source: trunk/Cbc/src/CbcModel.hpp @ 1650

Last change on this file since 1650 was 1650, checked in by forrest, 9 years ago

messages for fathoming plus soem attempts at robustness

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1/* $Id: CbcModel.hpp 1650 2011-05-10 12:33:58Z forrest $ */
2// Copyright (C) 2002, International Business Machines
3// Corporation and others.  All Rights Reserved.
4// This code is licensed under the terms of the Eclipse Public License (EPL).
5
6#ifndef CbcModel_H
7#define CbcModel_H
8#include <string>
9#include <vector>
10#include "CoinMessageHandler.hpp"
11#include "OsiSolverInterface.hpp"
12#include "OsiBranchingObject.hpp"
13#include "OsiCuts.hpp"
14#include "CoinWarmStartBasis.hpp"
15#include "CbcCompareBase.hpp"
16#include "CbcMessage.hpp"
17#include "CbcEventHandler.hpp"
18#include "ClpDualRowPivot.hpp"
19
20//class OsiSolverInterface;
21
22class CbcCutGenerator;
23class CbcBaseModel;
24class OsiRowCut;
25class OsiBabSolver;
26class OsiRowCutDebugger;
27class CglCutGenerator;
28class CglStored;
29class CbcCutModifier;
30class CglTreeProbingInfo;
31class CbcHeuristic;
32class OsiObject;
33class CbcThread;
34class CbcTree;
35class CbcStrategy;
36class CbcFeasibilityBase;
37class CbcStatistics;
38class CbcEventHandler ;
39class CglPreProcess;
40# ifdef COIN_HAS_CLP
41class ClpNodeStuff;
42#endif
43// #define CBC_CHECK_BASIS 1
44
45//#############################################################################
46
47/** Simple Branch and bound class
48
49  The initialSolve() method solves the initial LP relaxation of the MIP
50  problem. The branchAndBound() method can then be called to finish using
51  a branch and cut algorithm.
52
53  <h3>Search Tree Traversal</h3>
54
55  Subproblems (aka nodes) requiring additional evaluation are stored using
56  the CbcNode and CbcNodeInfo objects. Ancestry linkage is maintained in the
57  CbcNodeInfo object. Evaluation of a subproblem within branchAndBound()
58  proceeds as follows:
59  <ul>
60    <li> The node representing the most promising parent subproblem is popped
61         from the heap which holds the set of subproblems requiring further
62         evaluation.
63    <li> Using branching instructions stored in the node, and information in
64         its ancestors, the model and solver are adjusted to create the
65         active subproblem.
66    <li> If the parent subproblem will require further evaluation
67         (<i>i.e.</i>, there are branches remaining) its node is pushed back
68         on the heap. Otherwise, the node is deleted.  This may trigger
69         recursive deletion of ancestors.
70    <li> The newly created subproblem is evaluated.
71    <li> If the subproblem requires further evaluation, a node is created.
72         All information needed to recreate the subproblem (branching
73         information, row and column cuts) is placed in the node and the node
74         is added to the set of subproblems awaiting further evaluation.
75  </ul>
76  Note that there is never a node representing the active subproblem; the model
77  and solver represent the active subproblem.
78
79  <h3>Row (Constraint) Cut Handling</h3>
80
81  For a typical subproblem, the sequence of events is as follows:
82  <ul>
83    <li> The subproblem is rebuilt for further evaluation: One result of a
84         call to addCuts() is a traversal of ancestors, leaving a list of all
85         cuts used in the ancestors in #addedCuts_. This list is then scanned
86         to construct a basis that includes only tight cuts. Entries for
87         loose cuts are set to NULL.
88    <li> The subproblem is evaluated: One result of a call to solveWithCuts()
89         is the return of a set of newly generated cuts for the subproblem.
90         #addedCuts_ is also kept up-to-date as old cuts become loose.
91    <li> The subproblem is stored for further processing: A call to
92         CbcNodeInfo::addCuts() adds the newly generated cuts to the
93         CbcNodeInfo object associated with this node.
94  </ul>
95  See CbcCountRowCut for details of the bookkeeping associated with cut
96  management.
97*/
98
99class CbcModel  {
100
101public:
102
103    enum CbcIntParam {
104        /** The maximum number of nodes before terminating */
105        CbcMaxNumNode = 0,
106        /** The maximum number of solutions before terminating */
107        CbcMaxNumSol,
108        /** Fathoming discipline
109
110          Controls objective function comparisons for purposes of fathoming by bound
111          or determining monotonic variables.
112
113          If 1, action is taken only when the current objective is strictly worse
114          than the target. Implementation is handled by adding a small tolerance to
115          the target.
116        */
117        CbcFathomDiscipline,
118        /** Adjusts printout
119            1 does different node message with number unsatisfied on last branch
120        */
121        CbcPrinting,
122        /** Number of branches (may be more than number of nodes as may
123            include strong branching) */
124        CbcNumberBranches,
125        /** Just a marker, so that a static sized array can store parameters. */
126        CbcLastIntParam
127    };
128
129    enum CbcDblParam {
130        /** The maximum amount the value of an integer variable can vary from
131            integer and still be considered feasible. */
132        CbcIntegerTolerance = 0,
133        /** The objective is assumed to worsen by this amount for each
134            integer infeasibility. */
135        CbcInfeasibilityWeight,
136        /** The amount by which to tighten the objective function cutoff when
137            a new solution is discovered. */
138        CbcCutoffIncrement,
139        /** Stop when the gap between the objective value of the best known solution
140          and the best bound on the objective of any solution is less than this.
141
142          This is an absolute value. Conversion from a percentage is left to the
143          client.
144        */
145        CbcAllowableGap,
146        /** Stop when the gap between the objective value of the best known solution
147          and the best bound on the objective of any solution is less than this
148          fraction of of the absolute value of best known solution.
149
150          Code stops if either this test or CbcAllowableGap test succeeds
151        */
152        CbcAllowableFractionGap,
153        /** \brief The maximum number of seconds before terminating.
154               A double should be adequate! */
155        CbcMaximumSeconds,
156        /// Cutoff - stored for speed
157        CbcCurrentCutoff,
158        /// Optimization direction - stored for speed
159        CbcOptimizationDirection,
160        /// Current objective value
161        CbcCurrentObjectiveValue,
162        /// Current minimization objective value
163        CbcCurrentMinimizationObjectiveValue,
164        /** \brief The time at start of model.
165               So that other pieces of code can access */
166        CbcStartSeconds,
167        /** Stop doing heuristics when the gap between the objective value of the
168            best known solution and the best bound on the objective of any solution
169            is less than this.
170
171          This is an absolute value. Conversion from a percentage is left to the
172          client.
173        */
174        CbcHeuristicGap,
175        /** Stop doing heuristics when the gap between the objective value of the
176            best known solution and the best bound on the objective of any solution
177            is less than this fraction of of the absolute value of best known
178            solution.
179
180          Code stops if either this test or CbcAllowableGap test succeeds
181        */
182        CbcHeuristicFractionGap,
183        /// Smallest non-zero change on a branch
184        CbcSmallestChange,
185        /// Sum of non-zero changes on a branch
186        CbcSumChange,
187        /// Largest non-zero change on a branch
188        CbcLargestChange,
189        /// Small non-zero change on a branch to be used as guess
190        CbcSmallChange,
191        /** Just a marker, so that a static sized array can store parameters. */
192        CbcLastDblParam
193    };
194
195    //---------------------------------------------------------------------------
196
197public:
198    ///@name Solve methods
199    //@{
200    /** \brief Solve the initial LP relaxation
201
202      Invoke the solver's %initialSolve() method.
203    */
204    void initialSolve();
205
206    /** \brief Invoke the branch \& cut algorithm
207
208      The method assumes that initialSolve() has been called to solve the
209      LP relaxation. It processes the root node, then proceeds to explore the
210      branch & cut search tree. The search ends when the tree is exhausted or
211      one of several execution limits is reached.
212      If doStatistics is 1 summary statistics are printed
213      if 2 then also the path to best solution (if found by branching)
214      if 3 then also one line per node
215    */
216    void branchAndBound(int doStatistics = 0);
217private:
218
219    /** \brief Evaluate a subproblem using cutting planes and heuristics
220
221      The method invokes a main loop which generates cuts, applies heuristics,
222      and reoptimises using the solver's native %resolve() method.
223      It returns true if the subproblem remains feasible at the end of the
224      evaluation.
225    */
226    bool solveWithCuts(OsiCuts & cuts, int numberTries, CbcNode * node);
227    /** Generate one round of cuts - serial mode
228      returns -
229      0 - normal
230      1 - must keep going
231      2 - set numberTries to zero
232      -1 - infeasible
233    */
234    int serialCuts(OsiCuts & cuts, CbcNode * node, OsiCuts & slackCuts, int lastNumberCuts);
235    /** Generate one round of cuts - parallel mode
236        returns -
237        0 - normal
238        1 - must keep going
239        2 - set numberTries to zero
240        -1 - infeasible
241    */
242    int parallelCuts(CbcBaseModel * master, OsiCuts & cuts, CbcNode * node, OsiCuts & slackCuts, int lastNumberCuts);
243    /** Input one node output N nodes to put on tree and optional solution update
244        This should be able to operate in parallel so is given a solver and is const(ish)
245        However we will need to keep an array of solver_ and bases and more
246        status is 0 for normal, 1 if solution
247        Calling code should always push nodes back on tree
248    */
249    CbcNode ** solveOneNode(int whichSolver, CbcNode * node,
250                            int & numberNodesOutput, int & status) ;
251    /// Update size of whichGenerator
252    void resizeWhichGenerator(int numberNow, int numberAfter);
253public:
254#ifdef CBC_KEEP_DEPRECATED
255    // See if anyone is using these any more!!
256    /** \brief create a clean model from partially fixed problem
257
258      The method creates a new model with given bounds and with no tree.
259    */
260    CbcModel *  cleanModel(const double * lower, const double * upper);
261    /** \brief Invoke the branch \& cut algorithm on partially fixed problem
262
263      The method presolves the given model and does branch and cut. The search
264      ends when the tree is exhausted or maximum nodes is reached.
265
266      If better solution found then it is saved.
267
268      Returns 0 if search completed and solution, 1 if not completed and solution,
269      2 if completed and no solution, 3 if not completed and no solution.
270
271      Normally okay to do cleanModel immediately followed by subBranchandBound
272      (== other form of subBranchAndBound)
273      but may need to get at model for advanced features.
274
275      Deletes model2
276    */
277    int subBranchAndBound(CbcModel * model2,
278                          CbcModel * presolvedModel,
279                          int maximumNodes);
280    /** \brief Invoke the branch \& cut algorithm on partially fixed problem
281
282      The method creates a new model with given bounds, presolves it
283      then proceeds to explore the branch & cut search tree. The search
284      ends when the tree is exhausted or maximum nodes is reached.
285
286      If better solution found then it is saved.
287
288      Returns 0 if search completed and solution, 1 if not completed and solution,
289      2 if completed and no solution, 3 if not completed and no solution.
290
291      This is just subModel immediately followed by other version of
292      subBranchandBound.
293
294    */
295    int subBranchAndBound(const double * lower, const double * upper,
296                          int maximumNodes);
297
298    /** \brief Process root node and return a strengthened model
299
300      The method assumes that initialSolve() has been called to solve the
301      LP relaxation. It processes the root node and then returns a pointer
302      to the strengthened model (or NULL if infeasible)
303    */
304    OsiSolverInterface *  strengthenedModel();
305    /** preProcess problem - replacing solver
306        If makeEquality true then <= cliques converted to ==.
307        Presolve will be done numberPasses times.
308
309        Returns NULL if infeasible
310
311        If makeEquality is 1 add slacks to get cliques,
312        if 2 add slacks to get sos (but only if looks plausible) and keep sos info
313    */
314    CglPreProcess * preProcess( int makeEquality = 0, int numberPasses = 5,
315                                int tuning = 5);
316    /** Does postprocessing - original solver back.
317        User has to delete process */
318    void postProcess(CglPreProcess * process);
319#endif
320    /// Adds an update information object
321    void addUpdateInformation(const CbcObjectUpdateData & data);
322    /** Do one node - broken out for clarity?
