & parentModel)
1327  { parentModel_ = &parentModel;}
1328  //@}
1329
1330
1331  /** \name Heuristics and priorities */
1332  //@{
1333  /*! \brief Add one heuristic - up to user to delete
1334
1335    The name is just used for print messages.
1336  */
1337  void addHeuristic(CbcHeuristic * generator, const char *name = NULL);
1338  ///Get the specified heuristic
1339  inline CbcHeuristic * heuristic(int i) const
1340  { return heuristic_[i];}
1341  /// Get the number of heuristics
1342  inline int numberHeuristics() const
1343  { return numberHeuristics_;}
1344  /// Pointer to heuristic solver which found last solution (or NULL)
1345  inline CbcHeuristic * lastHeuristic() const
1346  { return lastHeuristic_;}
1347  /// set last heuristic which found a solution
1348  inline void setLastHeuristic(CbcHeuristic * last)
1349  { lastHeuristic_=last;}
1350
1351  /** Pass in branching priorities.
1352 
1353      If ifClique then priorities are on cliques otherwise priorities are
1354      on integer variables. 
1355      Other type (if exists set to default)
1356      1 is highest priority. (well actually -INT_MAX is but that's ugly)
1357      If hotstart > 0 then branches are created to force
1358      the variable to the value given by best solution.  This enables a
1359      sort of hot start.  The node choice should be greatest depth
1360      and hotstart should normally be switched off after a solution.
1361
1362      If ifNotSimpleIntegers true then appended to normal integers
1363
1364      This is now deprecated except for simple usage.  If user
1365      creates Cbcobjects then set priority in them
1366
1367      \internal Added for Kurt Spielberg.
1368  */
1369  void passInPriorities(const int * priorities, bool ifNotSimpleIntegers);
1370
1371  /// Returns priority level for an object (or 1000 if no priorities exist)
1372  inline int priority(int sequence) const
1373  { return object_[sequence]->priority();}
1374
1375  /*! \brief Set an event handler
1376 
1377    A clone of the handler passed as a parameter is stored in CbcModel.
1378  */
1379  void passInEventHandler(const CbcEventHandler *eventHandler) ;
1380
1381  /*! \brief Retrieve a pointer to the event handler */
1382  inline CbcEventHandler* getEventHandler() const
1383  { return (eventHandler_) ; } 
1384
1385  //@}
1386   
1387  /**@name Setting/Accessing application data */
1388  //@{
1389    /** Set application data.
1390
1391        This is a pointer that the application can store into and
1392        retrieve from the solver interface.
1393        This field is available for the application to optionally
1394        define and use.
1395    */
1396    void setApplicationData (void * appData);
1397
1398    /// Get application data
1399    void * getApplicationData() const;
1400  /**
1401      For advanced applications you may wish to modify the behavior of Cbc
1402      e.g. if the solver is a NLP solver then you may not have an exact
1403      optimum solution at each step.  Information could be built into
1404      OsiSolverInterface but this is an alternative so that that interface
1405      does not have to be changed.  If something similar is useful to
1406      enough solvers then it could be migrated
1407      You can also pass in by using solver->setAuxiliaryInfo.
1408      You should do that if solver is odd - if solver is normal simplex
1409      then use this.
