source: trunk/Cbc/src/CbcModel.hpp @ 1791

Last change on this file since 1791 was 1791, checked in by stefan, 9 years ago

merge r1790 from stable/2.7 (correct message if iterlim reached) and introduce secondaryStatus 8 for stop at iteration limit

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1/* $Id: CbcModel.hpp 1791 2012-06-08 15:15:10Z 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        8 stopped on iteration limit
935    */
936    inline int secondaryStatus() const {
937        return secondaryStatus_;
938    }
939    inline void setSecondaryStatus(int value) {
940        secondaryStatus_ = value;
941    }
942    /// Are there numerical difficulties (for initialSolve) ?
943    bool isInitialSolveAbandoned() const ;
944    /// Is optimality proven (for initialSolve) ?
945    bool isInitialSolveProvenOptimal() const ;
946    /// Is primal infeasiblity proven (for initialSolve) ?
947    bool isInitialSolveProvenPrimalInfeasible() const ;
948    /// Is dual infeasiblity proven (for initialSolve) ?
949    bool isInitialSolveProvenDualInfeasible() const ;
950
951    //@}
952
953    //---------------------------------------------------------------------------
954    /**@name Problem information methods
955
956       These methods call the solver's query routines to return
957       information about the problem referred to by the current object.
958       Querying a problem that has no data associated with it result in
959       zeros for the number of rows and columns, and NULL pointers from
960       the methods that return vectors.
961
962       Const pointers returned from any data-query method are valid as
963       long as the data is unchanged and the solver is not called.
964    */
965    //@{
966    /// Number of rows in continuous (root) problem.
967    inline int numberRowsAtContinuous() const {
968        return numberRowsAtContinuous_;
969    }
970
971    /// Get number of columns
972    inline int getNumCols() const {
973        return solver_->getNumCols();
974    }
975
976    /// Get number of rows
977    inline int getNumRows() const {
978        return solver_->getNumRows();
979    }
980
981    /// Get number of nonzero elements
982    inline CoinBigIndex getNumElements() const {
983        return solver_->getNumElements();
984    }
985
986    /// Number of integers in problem
987    inline int numberIntegers() const {
988        return numberIntegers_;
989    }
990    // Integer variables
991    inline const int * integerVariable() const {
992        return integerVariable_;
993    }
994    /// Whether or not integer
995    inline char integerType(int i) const {
996        assert (integerInfo_);
997        assert (integerInfo_[i] == 0 || integerInfo_[i] == 1);
998        return integerInfo_[i];
999    }
1000    /// Whether or not integer
1001    inline const char * integerType() const {
1002        return integerInfo_;
1003    }
1004
1005    /// Get pointer to array[getNumCols()] of column lower bounds
1006    inline const double * getColLower() const {
1007        return solver_->getColLower();
1008    }
1009
1010    /// Get pointer to array[getNumCols()] of column upper bounds
1011    inline const double * getColUpper() const {
1012        return solver_->getColUpper();
1013    }
1014
1015    /** Get pointer to array[getNumRows()] of row constraint senses.
1016        <ul>
1017        <li>'L': <= constraint
1018        <li>'E': =  constraint
1019        <li>'G': >= constraint
1020        <li>'R': ranged constraint
1021        <li>'N': free constraint
1022        </ul>
1023    */
1024    inline const char * getRowSense() const {
1025        return solver_->getRowSense();
1026    }
1027
1028    /** Get pointer to array[getNumRows()] of rows right-hand sides
1029        <ul>
1030        <li> if rowsense()[i] == 'L' then rhs()[i] == rowupper()[i]
1031        <li> if rowsense()[i] == 'G' then rhs()[i] == rowlower()[i]
1032        <li> if rowsense()[i] == 'R' then rhs()[i] == rowupper()[i]
1033        <li> if rowsense()[i] == 'N' then rhs()[i] == 0.0
1034        </ul>
1035    */
1036    inline const double * getRightHandSide() const {
1037        return solver_->getRightHandSide();
1038    }
1039
1040    /** Get pointer to array[getNumRows()] of row ranges.
1041        <ul>
1042        <li> if rowsense()[i] == 'R' then
1043        rowrange()[i] == rowupper()[i] - rowlower()[i]
1044        <li> if rowsense()[i] != 'R' then
1045        rowrange()[i] is 0.0
1046        </ul>
1047    */
1048    inline const double * getRowRange() const {
1049        return solver_->getRowRange();
1050    }
1051
1052    /// Get pointer to array[getNumRows()] of row lower bounds
1053    inline const double * getRowLower() const {
1054        return solver_->getRowLower();
1055    }
1056
1057    /// Get pointer to array[getNumRows()] of row upper bounds
1058    inline const double * getRowUpper() const {
1059        return solver_->getRowUpper();
1060    }
1061
1062    /// Get pointer to array[getNumCols()] of objective function coefficients
1063    inline const double * getObjCoefficients() const {
1064        return solver_->getObjCoefficients();
1065    }
1066
1067    /// Get objective function sense (1 for min (default), -1 for max)
1068    inline double getObjSense() const {
1069        //assert (dblParam_[CbcOptimizationDirection]== solver_->getObjSense());
1070        return dblParam_[CbcOptimizationDirection];
1071    }
1072
1073    /// Return true if variable is continuous
1074    inline bool isContinuous(int colIndex) const {
1075        return solver_->isContinuous(colIndex);
1076    }
1077
1078    /// Return true if variable is binary
1079    inline bool isBinary(int colIndex) const {
1080        return solver_->isBinary(colIndex);
1081    }
1082
1083    /** Return true if column is integer.
1084        Note: This function returns true if the the column
1085        is binary or a general integer.
1086    */
1087    inline bool isInteger(int colIndex) const {
1088        return solver_->isInteger(colIndex);
1089    }
1090
1091    /// Return true if variable is general integer
1092    inline bool isIntegerNonBinary(int colIndex) const {
1093        return solver_->isIntegerNonBinary(colIndex);
1094    }
1095
1096    /// Return true if variable is binary and not fixed at either bound
1097    inline bool isFreeBinary(int colIndex) const {
1098        return solver_->isFreeBinary(colIndex) ;
1099    }
1100
1101    /// Get pointer to row-wise copy of matrix
1102    inline const CoinPackedMatrix * getMatrixByRow() const {
1103        return solver_->getMatrixByRow();
1104    }
1105
1106    /// Get pointer to column-wise copy of matrix
1107    inline const CoinPackedMatrix * getMatrixByCol() const {
1108        return solver_->getMatrixByCol();
1109    }
1110
1111    /// Get solver's value for infinity
1112    inline double getInfinity() const {
1113        return solver_->getInfinity();
1114    }
1115    /// Get pointer to array[getNumCols()] (for speed) of column lower bounds
1116    inline const double * getCbcColLower() const {
1117        return cbcColLower_;
1118    }
1119    /// Get pointer to array[getNumCols()] (for speed) of column upper bounds
1120    inline const double * getCbcColUpper() const {
1121        return cbcColUpper_;
1122    }
1123    /// Get pointer to array[getNumRows()] (for speed) of row lower bounds
1124    inline const double * getCbcRowLower() const {
1125        return cbcRowLower_;
1126    }
1127    /// Get pointer to array[getNumRows()] (for speed) of row upper bounds
1128    inline const double * getCbcRowUpper() const {
1129        return cbcRowUpper_;
1130    }
1131    /// Get pointer to array[getNumCols()] (for speed) of primal solution vector
1132    inline const double * getCbcColSolution() const {
1133        return cbcColSolution_;
1134    }
1135    /// Get pointer to array[getNumRows()] (for speed) of dual prices
1136    inline const double * getCbcRowPrice() const {
1137        return cbcRowPrice_;
1138    }
1139    /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
1140    inline const double * getCbcReducedCost() const {
1141        return cbcReducedCost_;
1142    }
1143    /// Get pointer to array[getNumRows()] (for speed) of row activity levels.
1144    inline const double * getCbcRowActivity() const {
1145        return cbcRowActivity_;
1146    }
1147    //@}
1148
1149
1150    /**@name Methods related to querying the solution */
1151    //@{
1152    /// Holds solution at continuous (after cuts if branchAndBound called)
1153    inline double * continuousSolution() const {
1154        return continuousSolution_;
1155    }
1156    /** Array marked whenever a solution is found if non-zero.