323        also for parallel (when baseModel!=this)
324        Returns 1 if solution found
325        node NULL on return if no branches left
326        newNode NULL if no new node created
327    */
328    int doOneNode(CbcModel * baseModel, CbcNode * & node, CbcNode * & newNode);
329
330public:
331    /** \brief Reoptimise an LP relaxation
332
333      Invoke the solver's %resolve() method.
334      whereFrom -
335      0 - initial continuous
336      1 - resolve on branch (before new cuts)
337      2 - after new cuts
338      3  - obsolete code or something modified problem in unexpected way
339      10 - after strong branching has fixed variables at root
340      11 - after strong branching has fixed variables in tree
341
342      returns 1 feasible, 0 infeasible, -1 feasible but skip cuts
343    */
344    int resolve(CbcNodeInfo * parent, int whereFrom,
345                double * saveSolution = NULL,
346                double * saveLower = NULL,
347                double * saveUpper = NULL);
348    /// Make given rows (L or G) into global cuts and remove from lp
349    void makeGlobalCuts(int numberRows, const int * which);
350    /// Make given cut into a global cut
351    void makeGlobalCut(const OsiRowCut * cut);
352    /// Make given cut into a global cut
353    void makeGlobalCut(const OsiRowCut & cut);
354    /// Make given column cut into a global cut
355    void makeGlobalCut(const OsiColCut * cut);
356    /// Make given column cut into a global cut
357    void makeGlobalCut(const OsiColCut & cut);
358    //@}
359
360    /** \name Presolve methods */
361    //@{
362
363    /** Identify cliques and construct corresponding objects.
364
365        Find cliques with size in the range
366        [\p atLeastThisMany, \p lessThanThis] and construct corresponding
367        CbcClique objects.
368        If \p makeEquality is true then a new model may be returned if
369        modifications had to be made, otherwise \c this is returned.
370        If the problem is infeasible #numberObjects_ is set to -1.
371        A client must use deleteObjects() before a second call to findCliques().
372        If priorities exist, clique priority is set to the default.
373    */
374    CbcModel * findCliques(bool makeEquality, int atLeastThisMany,
375                           int lessThanThis, int defaultValue = 1000);
376
377    /** Do integer presolve, creating a new (presolved) model.
378
379      Returns the new model, or NULL if feasibility is lost.
380      If weak is true then just does a normal presolve
381
382      \todo It remains to work out the cleanest way of getting a solution to
383            the original problem at the end. So this is very preliminary.
384     */
385    CbcModel * integerPresolve(bool weak = false);
386
387    /** Do integer presolve, modifying the current model.
388
389        Returns true if the model remains feasible after presolve.
390    */
391    bool integerPresolveThisModel(OsiSolverInterface * originalSolver, bool weak = false);
392
393
394    /// Put back information into the original model after integer presolve.
395    void originalModel(CbcModel * presolvedModel, bool weak);
396
397    /** \brief For variables involved in VUB constraints, see if we can tighten
398           bounds by solving lp's
399
400        Returns false if feasibility is lost.
401        If CglProbing is available, it will be tried as well to see if it can
402        tighten bounds.
403        This routine is just a front end for tightenVubs(int,const int*,double).
404
405        If <tt>type = -1</tt> all variables are processed (could be very slow).
406        If <tt>type = 0</tt> only variables involved in VUBs are processed.
407        If <tt>type = n > 0</tt>, only the n most expensive VUB variables
408        are processed, where it is assumed that x is at its maximum so delta
409        would have to go to 1 (if x not at bound).
410
411        If \p allowMultipleBinary is true, then a VUB constraint is a row with
412        one continuous variable and any number of binary variables.
413
414        If <tt>useCutoff < 1.0e30</tt>, the original objective is installed as a
415        constraint with \p useCutoff as a bound.
416    */
417    bool tightenVubs(int type, bool allowMultipleBinary = false,
418                     double useCutoff = 1.0e50);
419
420    /** \brief For variables involved in VUB constraints, see if we can tighten
421           bounds by solving lp's
422
423      This version is just handed a list of variables to be processed.
424    */
425    bool tightenVubs(int numberVubs, const int * which,
426                     double useCutoff = 1.0e50);
427    /**
428      Analyze problem to find a minimum change in the objective function.
429    */
430    void analyzeObjective();
431
432    /**
433      Add additional integers.
434    */
435    void AddIntegers();
436
437    /**
438      Save copy of the model.
439    */
440    void saveModel(OsiSolverInterface * saveSolver, double * checkCutoffForRestart, bool * feasible);
441
442    //@}
443
444    /** \name Object manipulation routines
445
446      See OsiObject for an explanation of `object' in the context of CbcModel.
447    */
448    //@{
449
450    /// Get the number of objects
451    inline int numberObjects() const {
452        return numberObjects_;
453    }
454    /// Set the number of objects
455    inline void setNumberObjects(int number) {
456        numberObjects_ = number;
457    }
458
459    /// Get the array of objects
460    inline OsiObject ** objects() const {
461        return object_;
462    }
463
464    /// Get the specified object
465    const inline OsiObject * object(int which) const {
466        return object_[which];
467    }
468    /// Get the specified object
469    inline OsiObject * modifiableObject(int which) const {
470        return object_[which];
471    }
472
473    void setOptionalInteger(int index);
474
475    /// Delete all object information (and just back to integers if true)
476    void deleteObjects(bool findIntegers = true);
477
478    /** Add in object information.
479
480      Objects are cloned; the owner can delete the originals.
481    */
482    void addObjects(int numberObjects, OsiObject ** objects);
483
484    /** Add in object information.
485
486      Objects are cloned; the owner can delete the originals.
487    */
488    void addObjects(int numberObjects, CbcObject ** objects);
489
490    /// Ensure attached objects point to this model.
491    void synchronizeModel() ;
492
493    /** \brief Identify integer variables and create corresponding objects.
494
495      Record integer variables and create an CbcSimpleInteger object for each
496      one.
497      If \p startAgain is true, a new scan is forced, overwriting any existing
498      integer variable information.
499      If type > 0 then 1==PseudoCost, 2 new ones low priority
500    */
501
502    void findIntegers(bool startAgain, int type = 0);
503
504    //@}
505
506    //---------------------------------------------------------------------------
507
508    /**@name Parameter set/get methods
509
510       The set methods return true if the parameter was set to the given value,
511       false if the value of the parameter is out of range.
512
513       The get methods return the value of the parameter.
514
515    */
516    //@{
517    /// Set an integer parameter
518    inline bool setIntParam(CbcIntParam key, int value) {
519        intParam_[key] = value;
520        return true;
521    }
522    /// Set a double parameter
523    inline bool setDblParam(CbcDblParam key, double value) {
524        dblParam_[key] = value;
525        return true;
526    }
527    /// Get an integer parameter
528    inline int getIntParam(CbcIntParam key) const {
529        return intParam_[key];
530    }
531    /// Get a double parameter
532    inline double getDblParam(CbcDblParam key) const {
533        return dblParam_[key];
534    }
535    /*! \brief Set cutoff bound on the objective function.
536
537      When using strict comparison, the bound is adjusted by a tolerance to
538      avoid accidentally cutting off the optimal solution.
539    */
540    void setCutoff(double value) ;
541
542    /// Get the cutoff bound on the objective function - always as minimize
543    inline double getCutoff() const { //double value ;
544        //solver_->getDblParam(OsiDualObjectiveLimit,value) ;
545        //assert( dblParam_[CbcCurrentCutoff]== value * solver_->getObjSense());
546        return dblParam_[CbcCurrentCutoff];
547    }
548
549    /// Set the \link CbcModel::CbcMaxNumNode maximum node limit \endlink
550    inline bool setMaximumNodes( int value) {
551        return setIntParam(CbcMaxNumNode, value);
552    }
553
554    /// Get the \link CbcModel::CbcMaxNumNode maximum node limit \endlink
555    inline int getMaximumNodes() const {
556        return getIntParam(CbcMaxNumNode);
557    }
558
559    /** Set the
560        \link CbcModel::CbcMaxNumSol maximum number of solutions \endlink
561        desired.
562    */
563    inline bool setMaximumSolutions( int value) {
564        return setIntParam(CbcMaxNumSol, value);
565    }
566    /** Get the
567        \link CbcModel::CbcMaxNumSol maximum number of solutions \endlink
568        desired.
569    */
570    inline int getMaximumSolutions() const {
571        return getIntParam(CbcMaxNumSol);
572    }
573    /// Set the printing mode
574    inline bool setPrintingMode( int value) {
575        return setIntParam(CbcPrinting, value);
576    }
577
578    /// Get the printing mode
579    inline int getPrintingMode() const {
580        return getIntParam(CbcPrinting);
581    }
582
583    /** Set the
584        \link CbcModel::CbcMaximumSeconds maximum number of seconds \endlink
585        desired.
586    */
587    inline bool setMaximumSeconds( double value) {
588        return setDblParam(CbcMaximumSeconds, value);
589    }
590    /** Get the
591        \link CbcModel::CbcMaximumSeconds maximum number of seconds \endlink
592        desired.
593    */
594    inline double getMaximumSeconds() const {
595        return getDblParam(CbcMaximumSeconds);
596    }
597    /// Current time since start of branchAndbound
598    double getCurrentSeconds() const ;
599
600    /// Return true if maximum time reached
601    bool maximumSecondsReached() const ;
602
603    /** Set the
604      \link CbcModel::CbcIntegerTolerance integrality tolerance \endlink
605    */
606    inline bool setIntegerTolerance( double value) {
607        return setDblParam(CbcIntegerTolerance, value);
608    }
609    /** Get the
610      \link CbcModel::CbcIntegerTolerance integrality tolerance \endlink
611    */
612    inline double getIntegerTolerance() const {
613        return getDblParam(CbcIntegerTolerance);
614    }
615
616    /** Set the
617        \link CbcModel::CbcInfeasibilityWeight
618          weight per integer infeasibility \endlink
619    */
620    inline bool setInfeasibilityWeight( double value) {
621        return setDblParam(CbcInfeasibilityWeight, value);
622    }
623    /** Get the
624        \link CbcModel::CbcInfeasibilityWeight
625          weight per integer infeasibility \endlink
626    */
627    inline double getInfeasibilityWeight() const {
628        return getDblParam(CbcInfeasibilityWeight);
629    }
630
631    /** Set the \link CbcModel::CbcAllowableGap allowable gap \endlink
632        between the best known solution and the best possible solution.
633    */
634    inline bool setAllowableGap( double value) {
635        return setDblParam(CbcAllowableGap, value);
636    }
637    /** Get the \link CbcModel::CbcAllowableGap allowable gap \endlink
638        between the best known solution and the best possible solution.
639    */
640    inline double getAllowableGap() const {
641        return getDblParam(CbcAllowableGap);
642    }
643
644    /** Set the \link CbcModel::CbcAllowableFractionGap fraction allowable gap \endlink
645        between the best known solution and the best possible solution.
646    */
647    inline bool setAllowableFractionGap( double value) {
648        return setDblParam(CbcAllowableFractionGap, value);
649    }
650    /** Get the \link CbcModel::CbcAllowableFractionGap fraction allowable gap \endlink
651        between the best known solution and the best possible solution.
652    */
653    inline double getAllowableFractionGap() const {
654        return getDblParam(CbcAllowableFractionGap);
655    }
656    /** Set the \link CbcModel::CbcAllowableFractionGap percentage allowable gap \endlink
657        between the best known solution and the best possible solution.
658    */
659    inline bool setAllowablePercentageGap( double value) {
660        return setDblParam(CbcAllowableFractionGap, value*0.01);
661    }
662    /** Get the \link CbcModel::CbcAllowableFractionGap percentage allowable gap \endlink
663        between the best known solution and the best possible solution.
664    */
665    inline double getAllowablePercentageGap() const {
666        return 100.0*getDblParam(CbcAllowableFractionGap);
667    }
668    /** Set the \link CbcModel::CbcHeuristicGap heuristic gap \endlink
669        between the best known solution and the best possible solution.
670    */
671    inline bool setHeuristicGap( double value) {
672        return setDblParam(CbcHeuristicGap, value);
673    }
674    /** Get the \link CbcModel::CbcHeuristicGap heuristic gap \endlink
675        between the best known solution and the best possible solution.
676    */
677    inline double getHeuristicGap() const {
678        return getDblParam(CbcHeuristicGap);
679    }
680
681    /** Set the \link CbcModel::CbcHeuristicFractionGap fraction heuristic gap \endlink
682        between the best known solution and the best possible solution.
683    */
684    inline bool setHeuristicFractionGap( double value) {
685        return setDblParam(CbcHeuristicFractionGap, value);
686    }
687    /** Get the \link CbcModel::CbcHeuristicFractionGap fraction heuristic gap \endlink
688        between the best known solution and the best possible solution.