1410      NOTE - characteristics are not cloned
1411  */
1412  void passInSolverCharacteristics(OsiBabSolver * solverCharacteristics);
1413  /// Get solver characteristics
1414  inline const OsiBabSolver * solverCharacteristics() const
1415  { return solverCharacteristics_;}
1416  //@}
1417 
1418  //---------------------------------------------------------------------------
1419
1420  /**@name Message handling */
1421  //@{
1422  /// Pass in Message handler (not deleted at end)
1423  void passInMessageHandler(CoinMessageHandler * handler);
1424  /// Set language
1425  void newLanguage(CoinMessages::Language language);
1426  inline void setLanguage(CoinMessages::Language language)
1427  {newLanguage(language);}
1428  /// Return handler
1429  inline CoinMessageHandler * messageHandler() const
1430  {return handler_;}
1431  /// Return messages
1432  inline CoinMessages & messages() 
1433  {return messages_;}
1434  /// Return pointer to messages
1435  inline CoinMessages * messagesPointer() 
1436  {return &messages_;}
1437  /// Set log level
1438  void setLogLevel(int value);
1439  /// Get log level
1440  inline int logLevel() const
1441  { return handler_->logLevel();}
1442  //@}
1443  //---------------------------------------------------------------------------
1444  ///@name Specialized
1445  //@{
1446
1447  /**
1448      Set special options
1449      0 bit (1) - check if cuts valid (if on debugger list)
1450      1 bit (2) - use current basis to check integer solution (rather than all slack)
1451      2 bit (4) - don't check integer solution (by solving LP)
1452      3 bit (8) - fast analyze
1453      4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
1454      5 bit (32) - keep names
1455      6 bit (64) - try for dominated columns
1456      7 bit (128) - SOS type 1 but all declared integer
1457      8 bit (256) - Set to say solution just found, unset by doing cuts
1458  */
1459  /// Set special options
1460  inline void setSpecialOptions(int value)
1461  { specialOptions_=value;}
1462  /// Get special options
1463  inline int specialOptions() const
1464  { return specialOptions_;}
1465  /// Says if normal solver i.e. has well defined CoinPackedMatrix
1466  inline bool normalSolver() const
1467  { return (specialOptions_&16)==0;}
1468  /// Now we may not own objects - just point to solver's objects
1469  inline bool ownObjects() const
1470  { return ownObjects_;}
1471  /// Pointer to a mutex
1472  inline void * mutex()
1473  { return mutex_;}
1474  /// Split up nodes
1475  int splitModel(int numberModels, CbcModel ** model,
1476                  int numberNodes);
1477  /// Start threads
1478  void startSplitModel(int numberIterations);
1479  /// Merge models
1480  void mergeModels(int numberModel, CbcModel ** model,
1481                   int numberNodes);
1482  //@}
1483  //---------------------------------------------------------------------------
1484
1485  ///@name Constructors and destructors etc
1486  //@{
1487    /// Default Constructor
1488    CbcModel(); 
1489   
1490    /// Constructor from solver
1491    CbcModel(const OsiSolverInterface &);
1492 
1493    /** Assign a solver to the model (model assumes ownership)
1494
1495      On return, \p solver will be NULL.
1496      If deleteSolver then current solver deleted (if model owned)
1497
1498      \note Parameter settings in the outgoing solver are not inherited by
1499            the incoming solver.
1500    */
1501    void assignSolver(OsiSolverInterface *&solver,bool deleteSolver=true);
1502
1503    /** \brief Set ownership of solver
1504
1505      A parameter of false tells CbcModel it does not own the solver and
1506      should not delete it. Once you claim ownership of the solver, you're
1507      responsible for eventually deleting it. Note that CbcModel clones
1508      solvers with abandon.  Unless you have a deep understanding of the
1509      workings of CbcModel, the only time you want to claim ownership is when
1510      you're about to delete the CbcModel object but want the solver to
1511      continue to exist (as, for example, when branchAndBound has finished
1512      and you want to hang on to the answer).
1513    */
1514    inline void setModelOwnsSolver (bool ourSolver)
1515  { ownership_ = ourSolver ? (ownership_ |0x80000000) : (ownership_ & (~0x80000000)) ; } 
1516
1517    /*! \brief Get ownership of solver
1518   
1519      A return value of true means that CbcModel owns the solver and will
1520      take responsibility for deleting it when that becomes necessary.
1521    */
1522  inline bool modelOwnsSolver () { return ((ownership_&0x80000000)!=0) ; } 
1523 
1524    /** Copy constructor .
1525      If noTree is true then tree and cuts are not copied
1526    */ 
1527    CbcModel(const CbcModel & rhs, bool noTree=false);
1528 
1529    /// Assignment operator
1530    CbcModel & operator=(const CbcModel& rhs);
1531 
1532    /// Destructor
1533     ~CbcModel ();
1534
1535    /// Returns solver - has current state
1536    inline OsiSolverInterface * solver() const
1537    { return solver_;}
1538
1539    /// Returns current solver - sets new one
1540    inline OsiSolverInterface * swapSolver(OsiSolverInterface * solver) 
1541    { OsiSolverInterface * returnSolver = solver_; solver_ = solver; return returnSolver;}
1542
1543    /// Returns solver with continuous state
1544    inline OsiSolverInterface * continuousSolver() const
1545    { return continuousSolver_;}
1546
1547    /// Create solver with continuous state
1548    inline void createContinuousSolver()
1549    { continuousSolver_ = solver_->clone();}
1550    /// Clear solver with continuous state
1551    inline void clearContinuousSolver()
1552    { delete continuousSolver_; continuousSolver_ = NULL;}
1553
1554  /// A copy of the solver, taken at constructor or by saveReferenceSolver
1555  inline OsiSolverInterface * referenceSolver() const
1556  { return referenceSolver_;}
1557
1558  /// Save a copy of the current solver so can be reset to
1559  void saveReferenceSolver();
1560
1561  /** Uses a copy of reference solver to be current solver.
