source: trunk/Cbc/src/CbcModel.hpp @ 1733

Last change on this file since 1733 was 1733, checked in by stefan, 8 years ago

merge chgset 1732 from stable/2.7: add CbcModel::getExtraNodeCount

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1/* $Id: CbcModel.hpp 1733 2011-09-25 15:40:30Z stefan $ */
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
21class CbcCutGenerator;
22class CbcBaseModel;
23class OsiRowCut;
24class OsiBabSolver;
25class OsiRowCutDebugger;
26class CglCutGenerator;
27class CglStored;
28class CbcCutModifier;
29class CglTreeProbingInfo;
30class CbcHeuristic;
31class OsiObject;
32class CbcThread;
33class CbcTree;
34class CbcStrategy;
35class CbcFeasibilityBase;
36class CbcStatistics;
37class CbcEventHandler ;
38class CglPreProcess;
39# ifdef COIN_HAS_CLP
40class OsiClpSolverInterface;
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    /// See if can stop on gap
708    bool canStopOnGap() const;
709
710    /** Pass in target solution and optional priorities.
711        If priorities then >0 means only branch if incorrect
712        while <0 means branch even if correct. +1 or -1 are
713        highest priority */
714    void setHotstartSolution(const double * solution, const int * priorities = NULL) ;
715
716    /// Set the minimum drop to continue cuts
717    inline void setMinimumDrop(double value) {
718        minimumDrop_ = value;
719    }
720    /// Get the minimum drop to continue cuts
721    inline double getMinimumDrop() const {
722        return minimumDrop_;
723    }
724
725    /** Set the maximum number of cut passes at root node (default 20)
726        Minimum drop can also be used for fine tuning */
727    inline void setMaximumCutPassesAtRoot(int value) {
728        maximumCutPassesAtRoot_ = value;
729    }
730    /** Get the maximum number of cut passes at root node */
731    inline int getMaximumCutPassesAtRoot() const {
732        return maximumCutPassesAtRoot_;
733    }
734
735    /** Set the maximum number of cut passes at other nodes (default 10)
736        Minimum drop can also be used for fine tuning */
737    inline void setMaximumCutPasses(int value) {
738        maximumCutPasses_ = value;
739    }
740    /** Get the maximum number of cut passes at other nodes (default 10) */
741    inline int getMaximumCutPasses() const {
742        return maximumCutPasses_;
743    }
744    /** Get current cut pass number in this round of cuts.
745        (1 is first pass) */
746    inline int getCurrentPassNumber() const {
747        return currentPassNumber_;
748    }
749
750    /** Set the maximum number of candidates to be evaluated for strong
751      branching.
752
753      A value of 0 disables strong branching.
754    */
755    void setNumberStrong(int number);
756    /** Get the maximum number of candidates to be evaluated for strong
757      branching.
758    */
759    inline int numberStrong() const {
760        return numberStrong_;
761    }
762    /** Set global preferred way to branch
763        -1 down, +1 up, 0 no preference */
764    inline void setPreferredWay(int value) {
765        preferredWay_ = value;
766    }
767    /** Get the preferred way to branch (default 0) */
768    inline int getPreferredWay() const {
769        return preferredWay_;
770    }
771    /// Get at which depths to do cuts
772    inline int whenCuts() const {
773        return whenCuts_;
774    }
775    /// Set at which depths to do cuts
776    inline void setWhenCuts(int value) {
777        whenCuts_ = value;
778    }
779    /** Return true if we want to do cuts
780        If allowForTopOfTree zero then just does on multiples of depth
781        if 1 then allows for doing at top of tree
782        if 2 then says if cuts allowed anywhere apart from root
783    */
784    bool doCutsNow(int allowForTopOfTree) const;
785
786    /** Set the number of branches before pseudo costs believed
787        in dynamic strong branching.
788
789      A value of 0 disables dynamic strong branching.
790    */
791    void setNumberBeforeTrust(int number);
792    /** get the number of branches before pseudo costs believed
793        in dynamic strong branching. */
794    inline int numberBeforeTrust() const {
795        return numberBeforeTrust_;
796    }
797    /** Set the number of variables for which to compute penalties
798        in dynamic strong branching.
799
800      A value of 0 disables penalties.
801    */
802    void setNumberPenalties(int number);
803    /** get the number of variables for which to compute penalties
804        in dynamic strong branching. */
805    inline int numberPenalties() const {
806        return numberPenalties_;
807    }
808    /// Number of analyze iterations to do
809    inline void setNumberAnalyzeIterations(int number) {
810        numberAnalyzeIterations_ = number;
811    }
812    inline int numberAnalyzeIterations() const {
813        return numberAnalyzeIterations_;
814    }
815    /** Get scale factor to make penalties match strong.
816        Should/will be computed */
817    inline double penaltyScaleFactor() const {
818        return penaltyScaleFactor_;
819    }
820    /** Set scale factor to make penalties match strong.
821        Should/will be computed */
822    void setPenaltyScaleFactor(double value);
823    /** Problem type as set by user or found by analysis.  This will be extended
824        0 - not known
825        1 - Set partitioning <=
826        2 - Set partitioning ==
827        3 - Set covering
828        4 - all +- 1 or all +1 and odd
829    */
830    void inline setProblemType(int number) {
831        problemType_ = number;
832    }
833    inline int problemType() const {
834        return problemType_;
835    }
836    /// Current depth
837    inline int currentDepth() const {
838        return currentDepth_;
839    }
840
841    /// Set how often to scan global cuts
842    void setHowOftenGlobalScan(int number);
843    /// Get how often to scan global cuts
844    inline int howOftenGlobalScan() const {
845        return howOftenGlobalScan_;
846    }
847    /// Original columns as created by integerPresolve or preprocessing
848    inline int * originalColumns() const {
849        return originalColumns_;
850    }
851    /// Set original columns as created by preprocessing
852    void setOriginalColumns(const int * originalColumns) ;
853
854    /** Set the print frequency.
855
856      Controls the number of nodes evaluated between status prints.
857      If <tt>number <=0</tt> the print frequency is set to 100 nodes for large
858      problems, 1000 for small problems.
859      Print frequency has very slight overhead if small.
860    */
861    inline void setPrintFrequency(int number) {
862        printFrequency_ = number;
863    }
864    /// Get the print frequency
865    inline int printFrequency() const {
866        return printFrequency_;
867    }
868    //@}
869
870    //---------------------------------------------------------------------------
871    ///@name Methods returning info on how the solution process terminated
872    //@{
873    /// Are there a numerical difficulties?
874    bool isAbandoned() const;
875    /// Is optimality proven?
876    bool isProvenOptimal() const;
877    /// Is  infeasiblity proven (or none better than cutoff)?
878    bool isProvenInfeasible() const;
879    /// Was continuous solution unbounded
880    bool isContinuousUnbounded() const;
881    /// Was continuous solution unbounded
882    bool isProvenDualInfeasible() const;
883    /// Node limit reached?
884    bool isNodeLimitReached() const;
885    /// Time limit reached?
886    bool isSecondsLimitReached() const;
887    /// Solution limit reached?
888    bool isSolutionLimitReached() const;
889    /// Get how many iterations it took to solve the problem.
890    inline int getIterationCount() const {
891        return numberIterations_;
892    }
893    /// Increment how many iterations it took to solve the problem.
894    inline void incrementIterationCount(int value) {
895        numberIterations_ += value;
896    }
897    /// Get how many Nodes it took to solve the problem (including those in complete fathoming B&B inside CLP).
898    inline int getNodeCount() const {
899        return numberNodes_;
900    }
901    /// Increment how many nodes it took to solve the problem.
902    inline void incrementNodeCount(int value) {
903        numberNodes_ += value;
904    }
905    /// Get how many Nodes were enumerated in complete fathoming B&B inside CLP
906    inline int getExtraNodeCount() const {
907       return numberExtraNodes_;
908    }
909    /** Final status of problem
910        Some of these can be found out by is...... functions
911        -1 before branchAndBound
912        0 finished - check isProvenOptimal or isProvenInfeasible to see if solution found
913        (or check value of best solution)
914        1 stopped - on maxnodes, maxsols, maxtime
915        2 difficulties so run was abandoned
916        (5 event user programmed event occurred)
917    */
918    inline int status() const {
919        return status_;
920    }
921    inline void setProblemStatus(int value) {
922        status_ = value;
923    }
924    /** Secondary status of problem
925        -1 unset (status_ will also be -1)
926        0 search completed with solution
927        1 linear relaxation not feasible (or worse than cutoff)
928        2 stopped on gap
929        3 stopped on nodes
930        4 stopped on time
931        5 stopped on user event
932        6 stopped on solutions
933        7 linear relaxation unbounded
934    */
935    inline int secondaryStatus() const {
936        return secondaryStatus_;
937    }
938    inline void setSecondaryStatus(int value) {
939        secondaryStatus_ = value;
940    }
941    /// Are there numerical difficulties (for initialSolve) ?
942    bool isInitialSolveAbandoned() const ;
943    /// Is optimality proven (for initialSolve) ?
944    bool isInitialSolveProvenOptimal() const ;
945    /// Is primal infeasiblity proven (for initialSolve) ?
946    bool isInitialSolveProvenPrimalInfeasible() const ;
947    /// Is dual infeasiblity proven (for initialSolve) ?
948    bool isInitialSolveProvenDualInfeasible() const ;
949
950    //@}
951
952    //---------------------------------------------------------------------------
953    /**@name Problem information methods
954
955       These methods call the solver's query routines to return
956       information about the problem referred to by the current object.
957       Querying a problem that has no data associated with it result in
958       zeros for the number of rows and columns, and NULL pointers from
959       the methods that return vectors.