689    */
690    inline double getHeuristicFractionGap() const {
691        return getDblParam(CbcHeuristicFractionGap);
692    }
693    /** Set the
694        \link CbcModel::CbcCutoffIncrement  \endlink
695        desired.
696    */
697    inline bool setCutoffIncrement( double value) {
698        return setDblParam(CbcCutoffIncrement, value);
699    }
700    /** Get the
701        \link CbcModel::CbcCutoffIncrement  \endlink
702        desired.
703    */
704    inline double getCutoffIncrement() const {
705        return getDblParam(CbcCutoffIncrement);
706    }
707
708    /** Pass in target solution and optional priorities.
709        If priorities then >0 means only branch if incorrect
710        while <0 means branch even if correct. +1 or -1 are
711        highest priority */
712    void setHotstartSolution(const double * solution, const int * priorities = NULL) ;
713
714    /// Set the minimum drop to continue cuts
715    inline void setMinimumDrop(double value) {
716        minimumDrop_ = value;
717    }
718    /// Get the minimum drop to continue cuts
719    inline double getMinimumDrop() const {
720        return minimumDrop_;
721    }
722
723    /** Set the maximum number of cut passes at root node (default 20)
724        Minimum drop can also be used for fine tuning */
725    inline void setMaximumCutPassesAtRoot(int value) {
726        maximumCutPassesAtRoot_ = value;
727    }
728    /** Get the maximum number of cut passes at root node */
729    inline int getMaximumCutPassesAtRoot() const {
730        return maximumCutPassesAtRoot_;
731    }
732
733    /** Set the maximum number of cut passes at other nodes (default 10)
734        Minimum drop can also be used for fine tuning */
735    inline void setMaximumCutPasses(int value) {
736        maximumCutPasses_ = value;
737    }
738    /** Get the maximum number of cut passes at other nodes (default 10) */
739    inline int getMaximumCutPasses() const {
740        return maximumCutPasses_;
741    }
742    /** Get current cut pass number in this round of cuts.
743        (1 is first pass) */
744    inline int getCurrentPassNumber() const {
745        return currentPassNumber_;
746    }
747
748    /** Set the maximum number of candidates to be evaluated for strong
749      branching.
750
751      A value of 0 disables strong branching.
752    */
753    void setNumberStrong(int number);
754    /** Get the maximum number of candidates to be evaluated for strong
755      branching.
756    */
757    inline int numberStrong() const {
758        return numberStrong_;
759    }
760    /** Set global preferred way to branch
761        -1 down, +1 up, 0 no preference */
762    inline void setPreferredWay(int value) {
763        preferredWay_ = value;
764    }
765    /** Get the preferred way to branch (default 0) */
766    inline int getPreferredWay() const {
767        return preferredWay_;
768    }
769    /// Get at which depths to do cuts
770    inline int whenCuts() const {
771        return whenCuts_;
772    }
773    /// Set at which depths to do cuts
774    inline void setWhenCuts(int value) {
775        whenCuts_ = value;
776    }
777    /** Return true if we want to do cuts
778        If allowForTopOfTree zero then just does on multiples of depth
779        if 1 then allows for doing at top of tree
780        if 2 then says if cuts allowed anywhere apart from root
781    */
782    bool doCutsNow(int allowForTopOfTree) const;
783
784    /** Set the number of branches before pseudo costs believed
785        in dynamic strong branching.
786
787      A value of 0 disables dynamic strong branching.
788    */
789    void setNumberBeforeTrust(int number);
790    /** get the number of branches before pseudo costs believed
791        in dynamic strong branching. */
792    inline int numberBeforeTrust() const {
793        return numberBeforeTrust_;
794    }
795    /** Set the number of variables for which to compute penalties
796        in dynamic strong branching.
797
798      A value of 0 disables penalties.
799    */
800    void setNumberPenalties(int number);
801    /** get the number of variables for which to compute penalties
802        in dynamic strong branching. */
803    inline int numberPenalties() const {
804        return numberPenalties_;
805    }
806    /// Number of analyze iterations to do
807    inline void setNumberAnalyzeIterations(int number) {
808        numberAnalyzeIterations_ = number;
809    }
810    inline int numberAnalyzeIterations() const {
811        return numberAnalyzeIterations_;
812    }
813    /** Get scale factor to make penalties match strong.
814        Should/will be computed */
815    inline double penaltyScaleFactor() const {
816        return penaltyScaleFactor_;
817    }
818    /** Set scale factor to make penalties match strong.
819        Should/will be computed */
820    void setPenaltyScaleFactor(double value);
821    /** Problem type as set by user or found by analysis.  This will be extended
822        0 - not known
823        1 - Set partitioning <=
824        2 - Set partitioning ==
825        3 - Set covering
826        4 - all +- 1 or all +1 and odd
827    */
828    void inline setProblemType(int number) {
829        problemType_ = number;
830    }
831    inline int problemType() const {
832        return problemType_;
833    }
834    /// Current depth
835    inline int currentDepth() const {
836        return currentDepth_;
837    }
838
839    /// Set how often to scan global cuts
840    void setHowOftenGlobalScan(int number);
841    /// Get how often to scan global cuts
842    inline int howOftenGlobalScan() const {
843        return howOftenGlobalScan_;
844    }
845    /// Original columns as created by integerPresolve or preprocessing
846    inline int * originalColumns() const {
847        return originalColumns_;
848    }
849    /// Set original columns as created by preprocessing
850    void setOriginalColumns(const int * originalColumns) ;
851
852    /** Set the print frequency.
853
854      Controls the number of nodes evaluated between status prints.
855      If <tt>number <=0</tt> the print frequency is set to 100 nodes for large
856      problems, 1000 for small problems.
857      Print frequency has very slight overhead if small.
858    */
859    inline void setPrintFrequency(int number) {
860        printFrequency_ = number;
861    }
862    /// Get the print frequency
863    inline int printFrequency() const {
864        return printFrequency_;
865    }
866    //@}
867
868    //---------------------------------------------------------------------------
869    ///@name Methods returning info on how the solution process terminated
870    //@{
871    /// Are there a numerical difficulties?
872    bool isAbandoned() const;
873    /// Is optimality proven?
874    bool isProvenOptimal() const;
875    /// Is  infeasiblity proven (or none better than cutoff)?
876    bool isProvenInfeasible() const;
877    /// Was continuous solution unbounded
878    bool isContinuousUnbounded() const;
879    /// Was continuous solution unbounded
880    bool isProvenDualInfeasible() const;
881    /// Node limit reached?
882    bool isNodeLimitReached() const;
883    /// Time limit reached?
884    bool isSecondsLimitReached() const;
885    /// Solution limit reached?
886    bool isSolutionLimitReached() const;
887    /// Get how many iterations it took to solve the problem.
888    inline int getIterationCount() const {
889        return numberIterations_;
890    }
891    /// Increment how many iterations it took to solve the problem.
892    inline void incrementIterationCount(int value) {
893        numberIterations_ += value;
894    }
895    /// Get how many Nodes it took to solve the problem.
896    inline int getNodeCount() const {
897        return numberNodes_;
898    }
899    /// Increment how many nodes it took to solve the problem.
900    inline void incrementNodeCount(int value) {
901        numberNodes_ += value;
902    }
903    /** Final status of problem
904        Some of these can be found out by is...... functions
905        -1 before branchAndBound
906        0 finished - check isProvenOptimal or isProvenInfeasible to see if solution found
907        (or check value of best solution)
908        1 stopped - on maxnodes, maxsols, maxtime
909        2 difficulties so run was abandoned
910        (5 event user programmed event occurred)
911    */
912    inline int status() const {
913        return status_;
914    }
915    inline void setProblemStatus(int value) {
916        status_ = value;
917    }
918    /** Secondary status of problem
919        -1 unset (status_ will also be -1)
920        0 search completed with solution
921        1 linear relaxation not feasible (or worse than cutoff)
922        2 stopped on gap
923        3 stopped on nodes
924        4 stopped on time
925        5 stopped on user event
926        6 stopped on solutions
927        7 linear relaxation unbounded
928    */
929    inline int secondaryStatus() const {
930        return secondaryStatus_;
931    }
932    inline void setSecondaryStatus(int value) {
933        secondaryStatus_ = value;
934    }
935    /// Are there numerical difficulties (for initialSolve) ?
936    bool isInitialSolveAbandoned() const ;
937    /// Is optimality proven (for initialSolve) ?
938    bool isInitialSolveProvenOptimal() const ;
939    /// Is primal infeasiblity proven (for initialSolve) ?
940    bool isInitialSolveProvenPrimalInfeasible() const ;
941    /// Is dual infeasiblity proven (for initialSolve) ?
942    bool isInitialSolveProvenDualInfeasible() const ;
943
944    //@}
945
946    //---------------------------------------------------------------------------
947    /**@name Problem information methods
948
949       These methods call the solver's query routines to return
950       information about the problem referred to by the current object.
951       Querying a problem that has no data associated with it result in
952       zeros for the number of rows and columns, and NULL pointers from
953       the methods that return vectors.
954
955       Const pointers returned from any data-query method are valid as
956       long as the data is unchanged and the solver is not called.
957    */
958    //@{
959    /// Number of rows in continuous (root) problem.
960    inline int numberRowsAtContinuous() const {
961        return numberRowsAtContinuous_;
962    }
963
964    /// Get number of columns
965    inline int getNumCols() const {
966        return solver_->getNumCols();
967    }
968
969    /// Get number of rows
970    inline int getNumRows() const {
971        return solver_->getNumRows();
972    }
973
974    /// Get number of nonzero elements
975    inline CoinBigIndex getNumElements() const {
976        return solver_->getNumElements();
977    }
978
979    /// Number of integers in problem
980    inline int numberIntegers() const {
981        return numberIntegers_;
982    }
983    // Integer variables
984    inline const int * integerVariable() const {
985        return integerVariable_;
986    }
987    /// Whether or not integer
988    inline char integerType(int i) const {
989        assert (integerInfo_);
990        assert (integerInfo_[i] == 0 || integerInfo_[i] == 1);
991        return integerInfo_[i];
992    }
993    /// Whether or not integer
994    inline const char * integerType() const {
995        return integerInfo_;
996    }
997
998    /// Get pointer to array[getNumCols()] of column lower bounds
999    inline const double * getColLower() const {
1000        return solver_->getColLower();
1001    }
1002
1003    /// Get pointer to array[getNumCols()] of column upper bounds
1004    inline const double * getColUpper() const {
1005        return solver_->getColUpper();
1006    }
1007
1008    /** Get pointer to array[getNumRows()] of row constraint senses.
1009        <ul>
1010        <li>'L': <= constraint
1011        <li>'E': =  constraint
1012        <li>'G': >= constraint
1013        <li>'R': ranged constraint
1014        <li>'N': free constraint
1015        </ul>
1016    */
1017    inline const char * getRowSense() const {
1018        return solver_->getRowSense();
1019    }
1020
1021    /** Get pointer to array[getNumRows()] of rows right-hand sides
1022        <ul>
1023        <li> if rowsense()[i] == 'L' then rhs()[i] == rowupper()[i]
1024        <li> if rowsense()[i] == 'G' then rhs()[i] == rowlower()[i]
1025        <li> if rowsense()[i] == 'R' then rhs()[i] == rowupper()[i]
1026        <li> if rowsense()[i] == 'N' then rhs()[i] == 0.0
1027        </ul>
1028    */
1029    inline const double * getRightHandSide() const {
1030        return solver_->getRightHandSide();
1031    }
1032
1033    /** Get pointer to array[getNumRows()] of row ranges.
1034        <ul>
1035        <li> if rowsense()[i] == 'R' then
1036        rowrange()[i] == rowupper()[i] - rowlower()[i]
1037        <li> if rowsense()[i] != 'R' then
1038        rowrange()[i] is 0.0
1039        </ul>
1040    */
1041    inline const double * getRowRange() const {
1042        return solver_->getRowRange();
1043    }
1044
1045    /// Get pointer to array[getNumRows()] of row lower bounds
1046    inline const double * getRowLower() const {
1047        return solver_->getRowLower();
1048    }
1049
1050    /// Get pointer to array[getNumRows()] of row upper bounds
1051    inline const double * getRowUpper() const {
1052        return solver_->getRowUpper();
1053    }
1054
1055    /// Get pointer to array[getNumCols()] of objective function coefficients
1056    inline const double * getObjCoefficients() const {
1057        return solver_->getObjCoefficients();
1058    }
1059
1060    /// Get objective function sense (1 for min (default), -1 for max)
1061    inline double getObjSense() const {
1062        //assert (dblParam_[CbcOptimizationDirection]== solver_->getObjSense());
1063        return dblParam_[CbcOptimizationDirection];
1064    }
1065
1066    /// Return true if variable is continuous
1067    inline bool isContinuous(int colIndex) const {
1068        return solver_->isContinuous(colIndex);
1069    }
1070
1071    /// Return true if variable is binary
1072    inline bool isBinary(int colIndex) const {
1073        return solver_->isBinary(colIndex);
1074    }
1075
1076    /** Return true if column is integer.