1562      Because of possible mismatches all exotic integer information is loat
1563      (apart from normal information in OsiSolverInterface)
1564      so SOS etc and priorities will have to be redone
1565  */
1566  void resetToReferenceSolver();
1567
1568  /// Clears out as much as possible (except solver)
1569  void gutsOfDestructor();
1570  /** Clears out enough to reset CbcModel as if no branch and bound done
1571   */
1572  void gutsOfDestructor2();
1573  /** Clears out enough to reset CbcModel cutoff etc
1574   */
1575  void resetModel();
1576  /// Move status, nodes etc etc across
1577  void moveInfo(const CbcModel & rhs);
1578  //@}
1579
1580  ///@semi-private i.e. users should not use
1581  //@{
1582    /// Get how many Nodes it took to solve the problem.
1583    int getNodeCount2() const
1584    { return numberNodes2_;}
1585  /// Set pointers for speed
1586  void setPointers(const OsiSolverInterface * solver);
1587  /** Perform reduced cost fixing
1588
1589    Fixes integer variables at their current value based on reduced cost
1590    penalties.  Returns number fixed
1591  */
1592  int reducedCostFix() ;
1593  /// Encapsulates solver resolve
1594  int resolve(OsiSolverInterface * solver);
1595
1596  /** Encapsulates choosing a variable -
1597      anyAction -2, infeasible (-1 round again), 0 done
1598  */
1599  int chooseBranch(CbcNode * newNode, int numberPassesLeft,
1600                   CbcNode * oldNode, OsiCuts & cuts,
1601                   bool & resolved, CoinWarmStartBasis *lastws,
1602                   const double * lowerBefore,const double * upperBefore,
1603                   OsiSolverBranch * & branches);
1604  int chooseBranch(CbcNode * newNode, int numberPassesLeft, bool & resolved);
1605
1606  /** Return an empty basis object of the specified size
1607
1608    A useful utility when constructing a basis for a subproblem from scratch.
1609    The object returned will be of the requested capacity and appropriate for
1610    the solver attached to the model.
1611  */
1612  CoinWarmStartBasis *getEmptyBasis(int ns = 0, int na = 0) const ;
1613
1614  /** Remove inactive cuts from the model
1615
1616    An OsiSolverInterface is expected to maintain a valid basis, but not a
1617    valid solution, when loose cuts are deleted. Restoring a valid solution
1618    requires calling the solver to reoptimise. If it's certain the solution
1619    will not be required, set allowResolve to false to suppress
1620    reoptimisation.
1621    If saveCuts then slack cuts will be saved
1622    On input current cuts are cuts and newCuts
1623    on exit current cuts will be correct
1624  */
1625  void takeOffCuts(OsiCuts &cuts, 
1626                   bool allowResolve,OsiCuts * saveCuts,
1627                   int numberNewCuts=0, const OsiRowCut ** newCuts=NULL) ;
1628
1629  /** Determine and install the active cuts that need to be added for
1630    the current subproblem
1631
1632    The whole truth is a bit more complicated. The first action is a call to
1633    addCuts1(). addCuts() then sorts through the list, installs the tight
1634    cuts in the model, and does bookkeeping (adjusts reference counts).
1635    The basis returned from addCuts1() is adjusted accordingly.
1636   
1637    If it turns out that the node should really be fathomed by bound,
1638    addCuts() simply treats all the cuts as loose as it does the bookkeeping.
1639
1640    canFix true if extra information being passed
1641  */
1642  int addCuts(CbcNode * node, CoinWarmStartBasis *&lastws,bool canFix);
1643
1644  /** Traverse the tree from node to root and prep the model
1645
1646    addCuts1() begins the job of prepping the model to match the current
1647    subproblem. The model is stripped of all cuts, and the search tree is
1648    traversed from node to root to determine the changes required. Appropriate
1649    bounds changes are installed, a list of cuts is collected but not
1650    installed, and an appropriate basis (minus the cuts, but big enough to
1651    accommodate them) is constructed.