960
961       Const pointers returned from any data-query method are valid as
962       long as the data is unchanged and the solver is not called.
963    */
964    //@{
965    /// Number of rows in continuous (root) problem.
966    inline int numberRowsAtContinuous() const {
967        return numberRowsAtContinuous_;
968    }
969
970    /// Get number of columns
971    inline int getNumCols() const {
972        return solver_->getNumCols();
973    }
974
975    /// Get number of rows
976    inline int getNumRows() const {
977        return solver_->getNumRows();
978    }
979
980    /// Get number of nonzero elements
981    inline CoinBigIndex getNumElements() const {
982        return solver_->getNumElements();
983    }
984
985    /// Number of integers in problem
986    inline int numberIntegers() const {
987        return numberIntegers_;
988    }
989    // Integer variables
990    inline const int * integerVariable() const {
991        return integerVariable_;
992    }
993    /// Whether or not integer
994    inline char integerType(int i) const {
995        assert (integerInfo_);
996        assert (integerInfo_[i] == 0 || integerInfo_[i] == 1);
997        return integerInfo_[i];
998    }
999    /// Whether or not integer
1000    inline const char * integerType() const {
1001        return integerInfo_;
1002    }
1003
1004    /// Get pointer to array[getNumCols()] of column lower bounds
1005    inline const double * getColLower() const {
1006        return solver_->getColLower();
1007    }
1008
1009    /// Get pointer to array[getNumCols()] of column upper bounds
1010    inline const double * getColUpper() const {
1011        return solver_->getColUpper();
1012    }
1013
1014    /** Get pointer to array[getNumRows()] of row constraint senses.
1015        <ul>
1016        <li>'L': <= constraint
1017        <li>'E': =  constraint
1018        <li>'G': >= constraint
1019        <li>'R': ranged constraint
1020        <li>'N': free constraint
1021        </ul>
1022    */
1023    inline const char * getRowSense() const {
1024        return solver_->getRowSense();
1025    }
1026
1027    /** Get pointer to array[getNumRows()] of rows right-hand sides
1028        <ul>
1029        <li> if rowsense()[i] == 'L' then rhs()[i] == rowupper()[i]
1030        <li> if rowsense()[i] == 'G' then rhs()[i] == rowlower()[i]
1031        <li> if rowsense()[i] == 'R' then rhs()[i] == rowupper()[i]
1032        <li> if rowsense()[i] == 'N' then rhs()[i] == 0.0
1033        </ul>
1034    */
1035    inline const double * getRightHandSide() const {
1036        return solver_->getRightHandSide();
1037    }
1038
1039    /** Get pointer to array[getNumRows()] of row ranges.
1040        <ul>
1041        <li> if rowsense()[i] == 'R' then
1042        rowrange()[i] == rowupper()[i] - rowlower()[i]
1043        <li> if rowsense()[i] != 'R' then
1044        rowrange()[i] is 0.0
1045        </ul>
1046    */
1047    inline const double * getRowRange() const {
1048        return solver_->getRowRange();
1049    }
1050
1051    /// Get pointer to array[getNumRows()] of row lower bounds
1052    inline const double * getRowLower() const {
1053        return solver_->getRowLower();
1054    }
1055
1056    /// Get pointer to array[getNumRows()] of row upper bounds
1057    inline const double * getRowUpper() const {
1058        return solver_->getRowUpper();
1059    }
1060
1061    /// Get pointer to array[getNumCols()] of objective function coefficients
1062    inline const double * getObjCoefficients() const {
1063        return solver_->getObjCoefficients();
1064    }
1065
1066    /// Get objective function sense (1 for min (default), -1 for max)
1067    inline double getObjSense() const {
1068        //assert (dblParam_[CbcOptimizationDirection]== solver_->getObjSense());
1069        return dblParam_[CbcOptimizationDirection];
1070    }
1071
1072    /// Return true if variable is continuous
1073    inline bool isContinuous(int colIndex) const {
1074        return solver_->isContinuous(colIndex);
1075    }
1076
1077    /// Return true if variable is binary
1078    inline bool isBinary(int colIndex) const {
1079        return solver_->isBinary(colIndex);
1080    }
1081
1082    /** Return true if column is integer.
1083        Note: This function returns true if the the column
1084        is binary or a general integer.
1085    */
1086    inline bool isInteger(int colIndex) const {
1087        return solver_->isInteger(colIndex);
1088    }
1089
1090    /// Return true if variable is general integer
1091    inline bool isIntegerNonBinary(int colIndex) const {
1092        return solver_->isIntegerNonBinary(colIndex);
1093    }
1094
1095    /// Return true if variable is binary and not fixed at either bound
1096    inline bool isFreeBinary(int colIndex) const {
1097        return solver_->isFreeBinary(colIndex) ;
1098    }
1099
1100    /// Get pointer to row-wise copy of matrix
1101    inline const CoinPackedMatrix * getMatrixByRow() const {
1102        return solver_->getMatrixByRow();
1103    }
1104
1105    /// Get pointer to column-wise copy of matrix
1106    inline const CoinPackedMatrix * getMatrixByCol() const {
1107        return solver_->getMatrixByCol();
1108    }
1109
1110    /// Get solver's value for infinity
1111    inline double getInfinity() const {
1112        return solver_->getInfinity();
1113    }
1114    /// Get pointer to array[getNumCols()] (for speed) of column lower bounds
1115    inline const double * getCbcColLower() const {
1116        return cbcColLower_;
1117    }
1118    /// Get pointer to array[getNumCols()] (for speed) of column upper bounds
1119    inline const double * getCbcColUpper() const {
1120        return cbcColUpper_;
1121    }
1122    /// Get pointer to array[getNumRows()] (for speed) of row lower bounds
1123    inline const double * getCbcRowLower() const {
1124        return cbcRowLower_;
1125    }
1126    /// Get pointer to array[getNumRows()] (for speed) of row upper bounds
1127    inline const double * getCbcRowUpper() const {
1128        return cbcRowUpper_;
1129    }
1130    /// Get pointer to array[getNumCols()] (for speed) of primal solution vector
1131    inline const double * getCbcColSolution() const {
1132        return cbcColSolution_;
1133    }
1134    /// Get pointer to array[getNumRows()] (for speed) of dual prices
1135    inline const double * getCbcRowPrice() const {
1136        return cbcRowPrice_;
1137    }
1138    /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
1139    inline const double * getCbcReducedCost() const {
1140        return cbcReducedCost_;
1141    }
1142    /// Get pointer to array[getNumRows()] (for speed) of row activity levels.
1143    inline const double * getCbcRowActivity() const {
1144        return cbcRowActivity_;
1145    }
1146    //@}
1147
1148
1149    /**@name Methods related to querying the solution */
1150    //@{
1151    /// Holds solution at continuous (after cuts if branchAndBound called)
1152    inline double * continuousSolution() const {
1153        return continuousSolution_;
1154    }
1155    /** Array marked whenever a solution is found if non-zero.
1156        Code marks if heuristic returns better so heuristic
1157        need only mark if it wants to on solutions which
1158        are worse than current */
1159    inline int * usedInSolution() const {
1160        return usedInSolution_;
1161    }
1162    /// Increases usedInSolution for nonzeros
1163    void incrementUsed(const double * solution);
1164    /// Record a new incumbent solution and update objectiveValue
1165    void setBestSolution(CBC_Message how,
1166                         double & objectiveValue, const double *solution,
1167                         int fixVariables = 0);
1168    /// Just update objectiveValue
1169    void setBestObjectiveValue( double objectiveValue);
1170    /// Deals with event handler and solution
1171    CbcEventHandler::CbcAction dealWithEventHandler(CbcEventHandler::CbcEvent event,
1172            double objValue,
1173            const double * solution);
1174
1175    /** Call this to really test if a valid solution can be feasible
1176        Solution is number columns in size.
1177        If fixVariables true then bounds of continuous solver updated.
1178        Returns objective value (worse than cutoff if not feasible)
1179        Previously computed objective value is now passed in (in case user does not do solve)
1180    */
1181    double checkSolution(double cutoff, double * solution,
1182                         int fixVariables, double originalObjValue);
1183    /** Test the current solution for feasiblility.
1184
1185      Scan all objects for indications of infeasibility. This is broken down
1186      into simple integer infeasibility (\p numberIntegerInfeasibilities)
1187      and all other reports of infeasibility (\p numberObjectInfeasibilities).
1188    */
1189    bool feasibleSolution(int & numberIntegerInfeasibilities,
1190                          int & numberObjectInfeasibilities) const;
1191
1192    /** Solution to the most recent lp relaxation.
1193
1194      The solver's solution to the most recent lp relaxation.
1195    */
1196
1197    inline double * currentSolution() const {
1198        return currentSolution_;
1199    }
1200    /** For testing infeasibilities - will point to
1201        currentSolution_ or solver-->getColSolution()
1202    */
1203    inline const double * testSolution() const {
1204        return testSolution_;
1205    }
1206    inline void setTestSolution(const double * solution) {
1207        testSolution_ = solution;
1208    }
1209    /// Make sure region there and optionally copy solution
1210    void reserveCurrentSolution(const double * solution = NULL);
1211
1212    /// Get pointer to array[getNumCols()] of primal solution vector
1213    inline const double * getColSolution() const {
1214        return solver_->getColSolution();
1215    }
1216
1217    /// Get pointer to array[getNumRows()] of dual prices
1218    inline const double * getRowPrice() const {
1219        return solver_->getRowPrice();
1220    }
1221
1222    /// Get a pointer to array[getNumCols()] of reduced costs
1223    inline const double * getReducedCost() const {
1224        return solver_->getReducedCost();
1225    }
1226
1227    /// Get pointer to array[getNumRows()] of row activity levels.