1157        Code marks if heuristic returns better so heuristic
1158        need only mark if it wants to on solutions which
1159        are worse than current */
1160    inline int * usedInSolution() const {
1161        return usedInSolution_;
1162    }
1163    /// Increases usedInSolution for nonzeros
1164    void incrementUsed(const double * solution);
1165    /// Record a new incumbent solution and update objectiveValue
1166    void setBestSolution(CBC_Message how,
1167                         double & objectiveValue, const double *solution,
1168                         int fixVariables = 0);
1169    /// Just update objectiveValue
1170    void setBestObjectiveValue( double objectiveValue);
1171    /// Deals with event handler and solution
1172    CbcEventHandler::CbcAction dealWithEventHandler(CbcEventHandler::CbcEvent event,
1173            double objValue,
1174            const double * solution);
1175
1176    /** Call this to really test if a valid solution can be feasible
1177        Solution is number columns in size.
1178        If fixVariables true then bounds of continuous solver updated.
1179        Returns objective value (worse than cutoff if not feasible)
1180        Previously computed objective value is now passed in (in case user does not do solve)
1181    */
1182    double checkSolution(double cutoff, double * solution,
1183                         int fixVariables, double originalObjValue);
1184    /** Test the current solution for feasiblility.
1185
1186      Scan all objects for indications of infeasibility. This is broken down
1187      into simple integer infeasibility (\p numberIntegerInfeasibilities)
1188      and all other reports of infeasibility (\p numberObjectInfeasibilities).
1189    */
1190    bool feasibleSolution(int & numberIntegerInfeasibilities,
1191                          int & numberObjectInfeasibilities) const;
1192
1193    /** Solution to the most recent lp relaxation.
1194
1195      The solver's solution to the most recent lp relaxation.
1196    */
1197
1198    inline double * currentSolution() const {
1199        return currentSolution_;
1200    }
1201    /** For testing infeasibilities - will point to
1202        currentSolution_ or solver-->getColSolution()
1203    */
1204    inline const double * testSolution() const {
1205        return testSolution_;
1206    }
1207    inline void setTestSolution(const double * solution) {
1208        testSolution_ = solution;
1209    }
1210    /// Make sure region there and optionally copy solution
1211    void reserveCurrentSolution(const double * solution = NULL);
1212
1213    /// Get pointer to array[getNumCols()] of primal solution vector
1214    inline const double * getColSolution() const {
1215        return solver_->getColSolution();
1216    }
1217
1218    /// Get pointer to array[getNumRows()] of dual prices
1219    inline const double * getRowPrice() const {
1220        return solver_->getRowPrice();
1221    }
1222
1223    /// Get a pointer to array[getNumCols()] of reduced costs
1224    inline const double * getReducedCost() const {
1225        return solver_->getReducedCost();
1226    }
1227
1228    /// Get pointer to array[getNumRows()] of row activity levels.
1229    inline const double * getRowActivity() const {
1230        return solver_->getRowActivity();
1231    }
1232
1233    /// Get current objective function value
1234    inline double getCurrentObjValue() const {
1235        return dblParam_[CbcCurrentObjectiveValue];
1236    }
1237    /// Get current minimization objective function value
1238    inline double getCurrentMinimizationObjValue() const {
1239        return dblParam_[CbcCurrentMinimizationObjectiveValue];
1240    }
1241
1242    /// Get best objective function value as minimization
1243    inline double getMinimizationObjValue() const {
1244        return bestObjective_;
1245    }
1246    /// Set best objective function value as minimization
1247    inline void setMinimizationObjValue(double value) {
1248        bestObjective_ = value;
1249    }
1250
1251    /// Get best objective function value
1252    inline double getObjValue() const {
1253        return bestObjective_ * solver_->getObjSense() ;
1254    }
1255    /** Get best possible objective function value.
1256        This is better of best possible left on tree
1257        and best solution found.
1258        If called from within branch and cut may be optimistic.
1259    */
1260    double getBestPossibleObjValue() const;
1261    /// Set best objective function value
1262    inline void setObjValue(double value) {
1263        bestObjective_ = value * solver_->getObjSense() ;
1264    }
1265    /// Get solver objective function value (as minimization)
1266    inline double getSolverObjValue() const {
1267        return solver_->getObjValue() * solver_->getObjSense() ;
1268    }
1269
1270    /** The best solution to the integer programming problem.
1271
1272      The best solution to the integer programming problem found during
1273      the search. If no solution is found, the method returns null.
1274    */
1275
1276    inline double * bestSolution() const {
1277        return bestSolution_;
1278    }
1279    /** User callable setBestSolution.
1280        If check false does not check valid
1281        If true then sees if feasible and warns if objective value
1282        worse than given (so just set to COIN_DBL_MAX if you don't care).
1283        If check true then does not save solution if not feasible
1284    */
1285    void setBestSolution(const double * solution, int numberColumns,
1286                         double objectiveValue, bool check = false);
1287
1288    /// Get number of solutions
1289    inline int getSolutionCount() const {
1290        return numberSolutions_;
1291    }
1292
1293    /// Set number of solutions (so heuristics will be different)
1294    inline void setSolutionCount(int value) {
1295        numberSolutions_ = value;
1296    }
1297    /// Number of saved solutions (including best)
1298    int numberSavedSolutions() const;
1299    /// Maximum number of extra saved solutions
1300    inline int maximumSavedSolutions() const {
1301        return maximumSavedSolutions_;
1302    }
1303    /// Set maximum number of extra saved solutions
1304    void setMaximumSavedSolutions(int value);
1305    /// Return a saved solution (0==best) - NULL if off end
1306    const double * savedSolution(int which) const;
1307    /// Return a saved solution objective (0==best) - COIN_DBL_MAX if off end
1308    double savedSolutionObjective(int which) const;
1309    /// Delete a saved solution and move others up
1310    void deleteSavedSolution(int which);
1311
1312    /** Current phase (so heuristics etc etc can find out).
1313        0 - initial solve
1314        1 - solve with cuts at root
1315        2 - solve with cuts
1316        3 - other e.g. strong branching
1317        4 - trying to validate a solution
1318        5 - at end of search
1319    */
1320    inline int phase() const {
1321        return phase_;
1322    }
1323
1324    /// Get number of heuristic solutions
1325    inline int getNumberHeuristicSolutions() const {
1326        return numberHeuristicSolutions_;
1327    }
1328    /// Set number of heuristic solutions
1329    inline void setNumberHeuristicSolutions(int value) {
1330        numberHeuristicSolutions_ = value;
1331    }
1332
1333    /// Set objective function sense (1 for min (default), -1 for max,)
1334    inline void setObjSense(double s) {
1335        dblParam_[CbcOptimizationDirection] = s;
1336        solver_->setObjSense(s);
1337    }
1338
1339    /// Value of objective at continuous
1340    inline double getContinuousObjective() const {
1341        return originalContinuousObjective_;
1342    }
1343    inline void setContinuousObjective(double value) {
1344        originalContinuousObjective_ = value;
1345    }
1346    /// Number of infeasibilities at continuous
1347    inline int getContinuousInfeasibilities() const {
1348        return continuousInfeasibilities_;
1349    }
1350    inline void setContinuousInfeasibilities(int value) {
1351        continuousInfeasibilities_ = value;
1352    }
1353    /// Value of objective after root node cuts added
1354    inline double rootObjectiveAfterCuts() const {
1355        return continuousObjective_;
1356    }
1357    /// Sum of Changes to objective by first solve
1358    inline double sumChangeObjective() const {
1359        return sumChangeObjective1_;
1360    }
1361    /** Number of times global cuts violated.  When global cut pool then this
1362        should be kept for each cut and type of cut */
1363    inline int numberGlobalViolations() const {
1364        return numberGlobalViolations_;
1365    }
1366    inline void clearNumberGlobalViolations() {
1367        numberGlobalViolations_ = 0;
1368    }
1369    /// Whether to force a resolve after takeOffCuts
1370    inline bool resolveAfterTakeOffCuts() const {
1371        return resolveAfterTakeOffCuts_;
1372    }
1373    inline void setResolveAfterTakeOffCuts(bool yesNo) {
1374        resolveAfterTakeOffCuts_ = yesNo;
1375    }
1376    /// Maximum number of rows
1377    inline int maximumRows() const {
1378        return maximumRows_;
1379    }
1380    /// Work basis for temporary use
1381    inline CoinWarmStartBasis & workingBasis() {
1382        return workingBasis_;
1383    }
1384    /// Get number of "iterations" to stop after
1385    inline int getStopNumberIterations() const {
1386        return stopNumberIterations_;
1387    }
1388    /// Set number of "iterations" to stop after
1389    inline void setStopNumberIterations(int value) {
1390        stopNumberIterations_ = value;
1391    }
1392    //@}
1393
1394    /** \name Node selection */
1395    //@{
1396    // Comparison functions (which may be overridden by inheritance)
1397    inline CbcCompareBase * nodeComparison() const {
1398        return nodeCompare_;
1399    }
1400    void setNodeComparison(CbcCompareBase * compare);
1401    void setNodeComparison(CbcCompareBase & compare);
1402    //@}
1403
1404    /** \name Problem feasibility checking */
1405    //@{
1406    // Feasibility functions (which may be overridden by inheritance)
1407    inline CbcFeasibilityBase * problemFeasibility() const {
1408        return problemFeasibility_;
1409    }
1410    void setProblemFeasibility(CbcFeasibilityBase * feasibility);
1411    void setProblemFeasibility(CbcFeasibilityBase & feasibility);
1412    //@}
1413
1414    /** \name Tree methods and subtree methods */
1415    //@{
1416    /// Tree method e.g. heap (which may be overridden by inheritance)
1417    inline CbcTree * tree() const {
1418        return tree_;
1419    }
1420    /// For modifying tree handling (original is cloned)
1421    void passInTreeHandler(CbcTree & tree);
1422    /** For passing in an CbcModel to do a sub Tree (with derived tree handlers).