1077        Note: This function returns true if the the column
1078        is binary or a general integer.
1079    */
1080    inline bool isInteger(int colIndex) const {
1081        return solver_->isInteger(colIndex);
1082    }
1083
1084    /// Return true if variable is general integer
1085    inline bool isIntegerNonBinary(int colIndex) const {
1086        return solver_->isIntegerNonBinary(colIndex);
1087    }
1088
1089    /// Return true if variable is binary and not fixed at either bound
1090    inline bool isFreeBinary(int colIndex) const {
1091        return solver_->isFreeBinary(colIndex) ;
1092    }
1093
1094    /// Get pointer to row-wise copy of matrix
1095    inline const CoinPackedMatrix * getMatrixByRow() const {
1096        return solver_->getMatrixByRow();
1097    }
1098
1099    /// Get pointer to column-wise copy of matrix
1100    inline const CoinPackedMatrix * getMatrixByCol() const {
1101        return solver_->getMatrixByCol();
1102    }
1103
1104    /// Get solver's value for infinity
1105    inline double getInfinity() const {
1106        return solver_->getInfinity();
1107    }
1108    /// Get pointer to array[getNumCols()] (for speed) of column lower bounds
1109    inline const double * getCbcColLower() const {
1110        return cbcColLower_;
1111    }
1112    /// Get pointer to array[getNumCols()] (for speed) of column upper bounds
1113    inline const double * getCbcColUpper() const {
1114        return cbcColUpper_;
1115    }
1116    /// Get pointer to array[getNumRows()] (for speed) of row lower bounds
1117    inline const double * getCbcRowLower() const {
1118        return cbcRowLower_;
1119    }
1120    /// Get pointer to array[getNumRows()] (for speed) of row upper bounds
1121    inline const double * getCbcRowUpper() const {
1122        return cbcRowUpper_;
1123    }
1124    /// Get pointer to array[getNumCols()] (for speed) of primal solution vector
1125    inline const double * getCbcColSolution() const {
1126        return cbcColSolution_;
1127    }
1128    /// Get pointer to array[getNumRows()] (for speed) of dual prices
1129    inline const double * getCbcRowPrice() const {
1130        return cbcRowPrice_;
1131    }
1132    /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
1133    inline const double * getCbcReducedCost() const {
1134        return cbcReducedCost_;
1135    }
1136    /// Get pointer to array[getNumRows()] (for speed) of row activity levels.
1137    inline const double * getCbcRowActivity() const {
1138        return cbcRowActivity_;
1139    }
1140    //@}
1141
1142
1143    /**@name Methods related to querying the solution */
1144    //@{
1145    /// Holds solution at continuous (after cuts if branchAndBound called)
1146    inline double * continuousSolution() const {
1147        return continuousSolution_;
1148    }
1149    /** Array marked whenever a solution is found if non-zero.
1150        Code marks if heuristic returns better so heuristic
1151        need only mark if it wants to on solutions which
1152        are worse than current */
1153    inline int * usedInSolution() const {
1154        return usedInSolution_;
1155    }
1156    /// Increases usedInSolution for nonzeros
1157    void incrementUsed(const double * solution);
1158    /// Record a new incumbent solution and update objectiveValue
1159    void setBestSolution(CBC_Message how,
1160                         double & objectiveValue, const double *solution,
1161                         int fixVariables = 0);
1162    /// Just update objectiveValue
1163    void setBestObjectiveValue( double objectiveValue);
1164    /// Deals with event handler and solution
1165    CbcEventHandler::CbcAction dealWithEventHandler(CbcEventHandler::CbcEvent event,
1166            double objValue,
1167            const double * solution);
1168
1169    /** Call this to really test if a valid solution can be feasible
1170        Solution is number columns in size.
1171        If fixVariables true then bounds of continuous solver updated.
1172        Returns objective value (worse than cutoff if not feasible)
1173        Previously computed objective value is now passed in (in case user does not do solve)
1174    */
1175    double checkSolution(double cutoff, double * solution,
1176                         int fixVariables, double originalObjValue);
1177    /** Test the current solution for feasiblility.
1178
1179      Scan all objects for indications of infeasibility. This is broken down
1180      into simple integer infeasibility (\p numberIntegerInfeasibilities)
1181      and all other reports of infeasibility (\p numberObjectInfeasibilities).
1182    */
1183    bool feasibleSolution(int & numberIntegerInfeasibilities,
1184                          int & numberObjectInfeasibilities) const;
1185
1186    /** Solution to the most recent lp relaxation.
1187
1188      The solver's solution to the most recent lp relaxation.
1189    */
1190
1191    inline double * currentSolution() const {
1192        return currentSolution_;
1193    }
1194    /** For testing infeasibilities - will point to
1195        currentSolution_ or solver-->getColSolution()
1196    */
1197    inline const double * testSolution() const {
1198        return testSolution_;
1199    }
1200    inline void setTestSolution(const double * solution) {
1201        testSolution_ = solution;
1202    }
1203    /// Make sure region there and optionally copy solution
1204    void reserveCurrentSolution(const double * solution = NULL);
1205
1206    /// Get pointer to array[getNumCols()] of primal solution vector
1207    inline const double * getColSolution() const {
1208        return solver_->getColSolution();
1209    }
1210
1211    /// Get pointer to array[getNumRows()] of dual prices
1212    inline const double * getRowPrice() const {
1213        return solver_->getRowPrice();
1214    }
1215
1216    /// Get a pointer to array[getNumCols()] of reduced costs
1217    inline const double * getReducedCost() const {
1218        return solver_->getReducedCost();
1219    }
1220
1221    /// Get pointer to array[getNumRows()] of row activity levels.
1222    inline const double * getRowActivity() const {
1223        return solver_->getRowActivity();
1224    }
1225
1226    /// Get current objective function value
1227    inline double getCurrentObjValue() const {
1228        return dblParam_[CbcCurrentObjectiveValue];
1229    }
1230    /// Get current minimization objective function value
1231    inline double getCurrentMinimizationObjValue() const {
1232        return dblParam_[CbcCurrentMinimizationObjectiveValue];
1233    }
1234
1235    /// Get best objective function value as minimization
1236    inline double getMinimizationObjValue() const {
1237        return bestObjective_;
1238    }
1239    /// Set best objective function value as minimization
1240    inline void setMinimizationObjValue(double value) {
1241        bestObjective_ = value;
1242    }
1243
1244    /// Get best objective function value
1245    inline double getObjValue() const {
1246        return bestObjective_ * solver_->getObjSense() ;
1247    }
1248    /** Get best possible objective function value.
1249        This is better of best possible left on tree
1250        and best solution found.
1251        If called from within branch and cut may be optimistic.
1252    */
1253    double getBestPossibleObjValue() const;
1254    /// Set best objective function value
1255    inline void setObjValue(double value) {
1256        bestObjective_ = value * solver_->getObjSense() ;
1257    }
1258    /// Get solver objective function value (as minimization)
1259    inline double getSolverObjValue() const {
1260        return solver_->getObjValue() * solver_->getObjSense() ;
1261    }
1262
1263    /** The best solution to the integer programming problem.
1264
1265      The best solution to the integer programming problem found during
1266      the search. If no solution is found, the method returns null.
1267    */
1268
1269    inline double * bestSolution() const {
1270        return bestSolution_;
1271    }
1272    /** User callable setBestSolution.
1273        If check false does not check valid
1274        If true then sees if feasible and warns if objective value
1275        worse than given (so just set to COIN_DBL_MAX if you don't care).
1276        If check true then does not save solution if not feasible
1277    */
1278    void setBestSolution(const double * solution, int numberColumns,
1279                         double objectiveValue, bool check = false);
1280
1281    /// Get number of solutions
1282    inline int getSolutionCount() const {
1283        return numberSolutions_;
1284    }
1285
1286    /// Set number of solutions (so heuristics will be different)
1287    inline void setSolutionCount(int value) {
1288        numberSolutions_ = value;
1289    }
1290    /// Number of saved solutions (including best)
1291    int numberSavedSolutions() const;
1292    /// Maximum number of extra saved solutions
1293    inline int maximumSavedSolutions() const {
1294        return maximumSavedSolutions_;
1295    }
1296    /// Set maximum number of extra saved solutions
1297    void setMaximumSavedSolutions(int value);
1298    /// Return a saved solution (0==best) - NULL if off end
1299    const double * savedSolution(int which) const;
1300    /// Return a saved solution objective (0==best) - COIN_DBL_MAX if off end
1301    double savedSolutionObjective(int which) const;
1302
1303    /** Current phase (so heuristics etc etc can find out).
1304        0 - initial solve
1305        1 - solve with cuts at root
1306        2 - solve with cuts
1307        3 - other e.g. strong branching
1308        4 - trying to validate a solution
1309        5 - at end of search
1310    */
1311    inline int phase() const {
1312        return phase_;
1313    }
1314
1315    /// Get number of heuristic solutions
1316    inline int getNumberHeuristicSolutions() const {
1317        return numberHeuristicSolutions_;
1318    }
1319    /// Set number of heuristic solutions
1320    inline void setNumberHeuristicSolutions(int value) {
1321        numberHeuristicSolutions_ = value;
1322    }
1323
1324    /// Set objective function sense (1 for min (default), -1 for max,)
1325    inline void setObjSense(double s) {
1326        dblParam_[CbcOptimizationDirection] = s;
1327        solver_->setObjSense(s);
1328    }
1329
1330    /// Value of objective at continuous
1331    inline double getContinuousObjective() const {
1332        return originalContinuousObjective_;
1333    }
1334    inline void setContinuousObjective(double value) {
1335        originalContinuousObjective_ = value;
1336    }
1337    /// Number of infeasibilities at continuous
1338    inline int getContinuousInfeasibilities() const {
1339        return continuousInfeasibilities_;
1340    }
1341    inline void setContinuousInfeasibilities(int value) {
1342        continuousInfeasibilities_ = value;
1343    }
1344    /// Value of objective after root node cuts added
1345    inline double rootObjectiveAfterCuts() const {
1346        return continuousObjective_;
1347    }
1348    /// Sum of Changes to objective by first solve
1349    inline double sumChangeObjective() const {
1350        return sumChangeObjective1_;
1351    }
1352    /** Number of times global cuts violated.  When global cut pool then this
1353        should be kept for each cut and type of cut */
1354    inline int numberGlobalViolations() const {
1355        return numberGlobalViolations_;
1356    }
1357    inline void clearNumberGlobalViolations() {
1358        numberGlobalViolations_ = 0;
1359    }
1360    /// Whether to force a resolve after takeOffCuts
1361    inline bool resolveAfterTakeOffCuts() const {
1362        return resolveAfterTakeOffCuts_;
1363    }
1364    inline void setResolveAfterTakeOffCuts(bool yesNo) {
1365        resolveAfterTakeOffCuts_ = yesNo;
1366    }
1367    /// Maximum number of rows
1368    inline int maximumRows() const {
1369        return maximumRows_;
1370    }
1371    /// Work basis for temporary use
1372    inline CoinWarmStartBasis & workingBasis() {
1373        return workingBasis_;
1374    }
1375    /// Get number of "iterations" to stop after
1376    inline int getStopNumberIterations() const {
1377        return stopNumberIterations_;
1378    }
1379    /// Set number of "iterations" to stop after
1380    inline void setStopNumberIterations(int value) {
1381        stopNumberIterations_ = value;
1382    }
1383    //@}
1384
1385    /** \name Node selection */
1386    //@{
1387    // Comparison functions (which may be overridden by inheritance)
1388    inline CbcCompareBase * nodeComparison() const {
1389        return nodeCompare_;
1390    }
1391    void setNodeComparison(CbcCompareBase * compare);
1392    void setNodeComparison(CbcCompareBase & compare);
1393    //@}
1394
1395    /** \name Problem feasibility checking */
1396    //@{
1397    // Feasibility functions (which may be overridden by inheritance)
1398    inline CbcFeasibilityBase * problemFeasibility() const {
1399        return problemFeasibility_;
1400    }
1401    void setProblemFeasibility(CbcFeasibilityBase * feasibility);
1402    void setProblemFeasibility(CbcFeasibilityBase & feasibility);
1403    //@}
1404
1405    /** \name Tree methods and subtree methods */
1406    //@{
1407    /// Tree method e.g. heap (which may be overridden by inheritance)
1408    inline CbcTree * tree() const {
1409        return tree_;
1410    }
1411    /// For modifying tree handling (original is cloned)
1412    void passInTreeHandler(CbcTree & tree);
1413    /** For passing in an CbcModel to do a sub Tree (with derived tree handlers).