1228    inline const double * getRowActivity() const {
1229        return solver_->getRowActivity();
1230    }
1231
1232    /// Get current objective function value
1233    inline double getCurrentObjValue() const {
1234        return dblParam_[CbcCurrentObjectiveValue];
1235    }
1236    /// Get current minimization objective function value
1237    inline double getCurrentMinimizationObjValue() const {
1238        return dblParam_[CbcCurrentMinimizationObjectiveValue];
1239    }
1240
1241    /// Get best objective function value as minimization
1242    inline double getMinimizationObjValue() const {
1243        return bestObjective_;
1244    }
1245    /// Set best objective function value as minimization
1246    inline void setMinimizationObjValue(double value) {
1247        bestObjective_ = value;
1248    }
1249
1250    /// Get best objective function value
1251    inline double getObjValue() const {
1252        return bestObjective_ * solver_->getObjSense() ;
1253    }
1254    /** Get best possible objective function value.
1255        This is better of best possible left on tree
1256        and best solution found.
1257        If called from within branch and cut may be optimistic.
1258    */
1259    double getBestPossibleObjValue() const;
1260    /// Set best objective function value
1261    inline void setObjValue(double value) {
1262        bestObjective_ = value * solver_->getObjSense() ;
1263    }
1264    /// Get solver objective function value (as minimization)
1265    inline double getSolverObjValue() const {
1266        return solver_->getObjValue() * solver_->getObjSense() ;
1267    }
1268
1269    /** The best solution to the integer programming problem.
1270
1271      The best solution to the integer programming problem found during
1272      the search. If no solution is found, the method returns null.
1273    */
1274
1275    inline double * bestSolution() const {
1276        return bestSolution_;
1277    }
1278    /** User callable setBestSolution.
1279        If check false does not check valid
1280        If true then sees if feasible and warns if objective value
1281        worse than given (so just set to COIN_DBL_MAX if you don't care).
1282        If check true then does not save solution if not feasible
1283    */
1284    void setBestSolution(const double * solution, int numberColumns,
1285                         double objectiveValue, bool check = false);
1286
1287    /// Get number of solutions
1288    inline int getSolutionCount() const {
1289        return numberSolutions_;
1290    }
1291
1292    /// Set number of solutions (so heuristics will be different)
1293    inline void setSolutionCount(int value) {
1294        numberSolutions_ = value;
1295    }
1296    /// Number of saved solutions (including best)
1297    int numberSavedSolutions() const;
1298    /// Maximum number of extra saved solutions
1299    inline int maximumSavedSolutions() const {
1300        return maximumSavedSolutions_;
1301    }
1302    /// Set maximum number of extra saved solutions
1303    void setMaximumSavedSolutions(int value);
1304    /// Return a saved solution (0==best) - NULL if off end
1305    const double * savedSolution(int which) const;
1306    /// Return a saved solution objective (0==best) - COIN_DBL_MAX if off end
1307    double savedSolutionObjective(int which) const;
1308
1309    /** Current phase (so heuristics etc etc can find out).
1310        0 - initial solve
1311        1 - solve with cuts at root
1312        2 - solve with cuts
1313        3 - other e.g. strong branching
1314        4 - trying to validate a solution
1315        5 - at end of search
1316    */
1317    inline int phase() const {
1318        return phase_;
1319    }
1320
1321    /// Get number of heuristic solutions
1322    inline int getNumberHeuristicSolutions() const {
1323        return numberHeuristicSolutions_;
1324    }
1325    /// Set number of heuristic solutions
1326    inline void setNumberHeuristicSolutions(int value) {
1327        numberHeuristicSolutions_ = value;
1328    }
1329
1330    /// Set objective function sense (1 for min (default), -1 for max,)
1331    inline void setObjSense(double s) {
1332        dblParam_[CbcOptimizationDirection] = s;
1333        solver_->setObjSense(s);
1334    }
1335
1336    /// Value of objective at continuous
1337    inline double getContinuousObjective() const {
1338        return originalContinuousObjective_;
1339    }
1340    inline void setContinuousObjective(double value) {
1341        originalContinuousObjective_ = value;
1342    }
1343    /// Number of infeasibilities at continuous
1344    inline int getContinuousInfeasibilities() const {
1345        return continuousInfeasibilities_;
1346    }
1347    inline void setContinuousInfeasibilities(int value) {
1348        continuousInfeasibilities_ = value;
1349    }
1350    /// Value of objective after root node cuts added
1351    inline double rootObjectiveAfterCuts() const {
1352        return continuousObjective_;
1353    }
1354    /// Sum of Changes to objective by first solve
1355    inline double sumChangeObjective() const {
1356        return sumChangeObjective1_;
1357    }
1358    /** Number of times global cuts violated.  When global cut pool then this
1359        should be kept for each cut and type of cut */
1360    inline int numberGlobalViolations() const {
1361        return numberGlobalViolations_;
1362    }
1363    inline void clearNumberGlobalViolations() {
1364        numberGlobalViolations_ = 0;
1365    }
1366    /// Whether to force a resolve after takeOffCuts
1367    inline bool resolveAfterTakeOffCuts() const {
1368        return resolveAfterTakeOffCuts_;
1369    }
1370    inline void setResolveAfterTakeOffCuts(bool yesNo) {
1371        resolveAfterTakeOffCuts_ = yesNo;
1372    }
1373    /// Maximum number of rows
1374    inline int maximumRows() const {
1375        return maximumRows_;
1376    }
1377    /// Work basis for temporary use
1378    inline CoinWarmStartBasis & workingBasis() {
1379        return workingBasis_;
1380    }
1381    /// Get number of "iterations" to stop after
1382    inline int getStopNumberIterations() const {
1383        return stopNumberIterations_;
1384    }
1385    /// Set number of "iterations" to stop after
1386    inline void setStopNumberIterations(int value) {
1387        stopNumberIterations_ = value;
1388    }
1389    //@}
1390
1391    /** \name Node selection */
1392    //@{
1393    // Comparison functions (which may be overridden by inheritance)
1394    inline CbcCompareBase * nodeComparison() const {
1395        return nodeCompare_;
1396    }
1397    void setNodeComparison(CbcCompareBase * compare);
1398    void setNodeComparison(CbcCompareBase & compare);
1399    //@}
1400
1401    /** \name Problem feasibility checking */
1402    //@{
1403    // Feasibility functions (which may be overridden by inheritance)
1404    inline CbcFeasibilityBase * problemFeasibility() const {
1405        return problemFeasibility_;
1406    }
1407    void setProblemFeasibility(CbcFeasibilityBase * feasibility);
1408    void setProblemFeasibility(CbcFeasibilityBase & feasibility);
1409    //@}
1410
1411    /** \name Tree methods and subtree methods */
1412    //@{
1413    /// Tree method e.g. heap (which may be overridden by inheritance)
1414    inline CbcTree * tree() const {
1415        return tree_;
1416    }
1417    /// For modifying tree handling (original is cloned)
1418    void passInTreeHandler(CbcTree & tree);
1419    /** For passing in an CbcModel to do a sub Tree (with derived tree handlers).
1420        Passed in model must exist for duration of branch and bound
1421    */
1422    void passInSubTreeModel(CbcModel & model);
1423    /** For retrieving a copy of subtree model with given OsiSolver.
1424        If no subtree model will use self (up to user to reset cutoff etc).
1425        If solver NULL uses current
1426    */
1427    CbcModel * subTreeModel(OsiSolverInterface * solver = NULL) const;
1428    /// Returns number of times any subtree stopped on nodes, time etc
1429    inline int numberStoppedSubTrees() const {
1430        return numberStoppedSubTrees_;
1431    }
1432    /// Says a sub tree was stopped
1433    inline void incrementSubTreeStopped() {
1434        numberStoppedSubTrees_++;
1435    }
1436    /** Whether to automatically do presolve before branch and bound (subTrees).
1437        0 - no
1438        1 - ordinary presolve
1439        2 - integer presolve (dodgy)
1440    */
1441    inline int typePresolve() const {
1442        return presolve_;
1443    }
1444    inline void setTypePresolve(int value) {
1445        presolve_ = value;
1446    }
1447
1448    //@}
1449
1450    /** \name Branching Decisions
1451
1452      See the CbcBranchDecision class for additional information.
1453    */
1454    //@{
1455
1456    /// Get the current branching decision method.
1457    inline CbcBranchDecision * branchingMethod() const {
1458        return branchingMethod_;
1459    }
1460    /// Set the branching decision method.
1461    inline void setBranchingMethod(CbcBranchDecision * method) {
1462        delete branchingMethod_;
1463        branchingMethod_ = method->clone();
1464    }
1465    /** Set the branching method
1466
1467      \overload
1468    */
1469    inline void setBranchingMethod(CbcBranchDecision & method) {
1470        delete branchingMethod_;
1471        branchingMethod_ = method.clone();
1472    }
1473    /// Get the current cut modifier method
1474    inline CbcCutModifier * cutModifier() const {
1475        return cutModifier_;
1476    }
1477    /// Set the cut modifier method
1478    void setCutModifier(CbcCutModifier * modifier);
1479    /** Set the cut modifier method
1480
1481      \overload
1482    */
1483    void setCutModifier(CbcCutModifier & modifier);
1484    //@}
1485
1486    /** \name Row (constraint) and Column (variable) cut generation */
1487    //@{
1488
1489    /** State of search
1490        0 - no solution
1491        1 - only heuristic solutions
1492        2 - branched to a solution
1493        3 - no solution but many nodes
1494    */
1495    inline int stateOfSearch() const {
1496        return stateOfSearch_;
1497    }
1498    inline void setStateOfSearch(int state) {
1499        stateOfSearch_ = state;
1500    }
1501    /// Strategy worked out - mainly at root node for use by CbcNode
1502    inline int searchStrategy() const {
1503        return searchStrategy_;
1504    }
1505    /// Set strategy worked out - mainly at root node for use by CbcNode
1506    inline void setSearchStrategy(int value) {
1507        searchStrategy_ = value;
1508    }
1509
1510    /// Get the number of cut generators
1511    inline int numberCutGenerators() const {
1512        return numberCutGenerators_;
1513    }
1514    /// Get the list of cut generators
1515    inline CbcCutGenerator ** cutGenerators() const {
1516        return generator_;
1517    }
1518    ///Get the specified cut generator
1519    inline CbcCutGenerator * cutGenerator(int i) const {
1520        return generator_[i];
1521    }
1522    ///Get the specified cut generator before any changes
1523    inline CbcCutGenerator * virginCutGenerator(int i) const {
1524        return virginGenerator_[i];
1525    }
1526    /** Add one generator - up to user to delete generators.