1423        Passed in model must exist for duration of branch and bound
1424    */
1425    void passInSubTreeModel(CbcModel & model);
1426    /** For retrieving a copy of subtree model with given OsiSolver.
1427        If no subtree model will use self (up to user to reset cutoff etc).
1428        If solver NULL uses current
1429    */
1430    CbcModel * subTreeModel(OsiSolverInterface * solver = NULL) const;
1431    /// Returns number of times any subtree stopped on nodes, time etc
1432    inline int numberStoppedSubTrees() const {
1433        return numberStoppedSubTrees_;
1434    }
1435    /// Says a sub tree was stopped
1436    inline void incrementSubTreeStopped() {
1437        numberStoppedSubTrees_++;
1438    }
1439    /** Whether to automatically do presolve before branch and bound (subTrees).
1440        0 - no
1441        1 - ordinary presolve
1442        2 - integer presolve (dodgy)
1443    */
1444    inline int typePresolve() const {
1445        return presolve_;
1446    }
1447    inline void setTypePresolve(int value) {
1448        presolve_ = value;
1449    }
1450
1451    //@}
1452
1453    /** \name Branching Decisions
1454
1455      See the CbcBranchDecision class for additional information.
1456    */
1457    //@{
1458
1459    /// Get the current branching decision method.
1460    inline CbcBranchDecision * branchingMethod() const {
1461        return branchingMethod_;
1462    }
1463    /// Set the branching decision method.
1464    inline void setBranchingMethod(CbcBranchDecision * method) {
1465        delete branchingMethod_;
1466        branchingMethod_ = method->clone();
1467    }
1468    /** Set the branching method
1469
1470      \overload
1471    */
1472    inline void setBranchingMethod(CbcBranchDecision & method) {
1473        delete branchingMethod_;
1474        branchingMethod_ = method.clone();
1475    }
1476    /// Get the current cut modifier method
1477    inline CbcCutModifier * cutModifier() const {
1478        return cutModifier_;
1479    }
1480    /// Set the cut modifier method
1481    void setCutModifier(CbcCutModifier * modifier);
1482    /** Set the cut modifier method
1483
1484      \overload
1485    */
1486    void setCutModifier(CbcCutModifier & modifier);
1487    //@}
1488
1489    /** \name Row (constraint) and Column (variable) cut generation */
1490    //@{
1491
1492    /** State of search
1493        0 - no solution
1494        1 - only heuristic solutions
1495        2 - branched to a solution
1496        3 - no solution but many nodes
1497    */
1498    inline int stateOfSearch() const {
1499        return stateOfSearch_;
1500    }
1501    inline void setStateOfSearch(int state) {
1502        stateOfSearch_ = state;
1503    }
1504    /// Strategy worked out - mainly at root node for use by CbcNode
1505    inline int searchStrategy() const {
1506        return searchStrategy_;
1507    }
1508    /// Set strategy worked out - mainly at root node for use by CbcNode
1509    inline void setSearchStrategy(int value) {
1510        searchStrategy_ = value;
1511    }
1512
1513    /// Get the number of cut generators
1514    inline int numberCutGenerators() const {
1515        return numberCutGenerators_;
1516    }
1517    /// Get the list of cut generators
1518    inline CbcCutGenerator ** cutGenerators() const {
1519        return generator_;
1520    }
1521    ///Get the specified cut generator
1522    inline CbcCutGenerator * cutGenerator(int i) const {
1523        return generator_[i];
1524    }
1525    ///Get the specified cut generator before any changes
1526    inline CbcCutGenerator * virginCutGenerator(int i) const {
1527        return virginGenerator_[i];
1528    }
1529    /** Add one generator - up to user to delete generators.
1530        howoften affects how generator is used. 0 or 1 means always,
1531        >1 means every that number of nodes.  Negative values have same
1532        meaning as positive but they may be switched off (-> -100) by code if
1533        not many cuts generated at continuous.  -99 is just done at root.
1534        Name is just for printout.
1535        If depth >0 overrides how often generator is called (if howOften==-1 or >0).
1536    */
1537    void addCutGenerator(CglCutGenerator * generator,
1538                         int howOften = 1, const char * name = NULL,
1539                         bool normal = true, bool atSolution = false,
1540                         bool infeasible = false, int howOftenInSub = -100,
1541                         int whatDepth = -1, int whatDepthInSub = -1);
1542//@}
1543    /** \name Strategy and sub models
1544
1545      See the CbcStrategy class for additional information.
1546    */
1547    //@{
1548
1549    /// Get the current strategy
1550    inline CbcStrategy * strategy() const {
1551        return strategy_;
1552    }
1553    /// Set the strategy. Clones
1554    void setStrategy(CbcStrategy & strategy);
1555    /// Set the strategy. assigns
1556    inline void setStrategy(CbcStrategy * strategy) {
1557        strategy_ = strategy;
1558    }
1559    /// Get the current parent model
1560    inline CbcModel * parentModel() const {
1561        return parentModel_;
1562    }
1563    /// Set the parent model
1564    inline void setParentModel(CbcModel & parentModel) {
1565        parentModel_ = &parentModel;
1566    }
1567    //@}
1568
1569
1570    /** \name Heuristics and priorities */
1571    //@{
1572    /*! \brief Add one heuristic - up to user to delete
1573
1574      The name is just used for print messages.
1575    */
1576    void addHeuristic(CbcHeuristic * generator, const char *name = NULL,
1577                      int before = -1);
1578    ///Get the specified heuristic
1579    inline CbcHeuristic * heuristic(int i) const {
1580        return heuristic_[i];
1581    }
1582    /// Get the number of heuristics
1583    inline int numberHeuristics() const {
1584        return numberHeuristics_;
1585    }
1586    /// Pointer to heuristic solver which found last solution (or NULL)
1587    inline CbcHeuristic * lastHeuristic() const {
1588        return lastHeuristic_;
1589    }
1590    /// set last heuristic which found a solution
1591    inline void setLastHeuristic(CbcHeuristic * last) {
1592        lastHeuristic_ = last;
1593    }
1594
1595    /** Pass in branching priorities.
1596
1597        If ifClique then priorities are on cliques otherwise priorities are
1598        on integer variables.
1599        Other type (if exists set to default)
1600        1 is highest priority. (well actually -INT_MAX is but that's ugly)
1601        If hotstart > 0 then branches are created to force
1602        the variable to the value given by best solution.  This enables a
1603        sort of hot start.  The node choice should be greatest depth
1604        and hotstart should normally be switched off after a solution.
1605
1606        If ifNotSimpleIntegers true then appended to normal integers
1607
1608        This is now deprecated except for simple usage.  If user
1609        creates Cbcobjects then set priority in them
1610
1611        \internal Added for Kurt Spielberg.
1612    */
1613    void passInPriorities(const int * priorities, bool ifNotSimpleIntegers);
1614
1615    /// Returns priority level for an object (or 1000 if no priorities exist)
1616    inline int priority(int sequence) const {
1617        return object_[sequence]->priority();
1618    }
1619
1620    /*! \brief Set an event handler
1621
1622      A clone of the handler passed as a parameter is stored in CbcModel.
1623    */
1624    void passInEventHandler(const CbcEventHandler *eventHandler) ;
1625
1626    /*! \brief Retrieve a pointer to the event handler */
1627    inline CbcEventHandler* getEventHandler() const {
1628        return (eventHandler_) ;
1629    }
1630
1631    //@}
1632
1633    /**@name Setting/Accessing application data */
1634    //@{
1635    /** Set application data.