1414        Passed in model must exist for duration of branch and bound
1415    */
1416    void passInSubTreeModel(CbcModel & model);
1417    /** For retrieving a copy of subtree model with given OsiSolver.
1418        If no subtree model will use self (up to user to reset cutoff etc).
1419        If solver NULL uses current
1420    */
1421    CbcModel * subTreeModel(OsiSolverInterface * solver = NULL) const;
1422    /// Returns number of times any subtree stopped on nodes, time etc
1423    inline int numberStoppedSubTrees() const {
1424        return numberStoppedSubTrees_;
1425    }
1426    /// Says a sub tree was stopped
1427    inline void incrementSubTreeStopped() {
1428        numberStoppedSubTrees_++;
1429    }
1430    /** Whether to automatically do presolve before branch and bound (subTrees).
1431        0 - no
1432        1 - ordinary presolve
1433        2 - integer presolve (dodgy)
1434    */
1435    inline int typePresolve() const {
1436        return presolve_;
1437    }
1438    inline void setTypePresolve(int value) {
1439        presolve_ = value;
1440    }
1441
1442    //@}
1443
1444    /** \name Branching Decisions
1445
1446      See the CbcBranchDecision class for additional information.
1447    */
1448    //@{
1449
1450    /// Get the current branching decision method.
1451    inline CbcBranchDecision * branchingMethod() const {
1452        return branchingMethod_;
1453    }
1454    /// Set the branching decision method.
1455    inline void setBranchingMethod(CbcBranchDecision * method) {
1456        delete branchingMethod_;
1457        branchingMethod_ = method->clone();
1458    }
1459    /** Set the branching method
1460
1461      \overload
1462    */
1463    inline void setBranchingMethod(CbcBranchDecision & method) {
1464        delete branchingMethod_;
1465        branchingMethod_ = method.clone();
1466    }
1467    /// Get the current cut modifier method
1468    inline CbcCutModifier * cutModifier() const {
1469        return cutModifier_;
1470    }
1471    /// Set the cut modifier method
1472    void setCutModifier(CbcCutModifier * modifier);
1473    /** Set the cut modifier method
1474
1475      \overload
1476    */
1477    void setCutModifier(CbcCutModifier & modifier);
1478    //@}
1479
1480    /** \name Row (constraint) and Column (variable) cut generation */
1481    //@{
1482
1483    /** State of search
1484        0 - no solution
1485        1 - only heuristic solutions
1486        2 - branched to a solution
1487        3 - no solution but many nodes
1488    */
1489    inline int stateOfSearch() const {
1490        return stateOfSearch_;
1491    }
1492    inline void setStateOfSearch(int state) {
1493        stateOfSearch_ = state;
1494    }
1495    /// Strategy worked out - mainly at root node for use by CbcNode
1496    inline int searchStrategy() const {
1497        return searchStrategy_;
1498    }
1499    /// Set strategy worked out - mainly at root node for use by CbcNode
1500    inline void setSearchStrategy(int value) {
1501        searchStrategy_ = value;
1502    }
1503
1504    /// Get the number of cut generators
1505    inline int numberCutGenerators() const {
1506        return numberCutGenerators_;
1507    }
1508    /// Get the list of cut generators
1509    inline CbcCutGenerator ** cutGenerators() const {
1510        return generator_;
1511    }
1512    ///Get the specified cut generator
1513    inline CbcCutGenerator * cutGenerator(int i) const {
1514        return generator_[i];
1515    }
1516    ///Get the specified cut generator before any changes
1517    inline CbcCutGenerator * virginCutGenerator(int i) const {
1518        return virginGenerator_[i];
1519    }
1520    /** Add one generator - up to user to delete generators.
1521        howoften affects how generator is used. 0 or 1 means always,
1522        >1 means every that number of nodes.  Negative values have same
1523        meaning as positive but they may be switched off (-> -100) by code if
1524        not many cuts generated at continuous.  -99 is just done at root.
1525        Name is just for printout.
1526        If depth >0 overrides how often generator is called (if howOften==-1 or >0).
1527    */
1528    void addCutGenerator(CglCutGenerator * generator,
1529                         int howOften = 1, const char * name = NULL,
1530                         bool normal = true, bool atSolution = false,
1531                         bool infeasible = false, int howOftenInSub = -100,
1532                         int whatDepth = -1, int whatDepthInSub = -1);
1533//@}
1534    /** \name Strategy and sub models
1535
1536      See the CbcStrategy class for additional information.
1537    */
1538    //@{
1539
1540    /// Get the current strategy
1541    inline CbcStrategy * strategy() const {
1542        return strategy_;
1543    }
1544    /// Set the strategy. Clones
1545    void setStrategy(CbcStrategy & strategy);
1546    /// Set the strategy. assigns
1547    inline void setStrategy(CbcStrategy * strategy) {
1548        strategy_ = strategy;
1549    }
1550    /// Get the current parent model
1551    inline CbcModel * parentModel() const {
1552        return parentModel_;
1553    }
1554    /// Set the parent model
1555    inline void setParentModel(CbcModel & parentModel) {
1556        parentModel_ = &parentModel;
1557    }
1558    //@}
1559
1560
1561    /** \name Heuristics and priorities */
1562    //@{
1563    /*! \brief Add one heuristic - up to user to delete
1564
1565      The name is just used for print messages.
1566    */
1567    void addHeuristic(CbcHeuristic * generator, const char *name = NULL,
1568                      int before = -1);
1569    ///Get the specified heuristic
1570    inline CbcHeuristic * heuristic(int i) const {
1571        return heuristic_[i];
1572    }
1573    /// Get the number of heuristics
1574    inline int numberHeuristics() const {
1575        return numberHeuristics_;
1576    }
1577    /// Pointer to heuristic solver which found last solution (or NULL)
1578    inline CbcHeuristic * lastHeuristic() const {
1579        return lastHeuristic_;
1580    }
1581    /// set last heuristic which found a solution
1582    inline void setLastHeuristic(CbcHeuristic * last) {
1583        lastHeuristic_ = last;
1584    }
1585
1586    /** Pass in branching priorities.
1587
1588        If ifClique then priorities are on cliques otherwise priorities are
1589        on integer variables.
1590        Other type (if exists set to default)
1591        1 is highest priority. (well actually -INT_MAX is but that's ugly)
1592        If hotstart > 0 then branches are created to force
1593        the variable to the value given by best solution.  This enables a
1594        sort of hot start.  The node choice should be greatest depth
1595        and hotstart should normally be switched off after a solution.
1596
1597        If ifNotSimpleIntegers true then appended to normal integers
1598
1599        This is now deprecated except for simple usage.  If user
1600        creates Cbcobjects then set priority in them
1601
1602        \internal Added for Kurt Spielberg.
1603    */
1604    void passInPriorities(const int * priorities, bool ifNotSimpleIntegers);
1605
1606    /// Returns priority level for an object (or 1000 if no priorities exist)
1607    inline int priority(int sequence) const {
1608        return object_[sequence]->priority();
1609    }
1610
1611    /*! \brief Set an event handler
1612
1613      A clone of the handler passed as a parameter is stored in CbcModel.
1614    */
1615    void passInEventHandler(const CbcEventHandler *eventHandler) ;
1616
1617    /*! \brief Retrieve a pointer to the event handler */
1618    inline CbcEventHandler* getEventHandler() const {
1619        return (eventHandler_) ;
1620    }
1621
1622    //@}
1623
1624    /**@name Setting/Accessing application data */
1625    //@{
1626    /** Set application data.
1627
1628    This is a pointer that the application can store into and
1629    retrieve from the solver interface.
1630    This field is available for the application to optionally
1631    define and use.
1632    */
1633    void setApplicationData (void * appData);
1634
1635    /// Get application data
1636    void * getApplicationData() const;
1637    /**
1638        For advanced applications you may wish to modify the behavior of Cbc
1639        e.g. if the solver is a NLP solver then you may not have an exact
1640        optimum solution at each step.  Information could be built into
1641        OsiSolverInterface but this is an alternative so that that interface
1642        does not have to be changed.  If something similar is useful to
1643        enough solvers then it could be migrated
1644        You can also pass in by using solver->setAuxiliaryInfo.
1645        You should do that if solver is odd - if solver is normal simplex
1646        then use this.
1647        NOTE - characteristics are not cloned
1648    */
1649    void passInSolverCharacteristics(OsiBabSolver * solverCharacteristics);
1650    /// Get solver characteristics
1651    inline const OsiBabSolver * solverCharacteristics() const {
1652        return solverCharacteristics_;
1653    }
1654    //@}
1655
1656    //---------------------------------------------------------------------------
1657
1658    /**@name Message handling etc */
1659    //@{
1660    /// Pass in Message handler (not deleted at end)
1661    void passInMessageHandler(CoinMessageHandler * handler);
1662    /// Set language
1663    void newLanguage(CoinMessages::Language language);
1664    inline void setLanguage(CoinMessages::Language language) {
1665        newLanguage(language);
1666    }
1667    /// Return handler
1668    inline CoinMessageHandler * messageHandler() const {
1669        return handler_;
1670    }
1671    /// Return messages
1672    inline CoinMessages & messages() {
1673        return messages_;
1674    }
1675    /// Return pointer to messages
1676    inline CoinMessages * messagesPointer() {
1677        return &messages_;
1678    }
1679    /// Set log level
1680    void setLogLevel(int value);
1681    /// Get log level
1682    inline int logLevel() const {
1683        return handler_->logLevel();
1684    }
1685    /** Set flag to say if handler_ is the default handler.
1686
1687      The default handler is deleted when the model is deleted. Other
1688      handlers (supplied by the client) will not be deleted.
1689    */
1690    inline void setDefaultHandler(bool yesNo) {
1691        defaultHandler_ = yesNo;
1692    }
1693    //@}
1694    //---------------------------------------------------------------------------
1695    ///@name Specialized
1696    //@{
1697
1698    /**
1699        Set special options
1700        0 bit (1) - check if cuts valid (if on debugger list)
1701        1 bit (2) - use current basis to check integer solution (rather than all slack)
1702        2 bit (4) - don't check integer solution (by solving LP)
1703        3 bit (8) - fast analyze
1704        4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
1705        5 bit (32) - keep names
1706        6 bit (64) - try for dominated columns
1707        7 bit (128) - SOS type 1 but all declared integer
1708        8 bit (256) - Set to say solution just found, unset by doing cuts
1709        9 bit (512) - Try reduced model after 100 nodes
1710        10 bit (1024) - Switch on some heuristics even if seems unlikely
1711        11 bit (2048) - Mark as in small branch and bound
1712        12 bit (4096) - Funny cuts so do slow way (in some places)
1713        13 bit (8192) - Funny cuts so do slow way (in other places)
1714        14 bit (16384) - Use Cplex! for fathoming
1715        15 bit (32768) - Try reduced model after 0 nodes
1716        16 bit (65536) - Original model had integer bounds
1717        17 bit (131072) - Perturbation switched off
1718    */
1719    inline void setSpecialOptions(int value) {
1720        specialOptions_ = value;
1721    }
1722    /// Get special options
1723    inline int specialOptions() const {
1724        return specialOptions_;
1725    }
1726    /// Says if normal solver i.e. has well defined CoinPackedMatrix
1727    inline bool normalSolver() const {
1728        return (specialOptions_&16) == 0;
1729    }
1730    /** Set more special options
1731        at present bottom 6 bits used for shadow price mode
1732        1024 for experimental hotstart
1733        2048,4096 breaking out of cuts
1734        8192 slowly increase minimum drop
1735        16384 gomory
1736        32768 more heuristics in sub trees
1737        65536 no cuts in preprocessing
1738        131072 Time limits elapsed
1739    */
1740    inline void setMoreSpecialOptions(int value) {
1741        moreSpecialOptions_ = value;
1742    }
1743    /// Get more special options
1744    inline int moreSpecialOptions() const {
1745        return moreSpecialOptions_;
1746    }
1747  /// Set time method
1748    inline void setUseElapsedTime(bool yesNo) {
1749        if (yesNo)
1750          moreSpecialOptions_ |= 131072;
1751        else
1752          moreSpecialOptions_ &= ~131072;
1753    }
1754    /// Get time method
1755    inline bool useElapsedTime() const {
1756        return (moreSpecialOptions_&131072)!=0;
1757    }
1758    /// Go to dantzig pivot selection if easy problem (clp only)
1759#ifdef COIN_HAS_CLP
1760    void goToDantzig(int numberNodes, ClpDualRowPivot *& savePivotMethod);
1761#endif
1762    /// Now we may not own objects - just point to solver's objects
1763    inline bool ownObjects() const {
1764        return ownObjects_;
1765    }
1766    /// Check original model before it gets messed up
1767    void checkModel();
1768    //@}
1769    //---------------------------------------------------------------------------
1770
1771    ///@name Constructors and destructors etc
1772    //@{
1773    /// Default Constructor
1774    CbcModel();
1775
1776    /// Constructor from solver
1777    CbcModel(const OsiSolverInterface &);
1778
1779    /** Assign a solver to the model (model assumes ownership)
1780
1781      On return, \p solver will be NULL.
1782      If deleteSolver then current solver deleted (if model owned)
1783
1784      \note Parameter settings in the outgoing solver are not inherited by
1785        the incoming solver.