1527        howoften affects how generator is used. 0 or 1 means always,
1528        >1 means every that number of nodes.  Negative values have same
1529        meaning as positive but they may be switched off (-> -100) by code if
1530        not many cuts generated at continuous.  -99 is just done at root.
1531        Name is just for printout.
1532        If depth >0 overrides how often generator is called (if howOften==-1 or >0).
1533    */
1534    void addCutGenerator(CglCutGenerator * generator,
1535                         int howOften = 1, const char * name = NULL,
1536                         bool normal = true, bool atSolution = false,
1537                         bool infeasible = false, int howOftenInSub = -100,
1538                         int whatDepth = -1, int whatDepthInSub = -1);
1539//@}
1540    /** \name Strategy and sub models
1541
1542      See the CbcStrategy class for additional information.
1543    */
1544    //@{
1545
1546    /// Get the current strategy
1547    inline CbcStrategy * strategy() const {
1548        return strategy_;
1549    }
1550    /// Set the strategy. Clones
1551    void setStrategy(CbcStrategy & strategy);
1552    /// Set the strategy. assigns
1553    inline void setStrategy(CbcStrategy * strategy) {
1554        strategy_ = strategy;
1555    }
1556    /// Get the current parent model
1557    inline CbcModel * parentModel() const {
1558        return parentModel_;
1559    }
1560    /// Set the parent model
1561    inline void setParentModel(CbcModel & parentModel) {
1562        parentModel_ = &parentModel;
1563    }
1564    //@}
1565
1566
1567    /** \name Heuristics and priorities */
1568    //@{
1569    /*! \brief Add one heuristic - up to user to delete
1570
1571      The name is just used for print messages.
1572    */
1573    void addHeuristic(CbcHeuristic * generator, const char *name = NULL,
1574                      int before = -1);
1575    ///Get the specified heuristic
1576    inline CbcHeuristic * heuristic(int i) const {
1577        return heuristic_[i];
1578    }
1579    /// Get the number of heuristics
1580    inline int numberHeuristics() const {
1581        return numberHeuristics_;
1582    }
1583    /// Pointer to heuristic solver which found last solution (or NULL)
1584    inline CbcHeuristic * lastHeuristic() const {
1585        return lastHeuristic_;
1586    }
1587    /// set last heuristic which found a solution
1588    inline void setLastHeuristic(CbcHeuristic * last) {
1589        lastHeuristic_ = last;
1590    }
1591
1592    /** Pass in branching priorities.
1593
1594        If ifClique then priorities are on cliques otherwise priorities are
1595        on integer variables.
1596        Other type (if exists set to default)
1597        1 is highest priority. (well actually -INT_MAX is but that's ugly)
1598        If hotstart > 0 then branches are created to force
1599        the variable to the value given by best solution.  This enables a
1600        sort of hot start.  The node choice should be greatest depth
1601        and hotstart should normally be switched off after a solution.
1602
1603        If ifNotSimpleIntegers true then appended to normal integers
1604
1605        This is now deprecated except for simple usage.  If user
1606        creates Cbcobjects then set priority in them
1607
1608        \internal Added for Kurt Spielberg.
1609    */
1610    void passInPriorities(const int * priorities, bool ifNotSimpleIntegers);
1611
1612    /// Returns priority level for an object (or 1000 if no priorities exist)
1613    inline int priority(int sequence) const {
1614        return object_[sequence]->priority();
1615    }
1616
1617    /*! \brief Set an event handler
1618
1619      A clone of the handler passed as a parameter is stored in CbcModel.
1620    */
1621    void passInEventHandler(const CbcEventHandler *eventHandler) ;
1622
1623    /*! \brief Retrieve a pointer to the event handler */
1624    inline CbcEventHandler* getEventHandler() const {
1625        return (eventHandler_) ;
1626    }
1627
1628    //@}
1629
1630    /**@name Setting/Accessing application data */
1631    //@{
1632    /** Set application data.
1633
1634    This is a pointer that the application can store into and
1635    retrieve from the solver interface.
1636    This field is available for the application to optionally
1637    define and use.
1638    */
1639    void setApplicationData (void * appData);
1640
1641    /// Get application data
1642    void * getApplicationData() const;
1643    /**
1644        For advanced applications you may wish to modify the behavior of Cbc
1645        e.g. if the solver is a NLP solver then you may not have an exact
1646        optimum solution at each step.  Information could be built into
1647        OsiSolverInterface but this is an alternative so that that interface
1648        does not have to be changed.  If something similar is useful to
1649        enough solvers then it could be migrated
1650        You can also pass in by using solver->setAuxiliaryInfo.
1651        You should do that if solver is odd - if solver is normal simplex
1652        then use this.
1653        NOTE - characteristics are not cloned
1654    */
1655    void passInSolverCharacteristics(OsiBabSolver * solverCharacteristics);
1656    /// Get solver characteristics
1657    inline const OsiBabSolver * solverCharacteristics() const {
1658        return solverCharacteristics_;
1659    }
1660    //@}
1661
1662    //---------------------------------------------------------------------------
1663
1664    /**@name Message handling etc */
1665    //@{
1666    /// Pass in Message handler (not deleted at end)
1667    void passInMessageHandler(CoinMessageHandler * handler);
1668    /// Set language
1669    void newLanguage(CoinMessages::Language language);
1670    inline void setLanguage(CoinMessages::Language language) {
1671        newLanguage(language);
1672    }
1673    /// Return handler
1674    inline CoinMessageHandler * messageHandler() const {
1675        return handler_;
1676    }
1677    /// Return messages
1678    inline CoinMessages & messages() {
1679        return messages_;
1680    }
1681    /// Return pointer to messages
1682    inline CoinMessages * messagesPointer() {
1683        return &messages_;
1684    }
1685    /// Set log level
1686    void setLogLevel(int value);
1687    /// Get log level
1688    inline int logLevel() const {
1689        return handler_->logLevel();
1690    }
1691    /** Set flag to say if handler_ is the default handler.
1692
1693      The default handler is deleted when the model is deleted. Other
1694      handlers (supplied by the client) will not be deleted.
1695    */
1696    inline void setDefaultHandler(bool yesNo) {
1697        defaultHandler_ = yesNo;
1698    }
1699    //@}
1700    //---------------------------------------------------------------------------
1701    ///@name Specialized
1702    //@{
1703
1704    /**
1705        Set special options
1706        0 bit (1) - check if cuts valid (if on debugger list)
1707        1 bit (2) - use current basis to check integer solution (rather than all slack)
1708        2 bit (4) - don't check integer solution (by solving LP)
1709        3 bit (8) - fast analyze
1710        4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
1711        5 bit (32) - keep names
1712        6 bit (64) - try for dominated columns
1713        7 bit (128) - SOS type 1 but all declared integer
1714        8 bit (256) - Set to say solution just found, unset by doing cuts
1715        9 bit (512) - Try reduced model after 100 nodes
1716        10 bit (1024) - Switch on some heuristics even if seems unlikely
1717        11 bit (2048) - Mark as in small branch and bound
1718        12 bit (4096) - Funny cuts so do slow way (in some places)
1719        13 bit (8192) - Funny cuts so do slow way (in other places)
1720        14 bit (16384) - Use Cplex! for fathoming
1721        15 bit (32768) - Try reduced model after 0 nodes
1722        16 bit (65536) - Original model had integer bounds
1723        17 bit (131072) - Perturbation switched off
1724        18 bit (262144) - donor CbcModel
1725        19 bit (524288) - recipient CbcModel
1726        20 bit (1048576) - waiting for sub model to return
1727    */
1728    inline void setSpecialOptions(int value) {
1729        specialOptions_ = value;
1730    }
1731    /// Get special options
1732    inline int specialOptions() const {
1733        return specialOptions_;
1734    }
1735    /// Says if normal solver i.e. has well defined CoinPackedMatrix
1736    inline bool normalSolver() const {
1737        return (specialOptions_&16) == 0;
1738    }
1739    /** Says if model is sitting there waiting for mini branch and bound to finish
1740        This is because an event handler may only have access to parent model in
1741        mini branch and bound
1742    */
1743    inline bool waitingForMiniBranchAndBound() const {
1744        return (specialOptions_&1048576) != 0;
1745    }
1746    /** Set more special options
1747        at present bottom 6 bits used for shadow price mode
1748        1024 for experimental hotstart
1749        2048,4096 breaking out of cuts
1750        8192 slowly increase minimum drop
1751        16384 gomory
1752        32768 more heuristics in sub trees
1753        65536 no cuts in preprocessing
1754        131072 Time limits elapsed
1755        18 bit (262144) - Perturb fathom nodes
1756        19 bit (524288) - No limit on fathom nodes
1757        20 bit (1048576) - Reduce sum of infeasibilities before cuts
1758        21 bit (2097152) - Reduce sum of infeasibilities after cuts
1759    */
1760    inline void setMoreSpecialOptions(int value) {
1761        moreSpecialOptions_ = value;
1762    }
1763    /// Get more special options
1764    inline int moreSpecialOptions() const {
1765        return moreSpecialOptions_;
1766    }
1767  /// Set time method
1768    inline void setUseElapsedTime(bool yesNo) {
1769        if (yesNo)
1770          moreSpecialOptions_ |= 131072;
1771        else
1772          moreSpecialOptions_ &= ~131072;
1773    }
1774    /// Get time method
1775    inline bool useElapsedTime() const {
1776        return (moreSpecialOptions_&131072)!=0;
1777    }
1778    /// Go to dantzig pivot selection if easy problem (clp only)
1779#ifdef COIN_HAS_CLP
1780    void goToDantzig(int numberNodes, ClpDualRowPivot *& savePivotMethod);
1781#endif
1782    /// Now we may not own objects - just point to solver's objects
1783    inline bool ownObjects() const {
1784        return ownObjects_;
1785    }
1786    /// Check original model before it gets messed up
1787    void checkModel();
1788    //@}
1789    //---------------------------------------------------------------------------
1790
1791    ///@name Constructors and destructors etc
1792    //@{
1793    /// Default Constructor
1794    CbcModel();
1795
1796    /// Constructor from solver
1797    CbcModel(const OsiSolverInterface &);
1798
1799    /** Assign a solver to the model (model assumes ownership)