1636
1637    This is a pointer that the application can store into and
1638    retrieve from the solver interface.
1639    This field is available for the application to optionally
1640    define and use.
1641    */
1642    void setApplicationData (void * appData);
1643
1644    /// Get application data
1645    void * getApplicationData() const;
1646    /**
1647        For advanced applications you may wish to modify the behavior of Cbc
1648        e.g. if the solver is a NLP solver then you may not have an exact
1649        optimum solution at each step.  Information could be built into
1650        OsiSolverInterface but this is an alternative so that that interface
1651        does not have to be changed.  If something similar is useful to
1652        enough solvers then it could be migrated
1653        You can also pass in by using solver->setAuxiliaryInfo.
1654        You should do that if solver is odd - if solver is normal simplex
1655        then use this.
1656        NOTE - characteristics are not cloned
1657    */
1658    void passInSolverCharacteristics(OsiBabSolver * solverCharacteristics);
1659    /// Get solver characteristics
1660    inline const OsiBabSolver * solverCharacteristics() const {
1661        return solverCharacteristics_;
1662    }
1663    //@}
1664
1665    //---------------------------------------------------------------------------
1666
1667    /**@name Message handling etc */
1668    //@{
1669    /// Pass in Message handler (not deleted at end)
1670    void passInMessageHandler(CoinMessageHandler * handler);
1671    /// Set language
1672    void newLanguage(CoinMessages::Language language);
1673    inline void setLanguage(CoinMessages::Language language) {
1674        newLanguage(language);
1675    }
1676    /// Return handler
1677    inline CoinMessageHandler * messageHandler() const {
1678        return handler_;
1679    }
1680    /// Return messages
1681    inline CoinMessages & messages() {
1682        return messages_;
1683    }
1684    /// Return pointer to messages
1685    inline CoinMessages * messagesPointer() {
1686        return &messages_;
1687    }
1688    /// Set log level
1689    void setLogLevel(int value);
1690    /// Get log level
1691    inline int logLevel() const {
1692        return handler_->logLevel();
1693    }
1694    /** Set flag to say if handler_ is the default handler.
1695
1696      The default handler is deleted when the model is deleted. Other
1697      handlers (supplied by the client) will not be deleted.
1698    */
1699    inline void setDefaultHandler(bool yesNo) {
1700        defaultHandler_ = yesNo;
1701    }
1702    //@}
1703    //---------------------------------------------------------------------------
1704    ///@name Specialized
1705    //@{
1706
1707    /**
1708        Set special options
1709        0 bit (1) - check if cuts valid (if on debugger list)
1710        1 bit (2) - use current basis to check integer solution (rather than all slack)
1711        2 bit (4) - don't check integer solution (by solving LP)
1712        3 bit (8) - fast analyze
1713        4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
1714        5 bit (32) - keep names
1715        6 bit (64) - try for dominated columns
1716        7 bit (128) - SOS type 1 but all declared integer
1717        8 bit (256) - Set to say solution just found, unset by doing cuts
1718        9 bit (512) - Try reduced model after 100 nodes
1719        10 bit (1024) - Switch on some heuristics even if seems unlikely
1720        11 bit (2048) - Mark as in small branch and bound
1721        12 bit (4096) - Funny cuts so do slow way (in some places)
1722        13 bit (8192) - Funny cuts so do slow way (in other places)
1723        14 bit (16384) - Use Cplex! for fathoming
1724        15 bit (32768) - Try reduced model after 0 nodes
1725        16 bit (65536) - Original model had integer bounds
1726        17 bit (131072) - Perturbation switched off
1727        18 bit (262144) - donor CbcModel
1728        19 bit (524288) - recipient CbcModel
1729        20 bit (1048576) - waiting for sub model to return
1730    */
1731    inline void setSpecialOptions(int value) {
1732        specialOptions_ = value;
1733    }
1734    /// Get special options
1735    inline int specialOptions() const {
1736        return specialOptions_;
1737    }
1738    /// Tell model to stop on event
1739    inline void sayEventHappened()
1740    { eventHappened_=true;}
1741    /// Says if normal solver i.e. has well defined CoinPackedMatrix
1742    inline bool normalSolver() const {
1743        return (specialOptions_&16) == 0;
1744    }
1745    /** Says if model is sitting there waiting for mini branch and bound to finish
1746        This is because an event handler may only have access to parent model in
1747        mini branch and bound
1748    */
1749    inline bool waitingForMiniBranchAndBound() const {
1750        return (specialOptions_&1048576) != 0;
1751    }
1752    /** Set more special options
1753        at present bottom 6 bits used for shadow price mode
1754        1024 for experimental hotstart
1755        2048,4096 breaking out of cuts
1756        8192 slowly increase minimum drop
1757        16384 gomory
1758        32768 more heuristics in sub trees
1759        65536 no cuts in preprocessing
1760        131072 Time limits elapsed
1761        18 bit (262144) - Perturb fathom nodes
1762        19 bit (524288) - No limit on fathom nodes
1763        20 bit (1048576) - Reduce sum of infeasibilities before cuts
1764        21 bit (2097152) - Reduce sum of infeasibilities after cuts
1765    */
1766    inline void setMoreSpecialOptions(int value) {
1767        moreSpecialOptions_ = value;
1768    }
1769    /// Get more special options
1770    inline int moreSpecialOptions() const {
1771        return moreSpecialOptions_;
1772    }
1773  /// Set time method
1774    inline void setUseElapsedTime(bool yesNo) {
1775        if (yesNo)
1776          moreSpecialOptions_ |= 131072;
1777        else
1778          moreSpecialOptions_ &= ~131072;
1779    }
1780    /// Get time method
1781    inline bool useElapsedTime() const {
1782        return (moreSpecialOptions_&131072)!=0;
1783    }
1784    /// Go to dantzig pivot selection if easy problem (clp only)
1785#ifdef COIN_HAS_CLP
1786    void goToDantzig(int numberNodes, ClpDualRowPivot *& savePivotMethod);
1787#endif
1788    /// Now we may not own objects - just point to solver's objects
1789    inline bool ownObjects() const {
1790        return ownObjects_;
1791    }
1792    /// Check original model before it gets messed up
1793    void checkModel();
1794    //@}
1795    //---------------------------------------------------------------------------
1796
1797    ///@name Constructors and destructors etc
1798    //@{
1799    /// Default Constructor
1800    CbcModel();
1801
1802    /// Constructor from solver
1803    CbcModel(const OsiSolverInterface &);
1804
1805    /** Assign a solver to the model (model assumes ownership)
1806
1807      On return, \p solver will be NULL.
1808      If deleteSolver then current solver deleted (if model owned)
1809
1810      \note Parameter settings in the outgoing solver are not inherited by
1811        the incoming solver.
1812    */
1813    void assignSolver(OsiSolverInterface *&solver, bool deleteSolver = true);
1814
1815    /** \brief Set ownership of solver
1816
1817      A parameter of false tells CbcModel it does not own the solver and
1818      should not delete it. Once you claim ownership of the solver, you're
1819      responsible for eventually deleting it. Note that CbcModel clones
1820      solvers with abandon.  Unless you have a deep understanding of the
1821      workings of CbcModel, the only time you want to claim ownership is when
1822      you're about to delete the CbcModel object but want the solver to
1823      continue to exist (as, for example, when branchAndBound has finished
1824      and you want to hang on to the answer).
1825    */
1826    inline void setModelOwnsSolver (bool ourSolver) {
1827        ownership_ = ourSolver ? (ownership_ | 0x80000000) : (ownership_ & (~0x80000000)) ;
1828    }
1829
1830    /*! \brief Get ownership of solver
1831
1832      A return value of true means that CbcModel owns the solver and will
1833      take responsibility for deleting it when that becomes necessary.
1834    */
1835    inline bool modelOwnsSolver () {
1836        return ((ownership_&0x80000000) != 0) ;
1837    }
1838
1839    /** Copy constructor .