1652
1653    \todo addCuts1() is called in contexts where it's known in advance that
1654          all that's desired is to determine a list of cuts and do the
1655          bookkeeping (adjust the reference counts). The work of installing
1656          bounds and building a basis goes to waste.
1657  */
1658  void addCuts1(CbcNode * node, CoinWarmStartBasis *&lastws);
1659  /** Returns bounds just before where - initially original bounds.
1660      Also sets downstream nodes (lower if force 1, upper if 2)
1661  */
1662  void previousBounds (CbcNode * node, CbcNodeInfo * where,int iColumn,
1663                       double & lower, double & upper,int force);
1664  /** Set objective value in a node.  This is separated out so that
1665     odd solvers can use.  It may look at extra information in
1666     solverCharacteriscs_ and will also use bound from parent node
1667  */
1668  void setObjectiveValue(CbcNode * thisNode, const CbcNode * parentNode) const;
1669
1670  /** If numberBeforeTrust >0 then we are going to use CbcBranchDynamic.
1671      Scan and convert CbcSimpleInteger objects
1672  */
1673  void convertToDynamic();
1674  /// Set numberBeforeTrust in all objects
1675  void synchronizeNumberBeforeTrust();
1676  /// Zap integer information in problem (may leave object info)
1677  void zapIntegerInformation(bool leaveObjects=true);
1678  /// Use cliques for pseudocost information - return nonzero if infeasible
1679  int cliquePseudoCosts(int doStatistics);
1680  /// Fill in useful estimates
1681  void pseudoShadow(double * down, double * up);
1682  /** Return pseudo costs
1683      If not all integers or not pseudo costs - returns all zero
1684      Length of arrays are numberIntegers() and entries
1685      correspond to integerVariable()[i]
1686      User must allocate arrays before call
1687  */
1688  void fillPseudoCosts(double * downCosts, double * upCosts,
1689                       int * numberDown=NULL, int * numberUp=NULL,
1690                       int * numberDownInfeasible=NULL,
1691                       int * numberUpInfeasible=NULL) const;
1692  /** Do heuristics at root.
1693      0 - don't delete
1694      1 - delete
1695      2 - just delete - don't even use
1696  */
1697  void doHeuristicsAtRoot(int deleteHeuristicsAfterwards=0);
1698  /// Get the hotstart solution
1699  inline const double * hotstartSolution() const
1700  { return hotstartSolution_;}
1701  /// Get the hotstart priorities
1702  inline const int * hotstartPriorities() const
1703  { return hotstartPriorities_;}
1704
1705  /// Return the list of cuts initially collected for this subproblem
1706  inline CbcCountRowCut ** addedCuts() const
1707  { return addedCuts_;}
1708  /// Number of entries in the list returned by #addedCuts()
1709  inline int currentNumberCuts() const
1710  { return currentNumberCuts_;}
1711  /// Global cuts
1712  inline OsiCuts * globalCuts() 
1713  { return &globalCuts_;}
1714  /// Copy and set a pointer to a row cut which will be added instead of normal branching.
1715  void setNextRowCut(const OsiRowCut & cut);
1716  /// Get a pointer to current node (be careful)
1717  inline CbcNode * currentNode() const
1718  { return currentNode_;}
1719  /// Get a pointer to probing info
1720  inline CglTreeProbingInfo * probingInfo() const
1721  { return probingInfo_;}
1722  /// Set the number of iterations done in strong branching.
1723  inline void setNumberStrongIterations(int number)
1724  { numberStrongIterations_ = number;}
1725  /// Get the number of iterations done in strong branching.
1726  inline int numberStrongIterations() const
1727  { return numberStrongIterations_;}
1728# ifdef COIN_HAS_CLP
1729  /// Set depth for fast nodes
1730  inline void setFastNodeDepth(int value) 
1731  { fastNodeDepth_ = value;}
1732  /// Get depth for fast nodes
1733  inline int fastNodeDepth() const
1734  { return fastNodeDepth_;}
1735  inline void incrementExtra(int nodes, int iterations)
1736  { numberExtraNodes_ += nodes; numberExtraIterations_ += iterations;}
1737#endif
1738  /// Increment strong info
1739  void incrementStrongInfo(int numberTimes, int numberIterations,
1740                           int numberFixed, bool ifInfeasible);
1741  /// Says whether all dynamic integers
1742  inline bool allDynamic () const { return ((ownership_&0x40000000)!=0) ; } 
1743  /// Create C++ lines to get to current state
1744  void generateCpp( FILE * fp,int options);
1745  /// Generate an OsiBranchingInformation object
1746  OsiBranchingInformation usefulInformation() const;
1747  /** Warm start object produced by heuristic or strong branching
1748
1749      If get a valid integer solution outside branch and bound then it can take
1750      a reasonable time to solve LP which produces clean solution.  If this object has
1751      any size then it will be used in solve.