1800
1801      On return, \p solver will be NULL.
1802      If deleteSolver then current solver deleted (if model owned)
1803
1804      \note Parameter settings in the outgoing solver are not inherited by
1805        the incoming solver.
1806    */
1807    void assignSolver(OsiSolverInterface *&solver, bool deleteSolver = true);
1808
1809    /** \brief Set ownership of solver
1810
1811      A parameter of false tells CbcModel it does not own the solver and
1812      should not delete it. Once you claim ownership of the solver, you're
1813      responsible for eventually deleting it. Note that CbcModel clones
1814      solvers with abandon.  Unless you have a deep understanding of the
1815      workings of CbcModel, the only time you want to claim ownership is when
1816      you're about to delete the CbcModel object but want the solver to
1817      continue to exist (as, for example, when branchAndBound has finished
1818      and you want to hang on to the answer).
1819    */
1820    inline void setModelOwnsSolver (bool ourSolver) {
1821        ownership_ = ourSolver ? (ownership_ | 0x80000000) : (ownership_ & (~0x80000000)) ;
1822    }
1823
1824    /*! \brief Get ownership of solver
1825
1826      A return value of true means that CbcModel owns the solver and will
1827      take responsibility for deleting it when that becomes necessary.
1828    */
1829    inline bool modelOwnsSolver () {
1830        return ((ownership_&0x80000000) != 0) ;
1831    }
1832
1833    /** Copy constructor .
1834      If cloneHandler is true then message handler is cloned
1835    */
1836    CbcModel(const CbcModel & rhs, bool cloneHandler = false);
1837
1838    /// Assignment operator
1839    CbcModel & operator=(const CbcModel& rhs);
1840
1841    /// Destructor
1842    ~CbcModel ();
1843
1844    /// Returns solver - has current state
1845    inline OsiSolverInterface * solver() const {
1846        return solver_;
1847    }
1848
1849    /// Returns current solver - sets new one
1850    inline OsiSolverInterface * swapSolver(OsiSolverInterface * solver) {
1851        OsiSolverInterface * returnSolver = solver_;
1852        solver_ = solver;
1853        return returnSolver;
1854    }
1855
1856    /// Returns solver with continuous state
1857    inline OsiSolverInterface * continuousSolver() const {
1858        return continuousSolver_;
1859    }
1860
1861    /// Create solver with continuous state
1862    inline void createContinuousSolver() {
1863        continuousSolver_ = solver_->clone();
1864    }
1865    /// Clear solver with continuous state
1866    inline void clearContinuousSolver() {
1867        delete continuousSolver_;
1868        continuousSolver_ = NULL;
1869    }
1870
1871    /// A copy of the solver, taken at constructor or by saveReferenceSolver
1872    inline OsiSolverInterface * referenceSolver() const {
1873        return referenceSolver_;
1874    }
1875
1876    /// Save a copy of the current solver so can be reset to
1877    void saveReferenceSolver();
1878
1879    /** Uses a copy of reference solver to be current solver.
1880        Because of possible mismatches all exotic integer information is loat
1881        (apart from normal information in OsiSolverInterface)
1882        so SOS etc and priorities will have to be redone
1883    */
1884    void resetToReferenceSolver();
1885
1886    /// Clears out as much as possible (except solver)
1887    void gutsOfDestructor();
1888    /** Clears out enough to reset CbcModel as if no branch and bound done
1889     */
1890    void gutsOfDestructor2();
1891    /** Clears out enough to reset CbcModel cutoff etc
1892     */
1893    void resetModel();
1894    /** Most of copy constructor
1895        mode - 0 copy but don't delete before
1896               1 copy and delete before
1897           2 copy and delete before (but use virgin generators)
1898    */
1899    void gutsOfCopy(const CbcModel & rhs, int mode = 0);
1900    /// Move status, nodes etc etc across
1901    void moveInfo(const CbcModel & rhs);
1902    //@}
1903
1904    ///@name Multithreading
1905    //@{
1906    /// Indicates whether Cbc library has been compiled with multithreading support
1907    static bool haveMultiThreadSupport();
1908    /// Get pointer to masterthread
1909    CbcThread * masterThread() const {
1910        return masterThread_;
1911    }
1912    /// Get pointer to walkback
1913    CbcNodeInfo ** walkback() const {
1914        return walkback_;
1915    }
1916    /// Get number of threads
1917    inline int getNumberThreads() const {
1918        return numberThreads_;
1919    }
1920    /// Set number of threads
1921    inline void setNumberThreads(int value) {
1922        numberThreads_ = value;
1923    }
1924    /// Get thread mode
1925    inline int getThreadMode() const {
1926        return threadMode_;
1927    }
1928    /** Set thread mode
1929        always use numberThreads for branching
1930        1 set then deterministic
1931        2 set then use numberThreads for root cuts
1932        4 set then use numberThreads in root mini branch and bound
1933        8 set and numberThreads - do heuristics numberThreads at a time
1934        8 set and numberThreads==0 do all heuristics at once
1935        default is 0
1936    */
1937    inline void setThreadMode(int value) {
1938        threadMode_ = value;
1939    }
1940    /** Return
1941        -2 if deterministic threaded and main thread
1942        -1 if deterministic threaded and serial thread
1943        0 if serial
1944        1 if opportunistic threaded
1945    */
1946    inline int parallelMode() const {
1947        if (!numberThreads_) {
1948            if ((threadMode_&1) == 0)
1949                return 0;
1950            else
1951                return -1;
1952            return 0;
1953        } else {
1954            if ((threadMode_&1) == 0)
1955                return 1;
1956            else
1957                return -2;
1958        }
1959    }
1960    /// From here to end of section - code in CbcThread.cpp until class changed
1961    /// Returns true if locked
1962    bool isLocked() const;
1963#ifdef CBC_THREAD
1964    /**
1965       Locks a thread if parallel so that stuff like cut pool
1966       can be updated and/or used.
1967    */
1968    void lockThread();
1969    /**
1970       Unlocks a thread if parallel to say cut pool stuff not needed
1971    */
1972    void unlockThread();
1973#else
1974    inline void lockThread() {}
1975    inline void unlockThread() {}
1976#endif
1977    /** Set information in a child
1978        -3 pass pointer to child thread info
1979        -2 just stop
1980        -1 delete simple child stuff
1981        0 delete opportunistic child stuff
1982        1 delete deterministic child stuff
1983    */
1984    void setInfoInChild(int type, CbcThread * info);
1985    /** Move/copy information from one model to another
1986        -1 - initialization
1987        0 - from base model
1988        1 - to base model (and reset)
1989        2 - add in final statistics etc (and reset so can do clean destruction)
1990    */
1991    void moveToModel(CbcModel * baseModel, int mode);
1992    /// Split up nodes
1993    int splitModel(int numberModels, CbcModel ** model,
1994                   int numberNodes);
1995    /// Start threads
1996    void startSplitModel(int numberIterations);
1997    /// Merge models
1998    void mergeModels(int numberModel, CbcModel ** model,
1999                     int numberNodes);
2000    //@}
2001
2002    ///@name semi-private i.e. users should not use
2003    //@{
2004    /// Get how many Nodes it took to solve the problem.