1786    */
1787    void assignSolver(OsiSolverInterface *&solver, bool deleteSolver = true);
1788
1789    /** \brief Set ownership of solver
1790
1791      A parameter of false tells CbcModel it does not own the solver and
1792      should not delete it. Once you claim ownership of the solver, you're
1793      responsible for eventually deleting it. Note that CbcModel clones
1794      solvers with abandon.  Unless you have a deep understanding of the
1795      workings of CbcModel, the only time you want to claim ownership is when
1796      you're about to delete the CbcModel object but want the solver to
1797      continue to exist (as, for example, when branchAndBound has finished
1798      and you want to hang on to the answer).
1799    */
1800    inline void setModelOwnsSolver (bool ourSolver) {
1801        ownership_ = ourSolver ? (ownership_ | 0x80000000) : (ownership_ & (~0x80000000)) ;
1802    }
1803
1804    /*! \brief Get ownership of solver
1805
1806      A return value of true means that CbcModel owns the solver and will
1807      take responsibility for deleting it when that becomes necessary.
1808    */
1809    inline bool modelOwnsSolver () {
1810        return ((ownership_&0x80000000) != 0) ;
1811    }
1812
1813    /** Copy constructor .
1814      If cloneHandler is true then message handler is cloned
1815    */
1816    CbcModel(const CbcModel & rhs, bool cloneHandler = false);
1817
1818    /// Assignment operator
1819    CbcModel & operator=(const CbcModel& rhs);
1820
1821    /// Destructor
1822    ~CbcModel ();
1823
1824    /// Returns solver - has current state
1825    inline OsiSolverInterface * solver() const {
1826        return solver_;
1827    }
1828
1829    /// Returns current solver - sets new one
1830    inline OsiSolverInterface * swapSolver(OsiSolverInterface * solver) {
1831        OsiSolverInterface * returnSolver = solver_;
1832        solver_ = solver;
1833        return returnSolver;
1834    }
1835
1836    /// Returns solver with continuous state
1837    inline OsiSolverInterface * continuousSolver() const {
1838        return continuousSolver_;
1839    }
1840
1841    /// Create solver with continuous state
1842    inline void createContinuousSolver() {
1843        continuousSolver_ = solver_->clone();
1844    }
1845    /// Clear solver with continuous state
1846    inline void clearContinuousSolver() {
1847        delete continuousSolver_;
1848        continuousSolver_ = NULL;
1849    }
1850
1851    /// A copy of the solver, taken at constructor or by saveReferenceSolver
1852    inline OsiSolverInterface * referenceSolver() const {
1853        return referenceSolver_;
1854    }
1855
1856    /// Save a copy of the current solver so can be reset to
1857    void saveReferenceSolver();
1858
1859    /** Uses a copy of reference solver to be current solver.
1860        Because of possible mismatches all exotic integer information is loat
1861        (apart from normal information in OsiSolverInterface)
1862        so SOS etc and priorities will have to be redone
1863    */
1864    void resetToReferenceSolver();
1865
1866    /// Clears out as much as possible (except solver)
1867    void gutsOfDestructor();
1868    /** Clears out enough to reset CbcModel as if no branch and bound done
1869     */
1870    void gutsOfDestructor2();
1871    /** Clears out enough to reset CbcModel cutoff etc
1872     */
1873    void resetModel();
1874    /** Most of copy constructor
1875        mode - 0 copy but don't delete before
1876               1 copy and delete before
1877           2 copy and delete before (but use virgin generators)
1878    */
1879    void gutsOfCopy(const CbcModel & rhs, int mode = 0);
1880    /// Move status, nodes etc etc across
1881    void moveInfo(const CbcModel & rhs);
1882    //@}
1883
1884    /// To do with threads
1885    //@{
1886    /// Get pointer to masterthread
1887    CbcThread * masterThread() const {
1888        return masterThread_;
1889    }
1890    /// Get pointer to walkback
1891    CbcNodeInfo ** walkback() const {
1892        return walkback_;
1893    }
1894    /// Get number of threads
1895    inline int getNumberThreads() const {
1896        return numberThreads_;
1897    }
1898    /// Set number of threads
1899    inline void setNumberThreads(int value) {
1900        numberThreads_ = value;
1901    }
1902    /// Get thread mode
1903    inline int getThreadMode() const {
1904        return threadMode_;
1905    }
1906    /** Set thread mode
1907        always use numberThreads for branching
1908        1 set then deterministic
1909        2 set then use numberThreads for root cuts
1910        4 set then use numberThreads in root mini branch and bound
1911        8 set and numberThreads - do heuristics numberThreads at a time
1912        8 set and numberThreads==0 do all heuristics at once
1913        default is 0
1914    */
1915    inline void setThreadMode(int value) {
1916        threadMode_ = value;
1917    }
1918    /** Return
1919        -2 if deterministic threaded and main thread
1920        -1 if deterministic threaded and serial thread
1921        0 if serial
1922        1 if opportunistic threaded
1923    */
1924    inline int parallelMode() const {
1925        if (!numberThreads_) {
1926            if ((threadMode_&1) == 0)
1927                return 0;
1928            else
1929                return -1;
1930            return 0;
1931        } else {
1932            if ((threadMode_&1) == 0)
1933                return 1;
1934            else
1935                return -2;
1936        }
1937    }
1938    /// From here to end of section - code in CbcThread.cpp until class changed
1939    /// Returns true if locked
1940    bool isLocked() const;
1941#ifdef CBC_THREAD
1942    /**
1943       Locks a thread if parallel so that stuff like cut pool
1944       can be updated and/or used.
1945    */
1946    void lockThread();
1947    /**
1948       Unlocks a thread if parallel to say cut pool stuff not needed
1949    */
1950    void unlockThread();
1951#else
1952    inline void lockThread() {}
1953    inline void unlockThread() {}
1954#endif
1955    /** Set information in a child
1956        -3 pass pointer to child thread info
1957        -2 just stop
1958        -1 delete simple child stuff
1959        0 delete opportunistic child stuff
1960        1 delete deterministic child stuff
1961    */
1962    void setInfoInChild(int type, CbcThread * info);
1963    /** Move/copy information from one model to another
1964        -1 - initialization
1965        0 - from base model
1966        1 - to base model (and reset)
1967        2 - add in final statistics etc (and reset so can do clean destruction)
1968    */
1969    void moveToModel(CbcModel * baseModel, int mode);
1970    /// Split up nodes
1971    int splitModel(int numberModels, CbcModel ** model,
1972                   int numberNodes);
1973    /// Start threads
1974    void startSplitModel(int numberIterations);
1975    /// Merge models
1976    void mergeModels(int numberModel, CbcModel ** model,
1977                     int numberNodes);
1978    //@}
1979
1980    /// semi-private i.e. users should not use
1981    //@{
1982    /// Get how many Nodes it took to solve the problem.
1983    int getNodeCount2() const {
1984        return numberNodes2_;
1985    }
1986    /// Set pointers for speed
1987    void setPointers(const OsiSolverInterface * solver);
1988    /** Perform reduced cost fixing
1989
1990      Fixes integer variables at their current value based on reduced cost
1991      penalties.  Returns number fixed
1992    */
1993    int reducedCostFix() ;
1994    /** Makes all handlers same.  If makeDefault 1 then makes top level
1995        default and rest point to that.  If 2 then each is copy
1996    */
1997    void synchronizeHandlers(int makeDefault);
1998    /// Save a solution to saved list
1999    void saveExtraSolution(const double * solution, double objectiveValue);
2000    /// Save a solution to best and move current to saved
2001    void saveBestSolution(const double * solution, double objectiveValue);
2002    /// Delete best and saved solutions
2003    void deleteSolutions();
2004    /// Encapsulates solver resolve
2005    int resolve(OsiSolverInterface * solver);
2006
2007    /** Encapsulates choosing a variable -
2008        anyAction -2, infeasible (-1 round again), 0 done
2009    */
2010    int chooseBranch(CbcNode * & newNode, int numberPassesLeft,
2011                     CbcNode * oldNode, OsiCuts & cuts,
2012                     bool & resolved, CoinWarmStartBasis *lastws,
2013                     const double * lowerBefore, const double * upperBefore,
2014                     OsiSolverBranch * & branches);
2015    int chooseBranch(CbcNode * newNode, int numberPassesLeft, bool & resolved);
2016
2017    /** Return an empty basis object of the specified size
2018
2019      A useful utility when constructing a basis for a subproblem from scratch.
2020      The object returned will be of the requested capacity and appropriate for
2021      the solver attached to the model.
2022    */
2023    CoinWarmStartBasis *getEmptyBasis(int ns = 0, int na = 0) const ;
2024
2025    /** Remove inactive cuts from the model
2026
2027      An OsiSolverInterface is expected to maintain a valid basis, but not a
2028      valid solution, when loose cuts are deleted. Restoring a valid solution
2029      requires calling the solver to reoptimise. If it's certain the solution
2030      will not be required, set allowResolve to false to suppress
2031      reoptimisation.
2032      If saveCuts then slack cuts will be saved
2033      On input current cuts are cuts and newCuts
2034      on exit current cuts will be correct.  Returns number dropped
2035    */
2036    int takeOffCuts(OsiCuts &cuts,
2037                    bool allowResolve, OsiCuts * saveCuts,
2038                    int numberNewCuts = 0, const OsiRowCut ** newCuts = NULL) ;
2039
2040    /** Determine and install the active cuts that need to be added for
2041      the current subproblem
2042
2043      The whole truth is a bit more complicated. The first action is a call to
2044      addCuts1(). addCuts() then sorts through the list, installs the tight
2045      cuts in the model, and does bookkeeping (adjusts reference counts).
2046      The basis returned from addCuts1() is adjusted accordingly.
2047
2048      If it turns out that the node should really be fathomed by bound,
2049      addCuts() simply treats all the cuts as loose as it does the bookkeeping.
2050
2051      canFix true if extra information being passed
2052    */
2053    int addCuts(CbcNode * node, CoinWarmStartBasis *&lastws, bool canFix);
2054
2055    /** Traverse the tree from node to root and prep the model
2056
2057      addCuts1() begins the job of prepping the model to match the current
2058      subproblem. The model is stripped of all cuts, and the search tree is
2059      traversed from node to root to determine the changes required. Appropriate
2060      bounds changes are installed, a list of cuts is collected but not
2061      installed, and an appropriate basis (minus the cuts, but big enough to
2062      accommodate them) is constructed.
2063
2064      Returns true if new problem similar to old
2065
2066      \todo addCuts1() is called in contexts where it's known in advance that
2067        all that's desired is to determine a list of cuts and do the
2068        bookkeeping (adjust the reference counts). The work of installing
2069        bounds and building a basis goes to waste.
2070    */
2071    bool addCuts1(CbcNode * node, CoinWarmStartBasis *&lastws);
2072    /** Returns bounds just before where - initially original bounds.
2073        Also sets downstream nodes (lower if force 1, upper if 2)
2074    */
2075    void previousBounds (CbcNode * node, CbcNodeInfo * where, int iColumn,
2076                         double & lower, double & upper, int force);
2077    /** Set objective value in a node.  This is separated out so that
2078       odd solvers can use.  It may look at extra information in
2079       solverCharacteriscs_ and will also use bound from parent node
2080    */
2081    void setObjectiveValue(CbcNode * thisNode, const CbcNode * parentNode) const;
2082
2083    /** If numberBeforeTrust >0 then we are going to use CbcBranchDynamic.