1752  */
1753  inline void setBestSolutionBasis(const CoinWarmStartBasis & bestSolutionBasis)
1754  { bestSolutionBasis_ = bestSolutionBasis;}
1755  //@}
1756
1757//---------------------------------------------------------------------------
1758
1759private:
1760  ///@name Private member data
1761  //@{
1762
1763  /// The solver associated with this model.
1764  OsiSolverInterface * solver_;
1765
1766  /** Ownership of objects and other stuff
1767
1768      0x80000000 model owns solver
1769      0x40000000 all variables CbcDynamicPseudoCost
1770  */
1771  unsigned int ownership_ ;
1772
1773  /// A copy of the solver, taken at the continuous (root) node.
1774  OsiSolverInterface * continuousSolver_;
1775
1776  /// A copy of the solver, taken at constructor or by saveReferenceSolver
1777  OsiSolverInterface * referenceSolver_;
1778
1779   /// Message handler
1780  CoinMessageHandler * handler_;
1781
1782  /** Flag to say if handler_ is the default handler.
1783 
1784    The default handler is deleted when the model is deleted. Other
1785    handlers (supplied by the client) will not be deleted.
1786  */
1787  bool defaultHandler_;
1788
1789  /// Cbc messages
1790  CoinMessages messages_;
1791
1792  /// Array for integer parameters
1793  int intParam_[CbcLastIntParam];
1794
1795  /// Array for double parameters
1796  double dblParam_[CbcLastDblParam];
1797
1798  /** Pointer to an empty warm start object
1799
1800    It turns out to be useful to have this available as a base from
1801    which to build custom warm start objects. This is typed as CoinWarmStart
1802    rather than CoinWarmStartBasis to allow for the possibility that a
1803    client might want to apply a solver that doesn't use a basis-based warm
1804    start. See getEmptyBasis for an example of how this field can be used.
1805  */
1806  mutable CoinWarmStart *emptyWarmStart_ ;
1807
1808  /// Best objective
1809  double bestObjective_;
1810  /// Best possible objective
1811  double bestPossibleObjective_;
1812  /// Sum of Changes to objective by first solve
1813  double sumChangeObjective1_;
1814  /// Sum of Changes to objective by subsequent solves
1815  double sumChangeObjective2_;
1816
1817  /// Array holding the incumbent (best) solution.
1818  double * bestSolution_;
1819
1820  /** Array holding the current solution.
1821
1822    This array is used more as a temporary.
1823  */
1824  double * currentSolution_;
1825  /** For testing infeasibilities - will point to
1826      currentSolution_ or solver-->getColSolution()
1827  */
1828  mutable const double * testSolution_;
1829  /** Warm start object produced by heuristic or strong branching
1830
1831      If get a valid integer solution outside branch and bound then it can take
1832      a reasonable time to solve LP which produces clean solution.  If this object has
1833      any size then it will be used in solve.
1834  */
1835  CoinWarmStartBasis bestSolutionBasis_ ;
1836  /// Global cuts
1837  OsiCuts globalCuts_;
1838
1839  /// Minimum degradation in objective value to continue cut generation
1840  double minimumDrop_;
1841  /// Number of solutions
1842  int numberSolutions_;
1843  /** State of search
1844      0 - no solution
1845      1 - only heuristic solutions
1846      2 - branched to a solution
1847      3 - no solution but many nodes
1848  */
1849  int stateOfSearch_;
1850  /// Hotstart solution
1851  double * hotstartSolution_;
1852  /// Hotstart priorities
1853  int * hotstartPriorities_;
1854  /// Number of heuristic solutions
1855  int numberHeuristicSolutions_;
1856  /// Cumulative number of nodes
1857  int numberNodes_;
1858  /** Cumulative number of nodes for statistics.