1840      If cloneHandler is true then message handler is cloned
1841    */
1842    CbcModel(const CbcModel & rhs, bool cloneHandler = false);
1843
1844    /// Assignment operator
1845    CbcModel & operator=(const CbcModel& rhs);
1846
1847    /// Destructor
1848    ~CbcModel ();
1849
1850    /// Returns solver - has current state
1851    inline OsiSolverInterface * solver() const {
1852        return solver_;
1853    }
1854
1855    /// Returns current solver - sets new one
1856    inline OsiSolverInterface * swapSolver(OsiSolverInterface * solver) {
1857        OsiSolverInterface * returnSolver = solver_;
1858        solver_ = solver;
1859        return returnSolver;
1860    }
1861
1862    /// Returns solver with continuous state
1863    inline OsiSolverInterface * continuousSolver() const {
1864        return continuousSolver_;
1865    }
1866
1867    /// Create solver with continuous state
1868    inline void createContinuousSolver() {
1869        continuousSolver_ = solver_->clone();
1870    }
1871    /// Clear solver with continuous state
1872    inline void clearContinuousSolver() {
1873        delete continuousSolver_;
1874        continuousSolver_ = NULL;
1875    }
1876
1877    /// A copy of the solver, taken at constructor or by saveReferenceSolver
1878    inline OsiSolverInterface * referenceSolver() const {
1879        return referenceSolver_;
1880    }
1881
1882    /// Save a copy of the current solver so can be reset to
1883    void saveReferenceSolver();
1884
1885    /** Uses a copy of reference solver to be current solver.
1886        Because of possible mismatches all exotic integer information is loat
1887        (apart from normal information in OsiSolverInterface)
1888        so SOS etc and priorities will have to be redone
1889    */
1890    void resetToReferenceSolver();
1891
1892    /// Clears out as much as possible (except solver)
1893    void gutsOfDestructor();
1894    /** Clears out enough to reset CbcModel as if no branch and bound done
1895     */
1896    void gutsOfDestructor2();
1897    /** Clears out enough to reset CbcModel cutoff etc
1898     */
1899    void resetModel();
1900    /** Most of copy constructor
1901        mode - 0 copy but don't delete before
1902               1 copy and delete before
1903           2 copy and delete before (but use virgin generators)
1904    */
1905    void gutsOfCopy(const CbcModel & rhs, int mode = 0);
1906    /// Move status, nodes etc etc across
1907    void moveInfo(const CbcModel & rhs);
1908    //@}
1909
1910    ///@name Multithreading
1911    //@{
1912    /// Indicates whether Cbc library has been compiled with multithreading support
1913    static bool haveMultiThreadSupport();
1914    /// Get pointer to masterthread
1915    CbcThread * masterThread() const {
1916        return masterThread_;
1917    }
1918    /// Get pointer to walkback
1919    CbcNodeInfo ** walkback() const {
1920        return walkback_;
1921    }
1922    /// Get number of threads
1923    inline int getNumberThreads() const {
1924        return numberThreads_;
1925    }
1926    /// Set number of threads
1927    inline void setNumberThreads(int value) {
1928        numberThreads_ = value;
1929    }
1930    /// Get thread mode
1931    inline int getThreadMode() const {
1932        return threadMode_;
1933    }
1934    /** Set thread mode
1935        always use numberThreads for branching
1936        1 set then deterministic
1937        2 set then use numberThreads for root cuts
1938        4 set then use numberThreads in root mini branch and bound
1939        8 set and numberThreads - do heuristics numberThreads at a time
1940        8 set and numberThreads==0 do all heuristics at once
1941        default is 0
1942    */
1943    inline void setThreadMode(int value) {
1944        threadMode_ = value;
1945    }
1946    /** Return
1947        -2 if deterministic threaded and main thread
1948        -1 if deterministic threaded and serial thread
1949        0 if serial
1950        1 if opportunistic threaded
1951    */
1952    inline int parallelMode() const {
1953        if (!numberThreads_) {
1954            if ((threadMode_&1) == 0)
1955                return 0;
1956            else
1957                return -1;
1958            return 0;
1959        } else {
1960            if ((threadMode_&1) == 0)
1961                return 1;
1962            else
1963                return -2;
1964        }
1965    }
1966    /// From here to end of section - code in CbcThread.cpp until class changed
1967    /// Returns true if locked
1968    bool isLocked() const;
1969#ifdef CBC_THREAD
1970    /**
1971       Locks a thread if parallel so that stuff like cut pool
1972       can be updated and/or used.
1973    */
1974    void lockThread();
1975    /**
1976       Unlocks a thread if parallel to say cut pool stuff not needed
1977    */
1978    void unlockThread();
1979#else
1980    inline void lockThread() {}
1981    inline void unlockThread() {}
1982#endif
1983    /** Set information in a child
1984        -3 pass pointer to child thread info
1985        -2 just stop
1986        -1 delete simple child stuff
1987        0 delete opportunistic child stuff
1988        1 delete deterministic child stuff
1989    */
1990    void setInfoInChild(int type, CbcThread * info);
1991    /** Move/copy information from one model to another
1992        -1 - initialization
1993        0 - from base model
1994        1 - to base model (and reset)
1995        2 - add in final statistics etc (and reset so can do clean destruction)
1996    */
1997    void moveToModel(CbcModel * baseModel, int mode);
1998    /// Split up nodes
1999    int splitModel(int numberModels, CbcModel ** model,
2000                   int numberNodes);
2001    /// Start threads
2002    void startSplitModel(int numberIterations);
2003    /// Merge models
2004    void mergeModels(int numberModel, CbcModel ** model,
2005                     int numberNodes);
2006    //@}
2007
2008    ///@name semi-private i.e. users should not use
2009    //@{
2010    /// Get how many Nodes it took to solve the problem.
2011    int getNodeCount2() const {
2012        return numberNodes2_;
2013    }
2014    /// Set pointers for speed
2015    void setPointers(const OsiSolverInterface * solver);
2016    /** Perform reduced cost fixing
2017
2018      Fixes integer variables at their current value based on reduced cost
2019      penalties.  Returns number fixed
2020    */
2021    int reducedCostFix() ;
2022    /** Makes all handlers same.  If makeDefault 1 then makes top level
2023        default and rest point to that.  If 2 then each is copy
2024    */
2025    void synchronizeHandlers(int makeDefault);
2026    /// Save a solution to saved list
2027    void saveExtraSolution(const double * solution, double objectiveValue);
2028    /// Save a solution to best and move current to saved
2029    void saveBestSolution(const double * solution, double objectiveValue);
2030    /// Delete best and saved solutions
2031    void deleteSolutions();
2032    /// Encapsulates solver resolve
2033    int resolve(OsiSolverInterface * solver);
2034#ifdef CLP_RESOLVE
2035    /// Special purpose resolve
2036    int resolveClp(OsiClpSolverInterface * solver, int type);
2037#endif
2038
2039    /** Encapsulates choosing a variable -
2040        anyAction -2, infeasible (-1 round again), 0 done
2041    */
2042    int chooseBranch(CbcNode * & newNode, int numberPassesLeft,
2043                     CbcNode * oldNode, OsiCuts & cuts,
2044                     bool & resolved, CoinWarmStartBasis *lastws,
2045                     const double * lowerBefore, const double * upperBefore,
2046                     OsiSolverBranch * & branches);
2047    int chooseBranch(CbcNode * newNode, int numberPassesLeft, bool & resolved);
2048
2049    /** Return an empty basis object of the specified size
2050
2051      A useful utility when constructing a basis for a subproblem from scratch.
2052      The object returned will be of the requested capacity and appropriate for
2053      the solver attached to the model.
2054    */
2055    CoinWarmStartBasis *getEmptyBasis(int ns = 0, int na = 0) const ;
2056
2057    /** Remove inactive cuts from the model
2058
2059      An OsiSolverInterface is expected to maintain a valid basis, but not a
2060      valid solution, when loose cuts are deleted. Restoring a valid solution
2061      requires calling the solver to reoptimise. If it's certain the solution
2062      will not be required, set allowResolve to false to suppress
2063      reoptimisation.
2064      If saveCuts then slack cuts will be saved
2065      On input current cuts are cuts and newCuts
2066      on exit current cuts will be correct.  Returns number dropped
2067    */
2068    int takeOffCuts(OsiCuts &cuts,
2069                    bool allowResolve, OsiCuts * saveCuts,
2070                    int numberNewCuts = 0, const OsiRowCut ** newCuts = NULL) ;
2071
2072    /** Determine and install the active cuts that need to be added for
2073      the current subproblem
2074
2075      The whole truth is a bit more complicated. The first action is a call to
2076      addCuts1(). addCuts() then sorts through the list, installs the tight
2077      cuts in the model, and does bookkeeping (adjusts reference counts).
2078      The basis returned from addCuts1() is adjusted accordingly.
2079
2080      If it turns out that the node should really be fathomed by bound,
2081      addCuts() simply treats all the cuts as loose as it does the bookkeeping.