2084        Scan and convert CbcSimpleInteger objects
2085    */
2086    void convertToDynamic();
2087    /// Set numberBeforeTrust in all objects
2088    void synchronizeNumberBeforeTrust(int type = 0);
2089    /// Zap integer information in problem (may leave object info)
2090    void zapIntegerInformation(bool leaveObjects = true);
2091    /// Use cliques for pseudocost information - return nonzero if infeasible
2092    int cliquePseudoCosts(int doStatistics);
2093    /// Fill in useful estimates
2094    void pseudoShadow(int type);
2095    /** Return pseudo costs
2096        If not all integers or not pseudo costs - returns all zero
2097        Length of arrays are numberIntegers() and entries
2098        correspond to integerVariable()[i]
2099        User must allocate arrays before call
2100    */
2101    void fillPseudoCosts(double * downCosts, double * upCosts,
2102                         int * priority = NULL,
2103                         int * numberDown = NULL, int * numberUp = NULL,
2104                         int * numberDownInfeasible = NULL,
2105                         int * numberUpInfeasible = NULL) const;
2106    /** Do heuristics at root.
2107        0 - don't delete
2108        1 - delete
2109        2 - just delete - don't even use
2110    */
2111    void doHeuristicsAtRoot(int deleteHeuristicsAfterwards = 0);
2112    /// Adjust heuristics based on model
2113    void adjustHeuristics();
2114    /// Get the hotstart solution
2115    inline const double * hotstartSolution() const {
2116        return hotstartSolution_;
2117    }
2118    /// Get the hotstart priorities
2119    inline const int * hotstartPriorities() const {
2120        return hotstartPriorities_;
2121    }
2122
2123    /// Return the list of cuts initially collected for this subproblem
2124    inline CbcCountRowCut ** addedCuts() const {
2125        return addedCuts_;
2126    }
2127    /// Number of entries in the list returned by #addedCuts()
2128    inline int currentNumberCuts() const {
2129        return currentNumberCuts_;
2130    }
2131    /// Global cuts
2132    inline OsiCuts * globalCuts() {
2133        return &globalCuts_;
2134    }
2135    /// Copy and set a pointer to a row cut which will be added instead of normal branching.
2136    void setNextRowCut(const OsiRowCut & cut);
2137    /// Get a pointer to current node (be careful)
2138    inline CbcNode * currentNode() const {
2139        return currentNode_;
2140    }
2141    /// Get a pointer to probing info
2142    inline CglTreeProbingInfo * probingInfo() const {
2143        return probingInfo_;
2144    }
2145    /// Thread specific random number generator
2146    inline CoinThreadRandom * randomNumberGenerator() {
2147        return &randomNumberGenerator_;
2148    }
2149    /// Set the number of iterations done in strong branching.
2150    inline void setNumberStrongIterations(int number) {
2151        numberStrongIterations_ = number;
2152    }
2153    /// Get the number of iterations done in strong branching.
2154    inline int numberStrongIterations() const {
2155        return numberStrongIterations_;
2156    }
2157    /// Get maximum number of iterations (designed to be used in heuristics)
2158    inline int maximumNumberIterations() const {
2159        return maximumNumberIterations_;
2160    }
2161    /// Set maximum number of iterations (designed to be used in heuristics)
2162    inline void setMaximumNumberIterations(int value) {
2163        maximumNumberIterations_ = value;
2164    }
2165# ifdef COIN_HAS_CLP
2166    /// Set depth for fast nodes
2167    inline void setFastNodeDepth(int value) {
2168        fastNodeDepth_ = value;
2169    }
2170    /// Get depth for fast nodes
2171    inline int fastNodeDepth() const {
2172        return fastNodeDepth_;
2173    }
2174    /// Get anything with priority >= this can be treated as continuous
2175    inline int continuousPriority() const {
2176        return continuousPriority_;
2177    }
2178    /// Set anything with priority >= this can be treated as continuous
2179    inline void setContinuousPriority(int value) {
2180        continuousPriority_ = value;
2181    }
2182    inline void incrementExtra(int nodes, int iterations) {
2183        numberExtraNodes_ += nodes;
2184        numberExtraIterations_ += iterations;
2185    }
2186#endif
2187    /// Number of extra iterations
2188    inline int numberExtraIterations() const {
2189        return numberExtraIterations_;
2190    }
2191    /// Increment strong info
2192    void incrementStrongInfo(int numberTimes, int numberIterations,
2193                             int numberFixed, bool ifInfeasible);
2194    /// Return strong info
2195    inline const int * strongInfo() const {
2196        return strongInfo_;
2197    }
2198
2199    /// Return mutable strong info
2200    inline int * mutableStrongInfo() {
2201        return strongInfo_;
2202    }
2203    /// Get stored row cuts for donor/recipient CbcModel
2204    CglStored * storedRowCuts() const {
2205        return storedRowCuts_;
2206    }
2207    /// Set stored row cuts for donor/recipient CbcModel
2208    void setStoredRowCuts(CglStored * cuts) {
2209        storedRowCuts_ = cuts;
2210    }
2211    /// Says whether all dynamic integers
2212    inline bool allDynamic () const {
2213        return ((ownership_&0x40000000) != 0) ;
2214    }
2215    /// Create C++ lines to get to current state
2216    void generateCpp( FILE * fp, int options);
2217    /// Generate an OsiBranchingInformation object
2218    OsiBranchingInformation usefulInformation() const;
2219    /** Warm start object produced by heuristic or strong branching
2220
2221        If get a valid integer solution outside branch and bound then it can take
2222        a reasonable time to solve LP which produces clean solution.  If this object has
2223        any size then it will be used in solve.
2224    */
2225    inline void setBestSolutionBasis(const CoinWarmStartBasis & bestSolutionBasis) {
2226        bestSolutionBasis_ = bestSolutionBasis;
2227    }
2228    /// Redo walkback arrays
2229    void redoWalkBack();
2230    //@}
2231
2232//---------------------------------------------------------------------------
2233
2234private:
2235    ///@name Private member data
2236    //@{
2237
2238    /// The solver associated with this model.
2239    OsiSolverInterface * solver_;
2240
2241    /** Ownership of objects and other stuff
2242
2243        0x80000000 model owns solver
2244        0x40000000 all variables CbcDynamicPseudoCost
2245    */
2246    unsigned int ownership_ ;
2247
2248    /// A copy of the solver, taken at the continuous (root) node.
2249    OsiSolverInterface * continuousSolver_;
2250
2251    /// A copy of the solver, taken at constructor or by saveReferenceSolver
2252    OsiSolverInterface * referenceSolver_;
2253
2254    /// Message handler
2255    CoinMessageHandler * handler_;
2256
2257    /** Flag to say if handler_ is the default handler.
2258
2259      The default handler is deleted when the model is deleted. Other
2260      handlers (supplied by the client) will not be deleted.
2261    */
2262    bool defaultHandler_;
2263
2264    /// Cbc messages
2265    CoinMessages messages_;
2266
2267    /// Array for integer parameters
2268    int intParam_[CbcLastIntParam];
2269
2270    /// Array for double parameters
2271    double dblParam_[CbcLastDblParam];
2272
2273    /** Pointer to an empty warm start object
2274
2275      It turns out to be useful to have this available as a base from
2276      which to build custom warm start objects. This is typed as CoinWarmStart
2277      rather than CoinWarmStartBasis to allow for the possibility that a
2278      client might want to apply a solver that doesn't use a basis-based warm
2279      start. See getEmptyBasis for an example of how this field can be used.
2280    */
2281    mutable CoinWarmStart *emptyWarmStart_ ;
2282
2283    /// Best objective
2284    double bestObjective_;
2285    /// Best possible objective
2286    double bestPossibleObjective_;
2287    /// Sum of Changes to objective by first solve
2288    double sumChangeObjective1_;
2289    /// Sum of Changes to objective by subsequent solves
2290    double sumChangeObjective2_;
2291
2292    /// Array holding the incumbent (best) solution.
2293    double * bestSolution_;
2294    /// Arrays holding other solutions.
2295    double ** savedSolutions_;
2296
2297    /** Array holding the current solution.
2298
2299      This array is used more as a temporary.
2300    */
2301    double * currentSolution_;
2302    /** For testing infeasibilities - will point to
2303        currentSolution_ or solver-->getColSolution()
2304    */
2305    mutable const double * testSolution_;
2306    /** Warm start object produced by heuristic or strong branching
2307
2308        If get a valid integer solution outside branch and bound then it can take
2309        a reasonable time to solve LP which produces clean solution.  If this object has
2310        any size then it will be used in solve.
2311    */
2312    CoinWarmStartBasis bestSolutionBasis_ ;
2313    /// Global cuts
2314    OsiCuts globalCuts_;
2315
2316    /// Minimum degradation in objective value to continue cut generation
2317    double minimumDrop_;
2318    /// Number of solutions
2319    int numberSolutions_;
2320    /// Number of saved solutions
2321    int numberSavedSolutions_;
2322    /// Maximum number of saved solutions
2323    int maximumSavedSolutions_;
2324    /** State of search
2325        0 - no solution
2326        1 - only heuristic solutions
2327        2 - branched to a solution
2328        3 - no solution but many nodes
2329    */
2330    int stateOfSearch_;
2331    /// At which depths to do cuts
2332    int whenCuts_;
2333    /// Hotstart solution
2334    double * hotstartSolution_;
2335    /// Hotstart priorities
2336    int * hotstartPriorities_;
2337    /// Number of heuristic solutions
2338    int numberHeuristicSolutions_;
2339    /// Cumulative number of nodes
2340    int numberNodes_;
2341    /** Cumulative number of nodes for statistics.
2342        Must fix to match up
2343    */
2344    int numberNodes2_;
2345    /// Cumulative number of iterations
2346    int numberIterations_;
2347    /// Cumulative number of solves
2348    int numberSolves_;
2349    /// Status of problem - 0 finished, 1 stopped, 2 difficulties
2350    int status_;
2351    /** Secondary status of problem
2352        -1 unset (status_ will also be -1)
2353        0 search completed with solution
2354        1 linear relaxation not feasible (or worse than cutoff)
2355        2 stopped on gap
2356        3 stopped on nodes
2357        4 stopped on time
2358        5 stopped on user event
2359        6 stopped on solutions
2360     */
2361    int secondaryStatus_;
2362    /// Number of integers in problem
2363    int numberIntegers_;
2364    /// Number of rows at continuous
2365    int numberRowsAtContinuous_;
2366    /// Maximum number of cuts
2367    int maximumNumberCuts_;
2368    /** Current phase (so heuristics etc etc can find out).
2369        0 - initial solve
2370        1 - solve with cuts at root
2371        2 - solve with cuts
2372        3 - other e.g. strong branching
2373        4 - trying to validate a solution
2374        5 - at end of search
2375    */
2376    int phase_;
2377
2378    /// Number of entries in #addedCuts_
2379    int currentNumberCuts_;
2380
2381    /** Current limit on search tree depth
2382
2383      The allocated size of #walkback_. Increased as needed.
2384    */
2385    int maximumDepth_;
2386    /** Array used to assemble the path between a node and the search tree root
2387
2388      The array is resized when necessary. #maximumDepth_  is the current
2389      allocated size.
2390    */
2391    CbcNodeInfo ** walkback_;
2392    CbcNodeInfo ** lastNodeInfo_;
2393    const OsiRowCut ** lastCut_;
2394    int lastDepth_;
2395    int lastNumberCuts2_;
2396    int maximumCuts_;
2397    int * lastNumberCuts_;
2398
2399    /** The list of cuts initially collected for this subproblem
2400
2401      When the subproblem at this node is rebuilt, a set of cuts is collected
2402      for inclusion in the constraint system. If any of these cuts are
2403      subsequently removed because they have become loose, the corresponding
2404      entry is set to NULL.
2405    */
2406    CbcCountRowCut ** addedCuts_;
2407
2408    /** A pointer to a row cut which will be added instead of normal branching.