2005    int getNodeCount2() const {
2006        return numberNodes2_;
2007    }
2008    /// Set pointers for speed
2009    void setPointers(const OsiSolverInterface * solver);
2010    /** Perform reduced cost fixing
2011
2012      Fixes integer variables at their current value based on reduced cost
2013      penalties.  Returns number fixed
2014    */
2015    int reducedCostFix() ;
2016    /** Makes all handlers same.  If makeDefault 1 then makes top level
2017        default and rest point to that.  If 2 then each is copy
2018    */
2019    void synchronizeHandlers(int makeDefault);
2020    /// Save a solution to saved list
2021    void saveExtraSolution(const double * solution, double objectiveValue);
2022    /// Save a solution to best and move current to saved
2023    void saveBestSolution(const double * solution, double objectiveValue);
2024    /// Delete best and saved solutions
2025    void deleteSolutions();
2026    /// Encapsulates solver resolve
2027    int resolve(OsiSolverInterface * solver);
2028#ifdef CLP_RESOLVE
2029    /// Special purpose resolve
2030    int resolveClp(OsiClpSolverInterface * solver, int type);
2031#endif
2032
2033    /** Encapsulates choosing a variable -
2034        anyAction -2, infeasible (-1 round again), 0 done
2035    */
2036    int chooseBranch(CbcNode * & newNode, int numberPassesLeft,
2037                     CbcNode * oldNode, OsiCuts & cuts,
2038                     bool & resolved, CoinWarmStartBasis *lastws,
2039                     const double * lowerBefore, const double * upperBefore,
2040                     OsiSolverBranch * & branches);
2041    int chooseBranch(CbcNode * newNode, int numberPassesLeft, bool & resolved);
2042
2043    /** Return an empty basis object of the specified size
2044
2045      A useful utility when constructing a basis for a subproblem from scratch.
2046      The object returned will be of the requested capacity and appropriate for
2047      the solver attached to the model.
2048    */
2049    CoinWarmStartBasis *getEmptyBasis(int ns = 0, int na = 0) const ;
2050
2051    /** Remove inactive cuts from the model
2052
2053      An OsiSolverInterface is expected to maintain a valid basis, but not a
2054      valid solution, when loose cuts are deleted. Restoring a valid solution
2055      requires calling the solver to reoptimise. If it's certain the solution
2056      will not be required, set allowResolve to false to suppress
2057      reoptimisation.
2058      If saveCuts then slack cuts will be saved
2059      On input current cuts are cuts and newCuts
2060      on exit current cuts will be correct.  Returns number dropped
2061    */
2062    int takeOffCuts(OsiCuts &cuts,
2063                    bool allowResolve, OsiCuts * saveCuts,
2064                    int numberNewCuts = 0, const OsiRowCut ** newCuts = NULL) ;
2065
2066    /** Determine and install the active cuts that need to be added for
2067      the current subproblem
2068
2069      The whole truth is a bit more complicated. The first action is a call to
2070      addCuts1(). addCuts() then sorts through the list, installs the tight
2071      cuts in the model, and does bookkeeping (adjusts reference counts).
2072      The basis returned from addCuts1() is adjusted accordingly.
2073
2074      If it turns out that the node should really be fathomed by bound,
2075      addCuts() simply treats all the cuts as loose as it does the bookkeeping.
2076
2077      canFix true if extra information being passed
2078    */
2079    int addCuts(CbcNode * node, CoinWarmStartBasis *&lastws, bool canFix);
2080
2081    /** Traverse the tree from node to root and prep the model
2082
2083      addCuts1() begins the job of prepping the model to match the current
2084      subproblem. The model is stripped of all cuts, and the search tree is
2085      traversed from node to root to determine the changes required. Appropriate
2086      bounds changes are installed, a list of cuts is collected but not
2087      installed, and an appropriate basis (minus the cuts, but big enough to
2088      accommodate them) is constructed.
2089
2090      Returns true if new problem similar to old
2091
2092      \todo addCuts1() is called in contexts where it's known in advance that
2093        all that's desired is to determine a list of cuts and do the
2094        bookkeeping (adjust the reference counts). The work of installing
2095        bounds and building a basis goes to waste.
2096    */
2097    bool addCuts1(CbcNode * node, CoinWarmStartBasis *&lastws);
2098    /** Returns bounds just before where - initially original bounds.
2099        Also sets downstream nodes (lower if force 1, upper if 2)
2100    */
2101    void previousBounds (CbcNode * node, CbcNodeInfo * where, int iColumn,
2102                         double & lower, double & upper, int force);
2103    /** Set objective value in a node.  This is separated out so that
2104       odd solvers can use.  It may look at extra information in
2105       solverCharacteriscs_ and will also use bound from parent node
2106    */
2107    void setObjectiveValue(CbcNode * thisNode, const CbcNode * parentNode) const;
2108
2109    /** If numberBeforeTrust >0 then we are going to use CbcBranchDynamic.
2110        Scan and convert CbcSimpleInteger objects
2111    */
2112    void convertToDynamic();
2113    /// Set numberBeforeTrust in all objects
2114    void synchronizeNumberBeforeTrust(int type = 0);
2115    /// Zap integer information in problem (may leave object info)
2116    void zapIntegerInformation(bool leaveObjects = true);
2117    /// Use cliques for pseudocost information - return nonzero if infeasible
2118    int cliquePseudoCosts(int doStatistics);
2119    /// Fill in useful estimates
2120    void pseudoShadow(int type);
2121    /** Return pseudo costs
2122        If not all integers or not pseudo costs - returns all zero
2123        Length of arrays are numberIntegers() and entries
2124        correspond to integerVariable()[i]
2125        User must allocate arrays before call
2126    */
2127    void fillPseudoCosts(double * downCosts, double * upCosts,
2128                         int * priority = NULL,
2129                         int * numberDown = NULL, int * numberUp = NULL,
2130                         int * numberDownInfeasible = NULL,
2131                         int * numberUpInfeasible = NULL) const;
2132    /** Do heuristics at root.
2133        0 - don't delete
2134        1 - delete
2135        2 - just delete - don't even use
2136    */
2137    void doHeuristicsAtRoot(int deleteHeuristicsAfterwards = 0);
2138    /// Adjust heuristics based on model
2139    void adjustHeuristics();
2140    /// Get the hotstart solution
2141    inline const double * hotstartSolution() const {
2142        return hotstartSolution_;
2143    }
2144    /// Get the hotstart priorities
2145    inline const int * hotstartPriorities() const {
2146        return hotstartPriorities_;
2147    }
2148
2149    /// Return the list of cuts initially collected for this subproblem
2150    inline CbcCountRowCut ** addedCuts() const {
2151        return addedCuts_;
2152    }
2153    /// Number of entries in the list returned by #addedCuts()
2154    inline int currentNumberCuts() const {
2155        return currentNumberCuts_;
2156    }
2157    /// Global cuts
2158    inline OsiCuts * globalCuts() {
2159        return &globalCuts_;
2160    }
2161    /// Copy and set a pointer to a row cut which will be added instead of normal branching.
2162    void setNextRowCut(const OsiRowCut & cut);
2163    /// Get a pointer to current node (be careful)
2164    inline CbcNode * currentNode() const {
2165        return currentNode_;
2166    }
2167    /// Get a pointer to probing info
2168    inline CglTreeProbingInfo * probingInfo() const {
2169        return probingInfo_;
2170    }
2171    /// Thread specific random number generator
2172    inline CoinThreadRandom * randomNumberGenerator() {
2173        return &randomNumberGenerator_;
2174    }
2175    /// Set the number of iterations done in strong branching.
2176    inline void setNumberStrongIterations(int number) {
2177        numberStrongIterations_ = number;
2178    }
2179    /// Get the number of iterations done in strong branching.
2180    inline int numberStrongIterations() const {
2181        return numberStrongIterations_;
2182    }
2183    /// Get maximum number of iterations (designed to be used in heuristics)
2184    inline int maximumNumberIterations() const {
2185        return maximumNumberIterations_;
2186    }
2187    /// Set maximum number of iterations (designed to be used in heuristics)
2188    inline void setMaximumNumberIterations(int value) {
2189        maximumNumberIterations_ = value;
2190    }
2191# ifdef COIN_HAS_CLP
2192    /// Set depth for fast nodes
2193    inline void setFastNodeDepth(int value) {
2194        fastNodeDepth_ = value;
2195    }
2196    /// Get depth for fast nodes
2197    inline int fastNodeDepth() const {
2198        return fastNodeDepth_;
2199    }
2200    /// Get anything with priority >= this can be treated as continuous
2201    inline int continuousPriority() const {
2202        return continuousPriority_;
2203    }
2204    /// Set anything with priority >= this can be treated as continuous
2205    inline void setContinuousPriority(int value) {
2206        continuousPriority_ = value;
2207    }
2208    inline void incrementExtra(int nodes, int iterations) {
2209        numberExtraNodes_ += nodes;
2210        numberExtraIterations_ += iterations;
2211    }
2212#endif
2213    /// Number of extra iterations
2214    inline int numberExtraIterations() const {
2215        return numberExtraIterations_;
2216    }
2217    /// Increment strong info
2218    void incrementStrongInfo(int numberTimes, int numberIterations,
2219                             int numberFixed, bool ifInfeasible);
2220    /// Return strong info
2221    inline const int * strongInfo() const {
2222        return strongInfo_;
2223    }
2224
2225    /// Return mutable strong info
2226    inline int * mutableStrongInfo() {
2227        return strongInfo_;
2228    }
2229    /// Get stored row cuts for donor/recipient CbcModel
2230    CglStored * storedRowCuts() const {
2231        return storedRowCuts_;
2232    }
2233    /// Set stored row cuts for donor/recipient CbcModel
2234    void setStoredRowCuts(CglStored * cuts) {
2235        storedRowCuts_ = cuts;
2236    }
2237    /// Says whether all dynamic integers
2238    inline bool allDynamic () const {
2239        return ((ownership_&0x40000000) != 0) ;
2240    }
2241    /// Create C++ lines to get to current state
2242    void generateCpp( FILE * fp, int options);
2243    /// Generate an OsiBranchingInformation object
2244    OsiBranchingInformation usefulInformation() const;
2245    /** Warm start object produced by heuristic or strong branching
2246
2247        If get a valid integer solution outside branch and bound then it can take
2248        a reasonable time to solve LP which produces clean solution.  If this object has
2249        any size then it will be used in solve.