1859      Must fix to match up
1860  */
1861  int numberNodes2_;
1862  /// Cumulative number of iterations
1863  int numberIterations_;
1864  /// Status of problem - 0 finished, 1 stopped, 2 difficulties
1865  int status_;
1866  /** Secondary status of problem
1867      -1 unset (status_ will also be -1)
1868      0 search completed with solution
1869      1 linear relaxation not feasible (or worse than cutoff)
1870      2 stopped on gap
1871      3 stopped on nodes
1872      4 stopped on time
1873      5 stopped on user event
1874      6 stopped on solutions
1875   */
1876  int secondaryStatus_;
1877  /// Number of integers in problem
1878  int numberIntegers_;
1879  /// Number of rows at continuous
1880  int numberRowsAtContinuous_;
1881  /// Maximum number of cuts
1882  int maximumNumberCuts_;
1883  /** Current phase (so heuristics etc etc can find out).
1884      0 - initial solve
1885      1 - solve with cuts at root
1886      2 - solve with cuts
1887      3 - other e.g. strong branching
1888      4 - trying to validate a solution
1889      5 - at end of search
1890  */
1891  int phase_;
1892
1893  /// Number of entries in #addedCuts_
1894  int currentNumberCuts_;
1895
1896  /** Current limit on search tree depth
1897
1898    The allocated size of #walkback_. Increased as needed.
1899  */
1900  int maximumDepth_;
1901  /** Array used to assemble the path between a node and the search tree root
1902
1903    The array is resized when necessary. #maximumDepth_  is the current
1904    allocated size.
1905  */
1906  CbcNodeInfo ** walkback_;
1907
1908  /** The list of cuts initially collected for this subproblem
1909
1910    When the subproblem at this node is rebuilt, a set of cuts is collected
1911    for inclusion in the constraint system. If any of these cuts are
1912    subsequently removed because they have become loose, the corresponding
1913    entry is set to NULL.
1914  */
1915  CbcCountRowCut ** addedCuts_;
1916
1917  /** A pointer to a row cut which will be added instead of normal branching.
1918      After use it should be set to NULL.
1919  */
1920  OsiRowCut * nextRowCut_;
1921
1922  /// Current node so can be used elsewhere
1923  CbcNode * currentNode_;
1924
1925  /// Indices of integer variables
1926  int * integerVariable_;
1927  /// Whether of not integer
1928  char * integerInfo_;
1929  /// Holds solution at continuous (after cuts)
1930  double * continuousSolution_;
1931  /// Array marked whenever a solution is found if non-zero
1932  int * usedInSolution_;
1933  /**
1934      0 bit (1) - check if cuts valid (if on debugger list)
1935      1 bit (2) - use current basis to check integer solution (rather than all slack)
1936      2 bit (4) - don't check integer solution
1937      3 bit (8) - Strong is doing well - keep on
1938  */
1939  int specialOptions_;
1940  /// User node comparison function
1941  CbcCompareBase * nodeCompare_;
1942  /// User feasibility function (see CbcFeasibleBase.hpp)
1943  CbcFeasibilityBase * problemFeasibility_;
1944  /// Tree
1945  CbcTree * tree_;
1946  /// A pointer to model to be used for subtrees
1947  CbcModel * subTreeModel_;
1948  /// Number of times any subtree stopped on nodes, time etc
1949  int numberStoppedSubTrees_;
1950  /// Variable selection function
1951  CbcBranchDecision * branchingMethod_;
1952  /// Cut modifier function
1953  CbcCutModifier * cutModifier_;
1954  /// Strategy
1955  CbcStrategy * strategy_;
1956  /// Parent model
1957  CbcModel * parentModel_;
1958  /** Whether to automatically do presolve before branch and bound.
1959      0 - no
1960      1 - ordinary presolve
1961      2 - integer presolve (dodgy)
1962  */
1963  /// Pointer to array[getNumCols()] (for speed) of column lower bounds
1964  const double * cbcColLower_;
1965  /// Pointer to array[getNumCols()] (for speed) of column upper bounds
1966  const double * cbcColUpper_;
1967  /// Pointer to array[getNumRows()] (for speed) of row lower bounds
1968  const double * cbcRowLower_;
1969  /// Pointer to array[getNumRows()] (for speed) of row upper bounds
1970  const double * cbcRowUpper_;
1971  /// Pointer to array[getNumCols()] (for speed) of primal solution vector
1972  const double * cbcColSolution_;
1973  /// Pointer to array[getNumRows()] (for speed) of dual prices
1974  const double * cbcRowPrice_;
1975  /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
1976  const double * cbcReducedCost_;
1977  /// Pointer to array[getNumRows()] (for speed) of row activity levels.