2409        After use it should be set to NULL.
2410    */
2411    OsiRowCut * nextRowCut_;
2412
2413    /// Current node so can be used elsewhere
2414    CbcNode * currentNode_;
2415
2416    /// Indices of integer variables
2417    int * integerVariable_;
2418    /// Whether of not integer
2419    char * integerInfo_;
2420    /// Holds solution at continuous (after cuts)
2421    double * continuousSolution_;
2422    /// Array marked whenever a solution is found if non-zero
2423    int * usedInSolution_;
2424    /**
2425        Special options
2426        0 bit (1) - check if cuts valid (if on debugger list)
2427        1 bit (2) - use current basis to check integer solution (rather than all slack)
2428        2 bit (4) - don't check integer solution (by solving LP)
2429        3 bit (8) - fast analyze
2430        4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
2431        5 bit (32) - keep names
2432        6 bit (64) - try for dominated columns
2433        7 bit (128) - SOS type 1 but all declared integer
2434        8 bit (256) - Set to say solution just found, unset by doing cuts
2435        9 bit (512) - Try reduced model after 100 nodes
2436        10 bit (1024) - Switch on some heuristics even if seems unlikely
2437        11 bit (2048) - Mark as in small branch and bound
2438        12 bit (4096) - Funny cuts so do slow way (in some places)
2439        13 bit (8192) - Funny cuts so do slow way (in other places)
2440        14 bit (16384) - Use Cplex! for fathoming
2441        15 bit (32768) - Try reduced model after 0 nodes
2442        16 bit (65536) - Original model had integer bounds
2443        17 bit (131072) - Perturbation switched off
2444        18 bit (262144) - donor CbcModel
2445        19 bit (524288) - recipient CbcModel
2446    */
2447    int specialOptions_;
2448    /** More special options
2449        at present bottom 6 bits used for shadow price mode
2450        1024 for experimental hotstart
2451        2048,4096 breaking out of cuts
2452        8192 slowly increase minimum drop
2453        16384 gomory
2454        32768 more heuristics in sub trees
2455        65536 no cuts in preprocessing
2456        131072 Time limits elapsed
2457        18 bit (262144) - Perturb fathom nodes
2458        19 bit (524288) - No limit on fathom nodes
2459    */
2460    int moreSpecialOptions_;
2461    /// User node comparison function
2462    CbcCompareBase * nodeCompare_;
2463    /// User feasibility function (see CbcFeasibleBase.hpp)
2464    CbcFeasibilityBase * problemFeasibility_;
2465    /// Tree
2466    CbcTree * tree_;
2467    /// A pointer to model to be used for subtrees
2468    CbcModel * subTreeModel_;
2469    /// Number of times any subtree stopped on nodes, time etc
2470    int numberStoppedSubTrees_;
2471    /// Variable selection function
2472    CbcBranchDecision * branchingMethod_;
2473    /// Cut modifier function
2474    CbcCutModifier * cutModifier_;
2475    /// Strategy
2476    CbcStrategy * strategy_;
2477    /// Parent model
2478    CbcModel * parentModel_;
2479    /** Whether to automatically do presolve before branch and bound.
2480        0 - no
2481        1 - ordinary presolve
2482        2 - integer presolve (dodgy)
2483    */
2484    /// Pointer to array[getNumCols()] (for speed) of column lower bounds
2485    const double * cbcColLower_;
2486    /// Pointer to array[getNumCols()] (for speed) of column upper bounds
2487    const double * cbcColUpper_;
2488    /// Pointer to array[getNumRows()] (for speed) of row lower bounds
2489    const double * cbcRowLower_;
2490    /// Pointer to array[getNumRows()] (for speed) of row upper bounds
2491    const double * cbcRowUpper_;
2492    /// Pointer to array[getNumCols()] (for speed) of primal solution vector
2493    const double * cbcColSolution_;
2494    /// Pointer to array[getNumRows()] (for speed) of dual prices
2495    const double * cbcRowPrice_;
2496    /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
2497    const double * cbcReducedCost_;
2498    /// Pointer to array[getNumRows()] (for speed) of row activity levels.
2499    const double * cbcRowActivity_;
2500    /// Pointer to user-defined data structure
2501    void * appData_;
2502    /// Presolve for CbcTreeLocal
2503    int presolve_;
2504    /** Maximum number of candidates to consider for strong branching.
2505      To disable strong branching, set this to 0.
2506    */
2507    int numberStrong_;
2508    /** \brief The number of branches before pseudo costs believed
2509           in dynamic strong branching.
2510
2511      A value of 0 is  off.
2512    */
2513    int numberBeforeTrust_;
2514    /** \brief The number of variables for which to compute penalties
2515           in dynamic strong branching.
2516    */
2517    int numberPenalties_;
2518    /// For threads - stop after this many "iterations"
2519    int stopNumberIterations_;
2520    /** Scale factor to make penalties match strong.
2521        Should/will be computed */
2522    double penaltyScaleFactor_;
2523    /// Number of analyze iterations to do
2524    int numberAnalyzeIterations_;
2525    /// Arrays with analysis results
2526    double * analyzeResults_;
2527    /// Number of nodes infeasible by normal branching (before cuts)
2528    int numberInfeasibleNodes_;
2529    /** Problem type as set by user or found by analysis.  This will be extended
2530        0 - not known
2531        1 - Set partitioning <=
2532        2 - Set partitioning ==
2533        3 - Set covering
2534    */
2535    int problemType_;
2536    /// Print frequency
2537    int printFrequency_;
2538    /// Number of cut generators
2539    int numberCutGenerators_;
2540    // Cut generators
2541    CbcCutGenerator ** generator_;
2542    // Cut generators before any changes
2543    CbcCutGenerator ** virginGenerator_;
2544    /// Number of heuristics
2545    int numberHeuristics_;
2546    /// Heuristic solvers
2547    CbcHeuristic ** heuristic_;
2548    /// Pointer to heuristic solver which found last solution (or NULL)
2549    CbcHeuristic * lastHeuristic_;
2550# ifdef COIN_HAS_CLP
2551    /// Depth for fast nodes
2552    int fastNodeDepth_;
2553#endif
2554    /*! Pointer to the event handler */
2555# ifdef CBC_ONLY_CLP
2556    ClpEventHandler *eventHandler_ ;
2557# else
2558    CbcEventHandler *eventHandler_ ;
2559# endif
2560
2561    /// Total number of objects
2562    int numberObjects_;
2563
2564    /** \brief Integer and Clique and ... information
2565
2566      \note The code assumes that the first objects on the list will be
2567        SimpleInteger objects for each integer variable, followed by
2568        Clique objects. Portions of the code that understand Clique objects
2569        will fail if they do not immediately follow the SimpleIntegers.
2570        Large chunks of the code will fail if the first objects are not
2571        SimpleInteger. As of 2003.08, SimpleIntegers and Cliques are the only
2572        objects.
2573    */
2574    OsiObject ** object_;
2575    /// Now we may not own objects - just point to solver's objects
2576    bool ownObjects_;
2577
2578    /// Original columns as created by integerPresolve or preprocessing
2579    int * originalColumns_;
2580    /// How often to scan global cuts
2581    int howOftenGlobalScan_;
2582    /** Number of times global cuts violated.  When global cut pool then this
2583        should be kept for each cut and type of cut */
2584    int numberGlobalViolations_;
2585    /// Number of extra iterations in fast lp
2586    int numberExtraIterations_;
2587    /// Number of extra nodes in fast lp
2588    int numberExtraNodes_;
2589    /** Value of objective at continuous
2590        (Well actually after initial round of cuts)
2591    */
2592    double continuousObjective_;
2593    /** Value of objective before root node cuts added
2594    */
2595    double originalContinuousObjective_;
2596    /// Number of infeasibilities at continuous
2597    int continuousInfeasibilities_;
2598    /// Maximum number of cut passes at root
2599    int maximumCutPassesAtRoot_;
2600    /// Maximum number of cut passes
2601    int maximumCutPasses_;
2602    /// Preferred way of branching
2603    int preferredWay_;
2604    /// Current cut pass number
2605    int currentPassNumber_;
2606    /// Maximum number of cuts (for whichGenerator_)
2607    int maximumWhich_;
2608    /// Maximum number of rows
2609    int maximumRows_;
2610    /// Current depth
2611    int currentDepth_;
2612    /// Thread specific random number generator
2613    mutable CoinThreadRandom randomNumberGenerator_;
2614    /// Work basis for temporary use
2615    CoinWarmStartBasis workingBasis_;
2616    /// Which cut generator generated this cut
2617    int * whichGenerator_;
2618    /// Maximum number of statistics
2619    int maximumStatistics_;
2620    /// statistics
2621    CbcStatistics ** statistics_;
2622    /// Maximum depth reached
2623    int maximumDepthActual_;
2624    /// Number of reduced cost fixings
2625    double numberDJFixed_;
2626    /// Probing info
2627    CglTreeProbingInfo * probingInfo_;
2628    /// Number of fixed by analyze at root
2629    int numberFixedAtRoot_;
2630    /// Number fixed by analyze so far
2631    int numberFixedNow_;
2632    /// Whether stopping on gap
2633    bool stoppedOnGap_;
2634    /// Whether event happened
2635    mutable bool eventHappened_;
2636    /// Number of long strong goes
2637    int numberLongStrong_;
2638    /// Number of old active cuts
2639    int numberOldActiveCuts_;
2640    /// Number of new cuts
2641    int numberNewCuts_;
2642    /// Strategy worked out - mainly at root node
2643    int searchStrategy_;
2644    /// Number of iterations in strong branching
2645    int numberStrongIterations_;
2646    /** 0 - number times strong branching done, 1 - number fixed, 2 - number infeasible
2647        Second group of three is a snapshot at node [6] */
2648    int strongInfo_[7];
2649    /**
2650        For advanced applications you may wish to modify the behavior of Cbc
2651        e.g. if the solver is a NLP solver then you may not have an exact
2652        optimum solution at each step.  This gives characteristics - just for one BAB.
2653        For actually saving/restoring a solution you need the actual solver one.
2654    */
2655    OsiBabSolver * solverCharacteristics_;
2656    /// Whether to force a resolve after takeOffCuts
2657    bool resolveAfterTakeOffCuts_;
2658    /// Maximum number of iterations (designed to be used in heuristics)
2659    int maximumNumberIterations_;
2660    /// Anything with priority >= this can be treated as continuous
2661    int continuousPriority_;
2662    /// Number of outstanding update information items
2663    int numberUpdateItems_;
2664    /// Maximum number of outstanding update information items
2665    int maximumNumberUpdateItems_;
2666    /// Update items
2667    CbcObjectUpdateData * updateItems_;
2668    /// Stored row cuts for donor/recipient CbcModel
2669    CglStored * storedRowCuts_;
2670    /**
2671       Parallel
2672       0 - off
2673       1 - testing
2674       2-99 threads
2675       other special meanings
2676    */
2677    int numberThreads_;
2678    /** thread mode
2679        always use numberThreads for branching
2680        1 set then deterministic
2681        2 set then use numberThreads for root cuts
2682        4 set then use numberThreads in root mini branch and bound
2683        default is 0
2684    */
2685    int threadMode_;
2686    /// Thread stuff for master
2687    CbcBaseModel * master_;
2688    /// Pointer to masterthread
2689    CbcThread * masterThread_;
2690//@}
2691};
2692/// So we can use osiObject or CbcObject during transition
2693void getIntegerInformation(const OsiObject * object, double & originalLower,
2694                           double & originalUpper) ;
2695// So we can call from other programs
2696// Real main program
2697class OsiClpSolverInterface;
2698int CbcMain (int argc, const char *argv[], OsiClpSolverInterface & solver, CbcModel ** babSolver);
2699int CbcMain (int argc, const char *argv[], CbcModel & babSolver);
2700// four ways of calling
2701int callCbc(const char * input2, OsiClpSolverInterface& solver1);
2702int callCbc(const char * input2);
2703int callCbc(const std::string input2, OsiClpSolverInterface& solver1);
2704int callCbc(const std::string input2) ;
2705// When we want to load up CbcModel with options first
2706void CbcMain0 (CbcModel & babSolver);
2707int CbcMain1 (int argc, const char *argv[], CbcModel & babSolver);
2708// two ways of calling
2709int callCbc(const char * input2, CbcModel & babSolver);
2710int callCbc(const std::string input2, CbcModel & babSolver);
2711// And when CbcMain0 already called to initialize
2712int callCbc1(const char * input2, CbcModel & babSolver);
2713int callCbc1(const std::string input2, CbcModel & babSolver);
2714// And when CbcMain0 already called to initialize (with call back) (see CbcMain1 for whereFrom)
2715int callCbc1(const char * input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2716int callCbc1(const std::string input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2717int CbcMain1 (int argc, const char *argv[], CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2718// For uniform setting of cut and heuristic options
2719void setCutAndHeuristicOptions(CbcModel & model);
2720#endif
2721
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