2082
2083      canFix true if extra information being passed
2084    */
2085    int addCuts(CbcNode * node, CoinWarmStartBasis *&lastws, bool canFix);
2086
2087    /** Traverse the tree from node to root and prep the model
2088
2089      addCuts1() begins the job of prepping the model to match the current
2090      subproblem. The model is stripped of all cuts, and the search tree is
2091      traversed from node to root to determine the changes required. Appropriate
2092      bounds changes are installed, a list of cuts is collected but not
2093      installed, and an appropriate basis (minus the cuts, but big enough to
2094      accommodate them) is constructed.
2095
2096      Returns true if new problem similar to old
2097
2098      \todo addCuts1() is called in contexts where it's known in advance that
2099        all that's desired is to determine a list of cuts and do the
2100        bookkeeping (adjust the reference counts). The work of installing
2101        bounds and building a basis goes to waste.
2102    */
2103    bool addCuts1(CbcNode * node, CoinWarmStartBasis *&lastws);
2104    /** Returns bounds just before where - initially original bounds.
2105        Also sets downstream nodes (lower if force 1, upper if 2)
2106    */
2107    void previousBounds (CbcNode * node, CbcNodeInfo * where, int iColumn,
2108                         double & lower, double & upper, int force);
2109    /** Set objective value in a node.  This is separated out so that
2110       odd solvers can use.  It may look at extra information in
2111       solverCharacteriscs_ and will also use bound from parent node
2112    */
2113    void setObjectiveValue(CbcNode * thisNode, const CbcNode * parentNode) const;
2114
2115    /** If numberBeforeTrust >0 then we are going to use CbcBranchDynamic.
2116        Scan and convert CbcSimpleInteger objects
2117    */
2118    void convertToDynamic();
2119    /// Set numberBeforeTrust in all objects
2120    void synchronizeNumberBeforeTrust(int type = 0);
2121    /// Zap integer information in problem (may leave object info)
2122    void zapIntegerInformation(bool leaveObjects = true);
2123    /// Use cliques for pseudocost information - return nonzero if infeasible
2124    int cliquePseudoCosts(int doStatistics);
2125    /// Fill in useful estimates
2126    void pseudoShadow(int type);
2127    /** Return pseudo costs
2128        If not all integers or not pseudo costs - returns all zero
2129        Length of arrays are numberIntegers() and entries
2130        correspond to integerVariable()[i]
2131        User must allocate arrays before call
2132    */
2133    void fillPseudoCosts(double * downCosts, double * upCosts,
2134                         int * priority = NULL,
2135                         int * numberDown = NULL, int * numberUp = NULL,
2136                         int * numberDownInfeasible = NULL,
2137                         int * numberUpInfeasible = NULL) const;
2138    /** Do heuristics at root.
2139        0 - don't delete
2140        1 - delete
2141        2 - just delete - don't even use
2142    */
2143    void doHeuristicsAtRoot(int deleteHeuristicsAfterwards = 0);
2144    /// Adjust heuristics based on model
2145    void adjustHeuristics();
2146    /// Get the hotstart solution
2147    inline const double * hotstartSolution() const {
2148        return hotstartSolution_;
2149    }
2150    /// Get the hotstart priorities
2151    inline const int * hotstartPriorities() const {
2152        return hotstartPriorities_;
2153    }
2154
2155    /// Return the list of cuts initially collected for this subproblem
2156    inline CbcCountRowCut ** addedCuts() const {
2157        return addedCuts_;
2158    }
2159    /// Number of entries in the list returned by #addedCuts()
2160    inline int currentNumberCuts() const {
2161        return currentNumberCuts_;
2162    }
2163    /// Global cuts
2164    inline OsiCuts * globalCuts() {
2165        return &globalCuts_;
2166    }
2167    /// Copy and set a pointer to a row cut which will be added instead of normal branching.
2168    void setNextRowCut(const OsiRowCut & cut);
2169    /// Get a pointer to current node (be careful)
2170    inline CbcNode * currentNode() const {
2171        return currentNode_;
2172    }
2173    /// Get a pointer to probing info
2174    inline CglTreeProbingInfo * probingInfo() const {
2175        return probingInfo_;
2176    }
2177    /// Thread specific random number generator
2178    inline CoinThreadRandom * randomNumberGenerator() {
2179        return &randomNumberGenerator_;
2180    }
2181    /// Set the number of iterations done in strong branching.
2182    inline void setNumberStrongIterations(int number) {
2183        numberStrongIterations_ = number;
2184    }
2185    /// Get the number of iterations done in strong branching.
2186    inline int numberStrongIterations() const {
2187        return numberStrongIterations_;
2188    }
2189    /// Get maximum number of iterations (designed to be used in heuristics)
2190    inline int maximumNumberIterations() const {
2191        return maximumNumberIterations_;
2192    }
2193    /// Set maximum number of iterations (designed to be used in heuristics)
2194    inline void setMaximumNumberIterations(int value) {
2195        maximumNumberIterations_ = value;
2196    }
2197# ifdef COIN_HAS_CLP
2198    /// Set depth for fast nodes
2199    inline void setFastNodeDepth(int value) {
2200        fastNodeDepth_ = value;
2201    }
2202    /// Get depth for fast nodes
2203    inline int fastNodeDepth() const {
2204        return fastNodeDepth_;
2205    }
2206    /// Get anything with priority >= this can be treated as continuous
2207    inline int continuousPriority() const {
2208        return continuousPriority_;
2209    }
2210    /// Set anything with priority >= this can be treated as continuous
2211    inline void setContinuousPriority(int value) {
2212        continuousPriority_ = value;
2213    }
2214    inline void incrementExtra(int nodes, int iterations) {
2215        numberExtraNodes_ += nodes;
2216        numberExtraIterations_ += iterations;
2217    }
2218#endif
2219    /// Number of extra iterations
2220    inline int numberExtraIterations() const {
2221        return numberExtraIterations_;
2222    }
2223    /// Increment strong info
2224    void incrementStrongInfo(int numberTimes, int numberIterations,
2225                             int numberFixed, bool ifInfeasible);
2226    /// Return strong info
2227    inline const int * strongInfo() const {
2228        return strongInfo_;
2229    }
2230
2231    /// Return mutable strong info
2232    inline int * mutableStrongInfo() {
2233        return strongInfo_;
2234    }
2235    /// Get stored row cuts for donor/recipient CbcModel
2236    CglStored * storedRowCuts() const {
2237        return storedRowCuts_;
2238    }
2239    /// Set stored row cuts for donor/recipient CbcModel
2240    void setStoredRowCuts(CglStored * cuts) {
2241        storedRowCuts_ = cuts;
2242    }
2243    /// Says whether all dynamic integers
2244    inline bool allDynamic () const {
2245        return ((ownership_&0x40000000) != 0) ;
2246    }
2247    /// Create C++ lines to get to current state
2248    void generateCpp( FILE * fp, int options);
2249    /// Generate an OsiBranchingInformation object
2250    OsiBranchingInformation usefulInformation() const;
2251    /** Warm start object produced by heuristic or strong branching
2252
2253        If get a valid integer solution outside branch and bound then it can take
2254        a reasonable time to solve LP which produces clean solution.  If this object has
2255        any size then it will be used in solve.
2256    */
2257    inline void setBestSolutionBasis(const CoinWarmStartBasis & bestSolutionBasis) {
2258        bestSolutionBasis_ = bestSolutionBasis;
2259    }
2260    /// Redo walkback arrays
2261    void redoWalkBack();
2262    //@}
2263
2264//---------------------------------------------------------------------------
2265
2266private:
2267    ///@name Private member data
2268    //@{
2269
2270    /// The solver associated with this model.
2271    OsiSolverInterface * solver_;
2272
2273    /** Ownership of objects and other stuff
2274
2275        0x80000000 model owns solver
2276        0x40000000 all variables CbcDynamicPseudoCost
2277    */
2278    unsigned int ownership_ ;
2279
2280    /// A copy of the solver, taken at the continuous (root) node.
2281    OsiSolverInterface * continuousSolver_;
2282
2283    /// A copy of the solver, taken at constructor or by saveReferenceSolver
2284    OsiSolverInterface * referenceSolver_;
2285
2286    /// Message handler
2287    CoinMessageHandler * handler_;
2288
2289    /** Flag to say if handler_ is the default handler.
2290
2291      The default handler is deleted when the model is deleted. Other
2292      handlers (supplied by the client) will not be deleted.