1978  const double * cbcRowActivity_;
1979  /// Pointer to user-defined data structure
1980  void * appData_;
1981  /// Pointer to a mutex
1982  void * mutex_;
1983  /// Presolve for CbcTreeLocal
1984  int presolve_;
1985  /** Maximum number of candidates to consider for strong branching.
1986    To disable strong branching, set this to 0.
1987  */
1988  int numberStrong_;
1989  /** \brief The number of branches before pseudo costs believed
1990             in dynamic strong branching.
1991     
1992    A value of 0 is  off.
1993  */
1994  int numberBeforeTrust_;
1995  /** \brief The number of variables for which to compute penalties
1996             in dynamic strong branching.
1997  */
1998  int numberPenalties_;
1999  /// For threads - stop after this many "iterations"
2000  int stopNumberIterations_;
2001  /** Scale factor to make penalties match strong.
2002      Should/will be computed */
2003  double penaltyScaleFactor_;
2004  /// Number of analyze iterations to do
2005  int numberAnalyzeIterations_;
2006  /// Arrays with analysis results
2007  double * analyzeResults_;
2008  /// Number of nodes infeasible by normal branching (before cuts)
2009  int numberInfeasibleNodes_;
2010  /** Problem type as set by user or found by analysis.  This will be extended
2011      0 - not known
2012      1 - Set partitioning <=
2013      2 - Set partitioning ==
2014      3 - Set covering
2015  */
2016  int problemType_;
2017  /// Print frequency
2018  int printFrequency_;
2019  /// Number of cut generators
2020  int numberCutGenerators_;
2021  // Cut generators
2022  CbcCutGenerator ** generator_;
2023  // Cut generators before any changes
2024  CbcCutGenerator ** virginGenerator_;
2025  /// Number of heuristics
2026  int numberHeuristics_;
2027  /// Heuristic solvers
2028  CbcHeuristic ** heuristic_;
2029  /// Pointer to heuristic solver which found last solution (or NULL)
2030  CbcHeuristic * lastHeuristic_;
2031# ifdef COIN_HAS_CLP
2032  /// Depth for fast nodes
2033  int fastNodeDepth_;
2034#endif
2035  /*! Pointer to the event handler */
2036# ifdef CBC_ONLY_CLP
2037  ClpEventHandler *eventHandler_ ;
2038# else
2039  CbcEventHandler *eventHandler_ ;
2040# endif
2041
2042  /// Total number of objects
2043  int numberObjects_;
2044
2045  /** \brief Integer and Clique and ... information
2046
2047    \note The code assumes that the first objects on the list will be
2048          SimpleInteger objects for each integer variable, followed by
2049          Clique objects. Portions of the code that understand Clique objects
2050          will fail if they do not immediately follow the SimpleIntegers.
2051          Large chunks of the code will fail if the first objects are not
2052          SimpleInteger. As of 2003.08, SimpleIntegers and Cliques are the only
2053          objects.
2054  */
2055  OsiObject ** object_;
2056  /// Now we may not own objects - just point to solver's objects
2057  bool ownObjects_;
2058 
2059  /// Original columns as created by integerPresolve or preprocessing
2060  int * originalColumns_;
2061  /// How often to scan global cuts
2062  int howOftenGlobalScan_;
2063  /** Number of times global cuts violated.  When global cut pool then this
2064      should be kept for each cut and type of cut */
2065  int numberGlobalViolations_;
2066  /// Number of extra iterations in fast lp
2067  int numberExtraIterations_;
2068  /// Number of extra nodes in fast lp
2069  int numberExtraNodes_;
2070  /** Value of objective at continuous
2071      (Well actually after initial round of cuts)
2072  */
2073  double continuousObjective_;
2074  /** Value of objective before root node cuts added
2075  */
2076  double originalContinuousObjective_;
2077  /// Number of infeasibilities at continuous
2078  int continuousInfeasibilities_;
2079  /// Maximum number of cut passes at root
2080  int maximumCutPassesAtRoot_;
2081  /// Maximum number of cut passes
2082  int maximumCutPasses_;
2083  /// Preferred way of branching
2084  int preferredWay_;
2085  /// Current cut pass number
2086  int currentPassNumber_;
2087  /// Maximum number of cuts (for whichGenerator_)
2088  int maximumWhich_;
2089  /// Maximum number of rows
2090  int maximumRows_;
2091  /// Work basis for temporary use