2250    */
2251    inline void setBestSolutionBasis(const CoinWarmStartBasis & bestSolutionBasis) {
2252        bestSolutionBasis_ = bestSolutionBasis;
2253    }
2254    /// Redo walkback arrays
2255    void redoWalkBack();
2256    //@}
2257
2258//---------------------------------------------------------------------------
2259
2260private:
2261    ///@name Private member data
2262    //@{
2263
2264    /// The solver associated with this model.
2265    OsiSolverInterface * solver_;
2266
2267    /** Ownership of objects and other stuff
2268
2269        0x80000000 model owns solver
2270        0x40000000 all variables CbcDynamicPseudoCost
2271    */
2272    unsigned int ownership_ ;
2273
2274    /// A copy of the solver, taken at the continuous (root) node.
2275    OsiSolverInterface * continuousSolver_;
2276
2277    /// A copy of the solver, taken at constructor or by saveReferenceSolver
2278    OsiSolverInterface * referenceSolver_;
2279
2280    /// Message handler
2281    CoinMessageHandler * handler_;
2282
2283    /** Flag to say if handler_ is the default handler.
2284
2285      The default handler is deleted when the model is deleted. Other
2286      handlers (supplied by the client) will not be deleted.
2287    */
2288    bool defaultHandler_;
2289
2290    /// Cbc messages
2291    CoinMessages messages_;
2292
2293    /// Array for integer parameters
2294    int intParam_[CbcLastIntParam];
2295
2296    /// Array for double parameters
2297    double dblParam_[CbcLastDblParam];
2298
2299    /** Pointer to an empty warm start object
2300
2301      It turns out to be useful to have this available as a base from
2302      which to build custom warm start objects. This is typed as CoinWarmStart
2303      rather than CoinWarmStartBasis to allow for the possibility that a
2304      client might want to apply a solver that doesn't use a basis-based warm
2305      start. See getEmptyBasis for an example of how this field can be used.
2306    */
2307    mutable CoinWarmStart *emptyWarmStart_ ;
2308
2309    /// Best objective
2310    double bestObjective_;
2311    /// Best possible objective
2312    double bestPossibleObjective_;
2313    /// Sum of Changes to objective by first solve
2314    double sumChangeObjective1_;
2315    /// Sum of Changes to objective by subsequent solves
2316    double sumChangeObjective2_;
2317
2318    /// Array holding the incumbent (best) solution.
2319    double * bestSolution_;
2320    /// Arrays holding other solutions.
2321    double ** savedSolutions_;
2322
2323    /** Array holding the current solution.
2324
2325      This array is used more as a temporary.
2326    */
2327    double * currentSolution_;
2328    /** For testing infeasibilities - will point to
2329        currentSolution_ or solver-->getColSolution()
2330    */
2331    mutable const double * testSolution_;
2332    /** Warm start object produced by heuristic or strong branching
2333
2334        If get a valid integer solution outside branch and bound then it can take
2335        a reasonable time to solve LP which produces clean solution.  If this object has
2336        any size then it will be used in solve.
2337    */
2338    CoinWarmStartBasis bestSolutionBasis_ ;
2339    /// Global cuts
2340    OsiCuts globalCuts_;
2341
2342    /// Minimum degradation in objective value to continue cut generation
2343    double minimumDrop_;
2344    /// Number of solutions
2345    int numberSolutions_;
2346    /// Number of saved solutions
2347    int numberSavedSolutions_;
2348    /// Maximum number of saved solutions
2349    int maximumSavedSolutions_;
2350    /** State of search
2351        0 - no solution
2352        1 - only heuristic solutions
2353        2 - branched to a solution
2354        3 - no solution but many nodes
2355    */
2356    int stateOfSearch_;
2357    /// At which depths to do cuts
2358    int whenCuts_;
2359    /// Hotstart solution
2360    double * hotstartSolution_;
2361    /// Hotstart priorities
2362    int * hotstartPriorities_;
2363    /// Number of heuristic solutions
2364    int numberHeuristicSolutions_;
2365    /// Cumulative number of nodes
2366    int numberNodes_;
2367    /** Cumulative number of nodes for statistics.
2368        Must fix to match up
2369    */
2370    int numberNodes2_;
2371    /// Cumulative number of iterations
2372    int numberIterations_;
2373    /// Cumulative number of solves
2374    int numberSolves_;
2375    /// Status of problem - 0 finished, 1 stopped, 2 difficulties
2376    int status_;
2377    /** Secondary status of problem
2378        -1 unset (status_ will also be -1)
2379        0 search completed with solution
2380        1 linear relaxation not feasible (or worse than cutoff)
2381        2 stopped on gap
2382        3 stopped on nodes
2383        4 stopped on time
2384        5 stopped on user event
2385        6 stopped on solutions
2386     */
2387    int secondaryStatus_;
2388    /// Number of integers in problem
2389    int numberIntegers_;
2390    /// Number of rows at continuous
2391    int numberRowsAtContinuous_;
2392    /// Maximum number of cuts
2393    int maximumNumberCuts_;
2394    /** Current phase (so heuristics etc etc can find out).
2395        0 - initial solve
2396        1 - solve with cuts at root
2397        2 - solve with cuts
2398        3 - other e.g. strong branching
2399        4 - trying to validate a solution
2400        5 - at end of search
2401    */
2402    int phase_;
2403
2404    /// Number of entries in #addedCuts_
2405    int currentNumberCuts_;
2406
2407    /** Current limit on search tree depth
2408
2409      The allocated size of #walkback_. Increased as needed.
2410    */
2411    int maximumDepth_;
2412    /** Array used to assemble the path between a node and the search tree root
2413
2414      The array is resized when necessary. #maximumDepth_  is the current
2415      allocated size.
2416    */
2417    CbcNodeInfo ** walkback_;
2418    CbcNodeInfo ** lastNodeInfo_;
2419    const OsiRowCut ** lastCut_;
2420    int lastDepth_;
2421    int lastNumberCuts2_;
2422    int maximumCuts_;
2423    int * lastNumberCuts_;
2424
2425    /** The list of cuts initially collected for this subproblem
2426
2427      When the subproblem at this node is rebuilt, a set of cuts is collected
2428      for inclusion in the constraint system. If any of these cuts are
2429      subsequently removed because they have become loose, the corresponding
2430      entry is set to NULL.
2431    */
2432    CbcCountRowCut ** addedCuts_;
2433
2434    /** A pointer to a row cut which will be added instead of normal branching.
2435        After use it should be set to NULL.
2436    */
2437    OsiRowCut * nextRowCut_;
2438
2439    /// Current node so can be used elsewhere
2440    CbcNode * currentNode_;
2441
2442    /// Indices of integer variables
2443    int * integerVariable_;
2444    /// Whether of not integer
2445    char * integerInfo_;
2446    /// Holds solution at continuous (after cuts)
2447    double * continuousSolution_;
2448    /// Array marked whenever a solution is found if non-zero
2449    int * usedInSolution_;
2450    /**
2451        Special options
2452        0 bit (1) - check if cuts valid (if on debugger list)
2453        1 bit (2) - use current basis to check integer solution (rather than all slack)
2454        2 bit (4) - don't check integer solution (by solving LP)
2455        3 bit (8) - fast analyze
2456        4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
2457        5 bit (32) - keep names
2458        6 bit (64) - try for dominated columns
2459        7 bit (128) - SOS type 1 but all declared integer
2460        8 bit (256) - Set to say solution just found, unset by doing cuts
2461        9 bit (512) - Try reduced model after 100 nodes
2462        10 bit (1024) - Switch on some heuristics even if seems unlikely
2463        11 bit (2048) - Mark as in small branch and bound
2464        12 bit (4096) - Funny cuts so do slow way (in some places)
2465        13 bit (8192) - Funny cuts so do slow way (in other places)
2466        14 bit (16384) - Use Cplex! for fathoming
2467        15 bit (32768) - Try reduced model after 0 nodes
2468        16 bit (65536) - Original model had integer bounds
2469        17 bit (131072) - Perturbation switched off
2470        18 bit (262144) - donor CbcModel
2471        19 bit (524288) - recipient CbcModel
2472    */
2473    int specialOptions_;
2474    /** More special options
2475        at present bottom 6 bits used for shadow price mode
2476        1024 for experimental hotstart
2477        2048,4096 breaking out of cuts
2478        8192 slowly increase minimum drop
2479        16384 gomory
2480        32768 more heuristics in sub trees
2481        65536 no cuts in preprocessing
2482        131072 Time limits elapsed
2483        18 bit (262144) - Perturb fathom nodes
2484        19 bit (524288) - No limit on fathom nodes
2485        20 bit (1048576) - Reduce sum of infeasibilities before cuts
2486        21 bit (2097152) - Reduce sum of infeasibilities after cuts
2487    */
2488    int moreSpecialOptions_;
2489    /// User node comparison function
2490    CbcCompareBase * nodeCompare_;
2491    /// User feasibility function (see CbcFeasibleBase.hpp)
2492    CbcFeasibilityBase * problemFeasibility_;
2493    /// Tree
2494    CbcTree * tree_;
2495    /// A pointer to model to be used for subtrees
2496    CbcModel * subTreeModel_;
2497    /// Number of times any subtree stopped on nodes, time etc
2498    int numberStoppedSubTrees_;
2499    /// Variable selection function
2500    CbcBranchDecision * branchingMethod_;
2501    /// Cut modifier function
2502    CbcCutModifier * cutModifier_;
2503    /// Strategy
2504    CbcStrategy * strategy_;
2505    /// Parent model
2506    CbcModel * parentModel_;
2507    /** Whether to automatically do presolve before branch and bound.