2293    */
2294    bool defaultHandler_;
2295
2296    /// Cbc messages
2297    CoinMessages messages_;
2298
2299    /// Array for integer parameters
2300    int intParam_[CbcLastIntParam];
2301
2302    /// Array for double parameters
2303    double dblParam_[CbcLastDblParam];
2304
2305    /** Pointer to an empty warm start object
2306
2307      It turns out to be useful to have this available as a base from
2308      which to build custom warm start objects. This is typed as CoinWarmStart
2309      rather than CoinWarmStartBasis to allow for the possibility that a
2310      client might want to apply a solver that doesn't use a basis-based warm
2311      start. See getEmptyBasis for an example of how this field can be used.
2312    */
2313    mutable CoinWarmStart *emptyWarmStart_ ;
2314
2315    /// Best objective
2316    double bestObjective_;
2317    /// Best possible objective
2318    double bestPossibleObjective_;
2319    /// Sum of Changes to objective by first solve
2320    double sumChangeObjective1_;
2321    /// Sum of Changes to objective by subsequent solves
2322    double sumChangeObjective2_;
2323
2324    /// Array holding the incumbent (best) solution.
2325    double * bestSolution_;
2326    /// Arrays holding other solutions.
2327    double ** savedSolutions_;
2328
2329    /** Array holding the current solution.
2330
2331      This array is used more as a temporary.
2332    */
2333    double * currentSolution_;
2334    /** For testing infeasibilities - will point to
2335        currentSolution_ or solver-->getColSolution()
2336    */
2337    mutable const double * testSolution_;
2338    /** Warm start object produced by heuristic or strong branching
2339
2340        If get a valid integer solution outside branch and bound then it can take
2341        a reasonable time to solve LP which produces clean solution.  If this object has
2342        any size then it will be used in solve.
2343    */
2344    CoinWarmStartBasis bestSolutionBasis_ ;
2345    /// Global cuts
2346    OsiCuts globalCuts_;
2347
2348    /// Minimum degradation in objective value to continue cut generation
2349    double minimumDrop_;
2350    /// Number of solutions
2351    int numberSolutions_;
2352    /// Number of saved solutions
2353    int numberSavedSolutions_;
2354    /// Maximum number of saved solutions
2355    int maximumSavedSolutions_;
2356    /** State of search
2357        0 - no solution
2358        1 - only heuristic solutions
2359        2 - branched to a solution
2360        3 - no solution but many nodes
2361    */
2362    int stateOfSearch_;
2363    /// At which depths to do cuts
2364    int whenCuts_;
2365    /// Hotstart solution
2366    double * hotstartSolution_;
2367    /// Hotstart priorities
2368    int * hotstartPriorities_;
2369    /// Number of heuristic solutions
2370    int numberHeuristicSolutions_;
2371    /// Cumulative number of nodes
2372    int numberNodes_;
2373    /** Cumulative number of nodes for statistics.
2374        Must fix to match up
2375    */
2376    int numberNodes2_;
2377    /// Cumulative number of iterations
2378    int numberIterations_;
2379    /// Cumulative number of solves
2380    int numberSolves_;
2381    /// Status of problem - 0 finished, 1 stopped, 2 difficulties
2382    int status_;
2383    /** Secondary status of problem
2384        -1 unset (status_ will also be -1)
2385        0 search completed with solution
2386        1 linear relaxation not feasible (or worse than cutoff)
2387        2 stopped on gap
2388        3 stopped on nodes
2389        4 stopped on time
2390        5 stopped on user event
2391        6 stopped on solutions
2392     */
2393    int secondaryStatus_;
2394    /// Number of integers in problem
2395    int numberIntegers_;
2396    /// Number of rows at continuous
2397    int numberRowsAtContinuous_;
2398    /// Maximum number of cuts
2399    int maximumNumberCuts_;
2400    /** Current phase (so heuristics etc etc can find out).
2401        0 - initial solve
2402        1 - solve with cuts at root
2403        2 - solve with cuts
2404        3 - other e.g. strong branching
2405        4 - trying to validate a solution
2406        5 - at end of search
2407    */
2408    int phase_;
2409
2410    /// Number of entries in #addedCuts_
2411    int currentNumberCuts_;
2412
2413    /** Current limit on search tree depth
2414
2415      The allocated size of #walkback_. Increased as needed.
2416    */
2417    int maximumDepth_;
2418    /** Array used to assemble the path between a node and the search tree root
2419
2420      The array is resized when necessary. #maximumDepth_  is the current
2421      allocated size.
2422    */
2423    CbcNodeInfo ** walkback_;
2424    CbcNodeInfo ** lastNodeInfo_;
2425    const OsiRowCut ** lastCut_;
2426    int lastDepth_;
2427    int lastNumberCuts2_;
2428    int maximumCuts_;
2429    int * lastNumberCuts_;
2430
2431    /** The list of cuts initially collected for this subproblem
2432
2433      When the subproblem at this node is rebuilt, a set of cuts is collected
2434      for inclusion in the constraint system. If any of these cuts are
2435      subsequently removed because they have become loose, the corresponding
2436      entry is set to NULL.
2437    */
2438    CbcCountRowCut ** addedCuts_;
2439
2440    /** A pointer to a row cut which will be added instead of normal branching.
2441        After use it should be set to NULL.
2442    */
2443    OsiRowCut * nextRowCut_;
2444
2445    /// Current node so can be used elsewhere
2446    CbcNode * currentNode_;
2447
2448    /// Indices of integer variables
2449    int * integerVariable_;
2450    /// Whether of not integer
2451    char * integerInfo_;
2452    /// Holds solution at continuous (after cuts)
2453    double * continuousSolution_;
2454    /// Array marked whenever a solution is found if non-zero
2455    int * usedInSolution_;
2456    /**
2457        Special options
2458        0 bit (1) - check if cuts valid (if on debugger list)
2459        1 bit (2) - use current basis to check integer solution (rather than all slack)
2460        2 bit (4) - don't check integer solution (by solving LP)
2461        3 bit (8) - fast analyze
2462        4 bit (16) - non-linear model - so no well defined CoinPackedMatrix
2463        5 bit (32) - keep names
2464        6 bit (64) - try for dominated columns
2465        7 bit (128) - SOS type 1 but all declared integer
2466        8 bit (256) - Set to say solution just found, unset by doing cuts
2467        9 bit (512) - Try reduced model after 100 nodes
2468        10 bit (1024) - Switch on some heuristics even if seems unlikely
2469        11 bit (2048) - Mark as in small branch and bound
2470        12 bit (4096) - Funny cuts so do slow way (in some places)
2471        13 bit (8192) - Funny cuts so do slow way (in other places)
2472        14 bit (16384) - Use Cplex! for fathoming
2473        15 bit (32768) - Try reduced model after 0 nodes
2474        16 bit (65536) - Original model had integer bounds
2475        17 bit (131072) - Perturbation switched off
2476        18 bit (262144) - donor CbcModel
2477        19 bit (524288) - recipient CbcModel
2478    */
2479    int specialOptions_;
2480    /** More special options
2481        at present bottom 6 bits used for shadow price mode
2482        1024 for experimental hotstart
2483        2048,4096 breaking out of cuts
2484        8192 slowly increase minimum drop
2485        16384 gomory
2486        32768 more heuristics in sub trees
2487        65536 no cuts in preprocessing
2488        131072 Time limits elapsed
2489        18 bit (262144) - Perturb fathom nodes
2490        19 bit (524288) - No limit on fathom nodes
2491        20 bit (1048576) - Reduce sum of infeasibilities before cuts
2492        21 bit (2097152) - Reduce sum of infeasibilities after cuts
2493    */
2494    int moreSpecialOptions_;
2495    /// User node comparison function
2496    CbcCompareBase * nodeCompare_;
2497    /// User feasibility function (see CbcFeasibleBase.hpp)
2498    CbcFeasibilityBase * problemFeasibility_;
2499    /// Tree
2500    CbcTree * tree_;
2501    /// A pointer to model to be used for subtrees
2502    CbcModel * subTreeModel_;
2503    /// Number of times any subtree stopped on nodes, time etc
2504    int numberStoppedSubTrees_;
2505    /// Variable selection function
2506    CbcBranchDecision * branchingMethod_;
2507    /// Cut modifier function
2508    CbcCutModifier * cutModifier_;
2509    /// Strategy
2510    CbcStrategy * strategy_;
2511    /// Parent model
2512    CbcModel * parentModel_;
2513    /** Whether to automatically do presolve before branch and bound.