2092  CoinWarmStartBasis workingBasis_;
2093  /// Which cut generator generated this cut
2094  int * whichGenerator_;
2095  /// Maximum number of statistics
2096  int maximumStatistics_;
2097  /// statistics
2098  CbcStatistics ** statistics_;
2099  /// Maximum depth reached
2100  int maximumDepthActual_;
2101  /// Number of reduced cost fixings
2102  double numberDJFixed_;
2103  /// Probing info
2104  CglTreeProbingInfo * probingInfo_;
2105  /// Number of fixed by analyze at root
2106  int numberFixedAtRoot_;
2107  /// Number fixed by analyze so far
2108  int numberFixedNow_;
2109  /// Whether stopping on gap
2110  bool stoppedOnGap_;
2111  /// Whether event happened
2112  bool eventHappened_;
2113  /// Number of long strong goes
2114  int numberLongStrong_;
2115  /// Number of old active cuts
2116  int numberOldActiveCuts_;
2117  /// Number of new cuts
2118  int numberNewCuts_;
2119  /// Size of mini - tree
2120  int sizeMiniTree_;
2121  /// Strategy worked out - mainly at root node
2122  int searchStrategy_;
2123  /// Number of iterations in strong branching
2124  int numberStrongIterations_;
2125  /** 0 - number times strong branching done, 1 - number fixed, 2 - number infeasible */
2126  int strongInfo_[3];
2127  /**
2128      For advanced applications you may wish to modify the behavior of Cbc
2129      e.g. if the solver is a NLP solver then you may not have an exact
2130      optimum solution at each step.  This gives characteristics - just for one BAB.
2131      For actually saving/restoring a solution you need the actual solver one.
2132  */
2133  OsiBabSolver * solverCharacteristics_;
2134  /// Whether to force a resolve after takeOffCuts
2135  bool resolveAfterTakeOffCuts_;
2136#if NEW_UPDATE_OBJECT>1
2137  /// Number of outstanding update information items
2138  int numberUpdateItems_;
2139  /// Maximum number of outstanding update information items
2140  int maximumNumberUpdateItems_;
2141  /// Update items
2142  CbcObjectUpdateData * updateItems_;
2143#endif
2144  /**
2145     Parallel
2146     0 - off
2147     1 - testing
2148     2-99 threads
2149     other special meanings
2150  */
2151  int numberThreads_;
2152  /** thread mode
2153      always use numberThreads for branching
2154      1 set then use numberThreads in root mini branch and bound
2155      2 set then use numberThreads for root cuts
2156      default is 0
2157  */
2158  int threadMode_;
2159 //@}
2160};
2161/// So we can use osiObject or CbcObject during transition
2162void getIntegerInformation(const OsiObject * object, double & originalLower,
2163                           double & originalUpper) ;
2164// So we can call from other programs
2165// Real main program
2166class OsiClpSolverInterface;
2167int CbcMain (int argc, const char *argv[],OsiClpSolverInterface & solver,CbcModel ** babSolver);
2168int CbcMain (int argc, const char *argv[],CbcModel & babSolver);
2169// four ways of calling
2170int callCbc(const char * input2, OsiClpSolverInterface& solver1); 
2171int callCbc(const char * input2);
2172int callCbc(const std::string input2, OsiClpSolverInterface& solver1); 
2173int callCbc(const std::string input2) ;
2174// When we want to load up CbcModel with options first
2175void CbcMain0 (CbcModel & babSolver);
2176int CbcMain1 (int argc, const char *argv[],CbcModel & babSolver);
2177// two ways of calling
2178int callCbc(const char * input2, CbcModel & babSolver); 
2179int callCbc(const std::string input2, CbcModel & babSolver); 
2180// And when CbcMain0 already called to initialize
2181int callCbc1(const char * input2, CbcModel & babSolver); 
2182int callCbc1(const std::string input2, CbcModel & babSolver); 
2183// And when CbcMain0 already called to initialize (with call back) (see CbcMain1 for whereFrom)
2184int callCbc1(const char * input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom)); 
2185int callCbc1(const std::string input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom)); 
2186int CbcMain1 (int argc, const char *argv[],CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2187// For uniform setting of cut and heuristic options
2188void setCutAndHeuristicOptions(CbcModel & model);
2189#endif
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