2508        0 - no
2509        1 - ordinary presolve
2510        2 - integer presolve (dodgy)
2511    */
2512    /// Pointer to array[getNumCols()] (for speed) of column lower bounds
2513    const double * cbcColLower_;
2514    /// Pointer to array[getNumCols()] (for speed) of column upper bounds
2515    const double * cbcColUpper_;
2516    /// Pointer to array[getNumRows()] (for speed) of row lower bounds
2517    const double * cbcRowLower_;
2518    /// Pointer to array[getNumRows()] (for speed) of row upper bounds
2519    const double * cbcRowUpper_;
2520    /// Pointer to array[getNumCols()] (for speed) of primal solution vector
2521    const double * cbcColSolution_;
2522    /// Pointer to array[getNumRows()] (for speed) of dual prices
2523    const double * cbcRowPrice_;
2524    /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
2525    const double * cbcReducedCost_;
2526    /// Pointer to array[getNumRows()] (for speed) of row activity levels.
2527    const double * cbcRowActivity_;
2528    /// Pointer to user-defined data structure
2529    void * appData_;
2530    /// Presolve for CbcTreeLocal
2531    int presolve_;
2532    /** Maximum number of candidates to consider for strong branching.
2533      To disable strong branching, set this to 0.
2534    */
2535    int numberStrong_;
2536    /** \brief The number of branches before pseudo costs believed
2537           in dynamic strong branching.
2538
2539      A value of 0 is  off.
2540    */
2541    int numberBeforeTrust_;
2542    /** \brief The number of variables for which to compute penalties
2543           in dynamic strong branching.
2544    */
2545    int numberPenalties_;
2546    /// For threads - stop after this many "iterations"
2547    int stopNumberIterations_;
2548    /** Scale factor to make penalties match strong.
2549        Should/will be computed */
2550    double penaltyScaleFactor_;
2551    /// Number of analyze iterations to do
2552    int numberAnalyzeIterations_;
2553    /// Arrays with analysis results
2554    double * analyzeResults_;
2555    /// Number of nodes infeasible by normal branching (before cuts)
2556    int numberInfeasibleNodes_;
2557    /** Problem type as set by user or found by analysis.  This will be extended
2558        0 - not known
2559        1 - Set partitioning <=
2560        2 - Set partitioning ==
2561        3 - Set covering
2562    */
2563    int problemType_;
2564    /// Print frequency
2565    int printFrequency_;
2566    /// Number of cut generators
2567    int numberCutGenerators_;
2568    // Cut generators
2569    CbcCutGenerator ** generator_;
2570    // Cut generators before any changes
2571    CbcCutGenerator ** virginGenerator_;
2572    /// Number of heuristics
2573    int numberHeuristics_;
2574    /// Heuristic solvers
2575    CbcHeuristic ** heuristic_;
2576    /// Pointer to heuristic solver which found last solution (or NULL)
2577    CbcHeuristic * lastHeuristic_;
2578    /// Depth for fast nodes
2579    int fastNodeDepth_;
2580    /*! Pointer to the event handler */
2581# ifdef CBC_ONLY_CLP
2582    ClpEventHandler *eventHandler_ ;
2583# else
2584    CbcEventHandler *eventHandler_ ;
2585# endif
2586
2587    /// Total number of objects
2588    int numberObjects_;
2589
2590    /** \brief Integer and Clique and ... information
2591
2592      \note The code assumes that the first objects on the list will be
2593        SimpleInteger objects for each integer variable, followed by
2594        Clique objects. Portions of the code that understand Clique objects
2595        will fail if they do not immediately follow the SimpleIntegers.
2596        Large chunks of the code will fail if the first objects are not
2597        SimpleInteger. As of 2003.08, SimpleIntegers and Cliques are the only
2598        objects.
2599    */
2600    OsiObject ** object_;
2601    /// Now we may not own objects - just point to solver's objects
2602    bool ownObjects_;
2603
2604    /// Original columns as created by integerPresolve or preprocessing
2605    int * originalColumns_;
2606    /// How often to scan global cuts
2607    int howOftenGlobalScan_;
2608    /** Number of times global cuts violated.  When global cut pool then this
2609        should be kept for each cut and type of cut */
2610    int numberGlobalViolations_;
2611    /// Number of extra iterations in fast lp
2612    int numberExtraIterations_;
2613    /// Number of extra nodes in fast lp
2614    int numberExtraNodes_;
2615    /** Value of objective at continuous
2616        (Well actually after initial round of cuts)
2617    */
2618    double continuousObjective_;
2619    /** Value of objective before root node cuts added
2620    */
2621    double originalContinuousObjective_;
2622    /// Number of infeasibilities at continuous
2623    int continuousInfeasibilities_;
2624    /// Maximum number of cut passes at root
2625    int maximumCutPassesAtRoot_;
2626    /// Maximum number of cut passes
2627    int maximumCutPasses_;
2628    /// Preferred way of branching
2629    int preferredWay_;
2630    /// Current cut pass number
2631    int currentPassNumber_;
2632    /// Maximum number of cuts (for whichGenerator_)
2633    int maximumWhich_;
2634    /// Maximum number of rows
2635    int maximumRows_;
2636    /// Current depth
2637    int currentDepth_;
2638    /// Thread specific random number generator
2639    mutable CoinThreadRandom randomNumberGenerator_;
2640    /// Work basis for temporary use
2641    CoinWarmStartBasis workingBasis_;
2642    /// Which cut generator generated this cut
2643    int * whichGenerator_;
2644    /// Maximum number of statistics
2645    int maximumStatistics_;
2646    /// statistics
2647    CbcStatistics ** statistics_;
2648    /// Maximum depth reached
2649    int maximumDepthActual_;
2650    /// Number of reduced cost fixings
2651    double numberDJFixed_;
2652    /// Probing info
2653    CglTreeProbingInfo * probingInfo_;
2654    /// Number of fixed by analyze at root
2655    int numberFixedAtRoot_;
2656    /// Number fixed by analyze so far
2657    int numberFixedNow_;
2658    /// Whether stopping on gap
2659    bool stoppedOnGap_;
2660    /// Whether event happened
2661    mutable bool eventHappened_;
2662    /// Number of long strong goes
2663    int numberLongStrong_;
2664    /// Number of old active cuts
2665    int numberOldActiveCuts_;
2666    /// Number of new cuts
2667    int numberNewCuts_;
2668    /// Strategy worked out - mainly at root node
2669    int searchStrategy_;
2670    /// Number of iterations in strong branching
2671    int numberStrongIterations_;
2672    /** 0 - number times strong branching done, 1 - number fixed, 2 - number infeasible
2673        Second group of three is a snapshot at node [6] */
2674    int strongInfo_[7];
2675    /**
2676        For advanced applications you may wish to modify the behavior of Cbc
2677        e.g. if the solver is a NLP solver then you may not have an exact
2678        optimum solution at each step.  This gives characteristics - just for one BAB.
2679        For actually saving/restoring a solution you need the actual solver one.
2680    */
2681    OsiBabSolver * solverCharacteristics_;
2682    /// Whether to force a resolve after takeOffCuts
2683    bool resolveAfterTakeOffCuts_;
2684    /// Maximum number of iterations (designed to be used in heuristics)
2685    int maximumNumberIterations_;
2686    /// Anything with priority >= this can be treated as continuous
2687    int continuousPriority_;
2688    /// Number of outstanding update information items
2689    int numberUpdateItems_;
2690    /// Maximum number of outstanding update information items
2691    int maximumNumberUpdateItems_;
2692    /// Update items
2693    CbcObjectUpdateData * updateItems_;
2694    /// Stored row cuts for donor/recipient CbcModel
2695    CglStored * storedRowCuts_;
2696    /**
2697       Parallel
2698       0 - off
2699       1 - testing
2700       2-99 threads
2701       other special meanings
2702    */
2703    int numberThreads_;
2704    /** thread mode
2705        always use numberThreads for branching
2706        1 set then deterministic
2707        2 set then use numberThreads for root cuts
2708        4 set then use numberThreads in root mini branch and bound
2709        default is 0
2710    */
2711    int threadMode_;
2712    /// Thread stuff for master
2713    CbcBaseModel * master_;
2714    /// Pointer to masterthread
2715    CbcThread * masterThread_;
2716//@}
2717};
2718/// So we can use osiObject or CbcObject during transition
2719void getIntegerInformation(const OsiObject * object, double & originalLower,
2720                           double & originalUpper) ;
2721// So we can call from other programs
2722// Real main program
2723class OsiClpSolverInterface;
2724int CbcMain (int argc, const char *argv[], OsiClpSolverInterface & solver, CbcModel ** babSolver);
2725int CbcMain (int argc, const char *argv[], CbcModel & babSolver);
2726// four ways of calling
2727int callCbc(const char * input2, OsiClpSolverInterface& solver1);
2728int callCbc(const char * input2);
2729int callCbc(const std::string input2, OsiClpSolverInterface& solver1);
2730int callCbc(const std::string input2) ;
2731// When we want to load up CbcModel with options first
2732void CbcMain0 (CbcModel & babSolver);
2733int CbcMain1 (int argc, const char *argv[], CbcModel & babSolver);
2734// two ways of calling
2735int callCbc(const char * input2, CbcModel & babSolver);
2736int callCbc(const std::string input2, CbcModel & babSolver);
2737// And when CbcMain0 already called to initialize
2738int callCbc1(const char * input2, CbcModel & babSolver);
2739int callCbc1(const std::string input2, CbcModel & babSolver);
2740// And when CbcMain0 already called to initialize (with call back) (see CbcMain1 for whereFrom)
2741int callCbc1(const char * input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2742int callCbc1(const std::string input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2743int CbcMain1 (int argc, const char *argv[], CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2744// For uniform setting of cut and heuristic options
2745void setCutAndHeuristicOptions(CbcModel & model);
2746#endif
2747
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