2514        0 - no
2515        1 - ordinary presolve
2516        2 - integer presolve (dodgy)
2517    */
2518    /// Pointer to array[getNumCols()] (for speed) of column lower bounds
2519    const double * cbcColLower_;
2520    /// Pointer to array[getNumCols()] (for speed) of column upper bounds
2521    const double * cbcColUpper_;
2522    /// Pointer to array[getNumRows()] (for speed) of row lower bounds
2523    const double * cbcRowLower_;
2524    /// Pointer to array[getNumRows()] (for speed) of row upper bounds
2525    const double * cbcRowUpper_;
2526    /// Pointer to array[getNumCols()] (for speed) of primal solution vector
2527    const double * cbcColSolution_;
2528    /// Pointer to array[getNumRows()] (for speed) of dual prices
2529    const double * cbcRowPrice_;
2530    /// Get a pointer to array[getNumCols()] (for speed) of reduced costs
2531    const double * cbcReducedCost_;
2532    /// Pointer to array[getNumRows()] (for speed) of row activity levels.
2533    const double * cbcRowActivity_;
2534    /// Pointer to user-defined data structure
2535    void * appData_;
2536    /// Presolve for CbcTreeLocal
2537    int presolve_;
2538    /** Maximum number of candidates to consider for strong branching.
2539      To disable strong branching, set this to 0.
2540    */
2541    int numberStrong_;
2542    /** \brief The number of branches before pseudo costs believed
2543           in dynamic strong branching.
2544
2545      A value of 0 is  off.
2546    */
2547    int numberBeforeTrust_;
2548    /** \brief The number of variables for which to compute penalties
2549           in dynamic strong branching.
2550    */
2551    int numberPenalties_;
2552    /// For threads - stop after this many "iterations"
2553    int stopNumberIterations_;
2554    /** Scale factor to make penalties match strong.
2555        Should/will be computed */
2556    double penaltyScaleFactor_;
2557    /// Number of analyze iterations to do
2558    int numberAnalyzeIterations_;
2559    /// Arrays with analysis results
2560    double * analyzeResults_;
2561    /// Number of nodes infeasible by normal branching (before cuts)
2562    int numberInfeasibleNodes_;
2563    /** Problem type as set by user or found by analysis.  This will be extended
2564        0 - not known
2565        1 - Set partitioning <=
2566        2 - Set partitioning ==
2567        3 - Set covering
2568    */
2569    int problemType_;
2570    /// Print frequency
2571    int printFrequency_;
2572    /// Number of cut generators
2573    int numberCutGenerators_;
2574    // Cut generators
2575    CbcCutGenerator ** generator_;
2576    // Cut generators before any changes
2577    CbcCutGenerator ** virginGenerator_;
2578    /// Number of heuristics
2579    int numberHeuristics_;
2580    /// Heuristic solvers
2581    CbcHeuristic ** heuristic_;
2582    /// Pointer to heuristic solver which found last solution (or NULL)
2583    CbcHeuristic * lastHeuristic_;
2584    /// Depth for fast nodes
2585    int fastNodeDepth_;
2586    /*! Pointer to the event handler */
2587# ifdef CBC_ONLY_CLP
2588    ClpEventHandler *eventHandler_ ;
2589# else
2590    CbcEventHandler *eventHandler_ ;
2591# endif
2592
2593    /// Total number of objects
2594    int numberObjects_;
2595
2596    /** \brief Integer and Clique and ... information
2597
2598      \note The code assumes that the first objects on the list will be
2599        SimpleInteger objects for each integer variable, followed by
2600        Clique objects. Portions of the code that understand Clique objects
2601        will fail if they do not immediately follow the SimpleIntegers.
2602        Large chunks of the code will fail if the first objects are not
2603        SimpleInteger. As of 2003.08, SimpleIntegers and Cliques are the only
2604        objects.
2605    */
2606    OsiObject ** object_;
2607    /// Now we may not own objects - just point to solver's objects
2608    bool ownObjects_;
2609
2610    /// Original columns as created by integerPresolve or preprocessing
2611    int * originalColumns_;
2612    /// How often to scan global cuts
2613    int howOftenGlobalScan_;
2614    /** Number of times global cuts violated.  When global cut pool then this
2615        should be kept for each cut and type of cut */
2616    int numberGlobalViolations_;
2617    /// Number of extra iterations in fast lp
2618    int numberExtraIterations_;
2619    /// Number of extra nodes in fast lp
2620    int numberExtraNodes_;
2621    /** Value of objective at continuous
2622        (Well actually after initial round of cuts)
2623    */
2624    double continuousObjective_;
2625    /** Value of objective before root node cuts added
2626    */
2627    double originalContinuousObjective_;
2628    /// Number of infeasibilities at continuous
2629    int continuousInfeasibilities_;
2630    /// Maximum number of cut passes at root
2631    int maximumCutPassesAtRoot_;
2632    /// Maximum number of cut passes
2633    int maximumCutPasses_;
2634    /// Preferred way of branching
2635    int preferredWay_;
2636    /// Current cut pass number
2637    int currentPassNumber_;
2638    /// Maximum number of cuts (for whichGenerator_)
2639    int maximumWhich_;
2640    /// Maximum number of rows
2641    int maximumRows_;
2642    /// Current depth
2643    int currentDepth_;
2644    /// Thread specific random number generator
2645    mutable CoinThreadRandom randomNumberGenerator_;
2646    /// Work basis for temporary use
2647    CoinWarmStartBasis workingBasis_;
2648    /// Which cut generator generated this cut
2649    int * whichGenerator_;
2650    /// Maximum number of statistics
2651    int maximumStatistics_;
2652    /// statistics
2653    CbcStatistics ** statistics_;
2654    /// Maximum depth reached
2655    int maximumDepthActual_;
2656    /// Number of reduced cost fixings
2657    double numberDJFixed_;
2658    /// Probing info
2659    CglTreeProbingInfo * probingInfo_;
2660    /// Number of fixed by analyze at root
2661    int numberFixedAtRoot_;
2662    /// Number fixed by analyze so far
2663    int numberFixedNow_;
2664    /// Whether stopping on gap
2665    bool stoppedOnGap_;
2666    /// Whether event happened
2667    mutable bool eventHappened_;
2668    /// Number of long strong goes
2669    int numberLongStrong_;
2670    /// Number of old active cuts
2671    int numberOldActiveCuts_;
2672    /// Number of new cuts
2673    int numberNewCuts_;
2674    /// Strategy worked out - mainly at root node
2675    int searchStrategy_;
2676    /// Number of iterations in strong branching
2677    int numberStrongIterations_;
2678    /** 0 - number times strong branching done, 1 - number fixed, 2 - number infeasible
2679        Second group of three is a snapshot at node [6] */
2680    int strongInfo_[7];
2681    /**
2682        For advanced applications you may wish to modify the behavior of Cbc
2683        e.g. if the solver is a NLP solver then you may not have an exact
2684        optimum solution at each step.  This gives characteristics - just for one BAB.
2685        For actually saving/restoring a solution you need the actual solver one.
2686    */
2687    OsiBabSolver * solverCharacteristics_;
2688    /// Whether to force a resolve after takeOffCuts
2689    bool resolveAfterTakeOffCuts_;
2690    /// Maximum number of iterations (designed to be used in heuristics)
2691    int maximumNumberIterations_;
2692    /// Anything with priority >= this can be treated as continuous
2693    int continuousPriority_;
2694    /// Number of outstanding update information items
2695    int numberUpdateItems_;
2696    /// Maximum number of outstanding update information items
2697    int maximumNumberUpdateItems_;
2698    /// Update items
2699    CbcObjectUpdateData * updateItems_;
2700    /// Stored row cuts for donor/recipient CbcModel
2701    CglStored * storedRowCuts_;
2702    /**
2703       Parallel
2704       0 - off
2705       1 - testing
2706       2-99 threads
2707       other special meanings
2708    */
2709    int numberThreads_;
2710    /** thread mode
2711        always use numberThreads for branching
2712        1 set then deterministic
2713        2 set then use numberThreads for root cuts
2714        4 set then use numberThreads in root mini branch and bound
2715        default is 0
2716    */
2717    int threadMode_;
2718    /// Thread stuff for master
2719    CbcBaseModel * master_;
2720    /// Pointer to masterthread
2721    CbcThread * masterThread_;
2722//@}
2723};
2724/// So we can use osiObject or CbcObject during transition
2725void getIntegerInformation(const OsiObject * object, double & originalLower,
2726                           double & originalUpper) ;
2727// So we can call from other programs
2728// Real main program
2729class OsiClpSolverInterface;
2730int CbcMain (int argc, const char *argv[], OsiClpSolverInterface & solver, CbcModel ** babSolver);
2731int CbcMain (int argc, const char *argv[], CbcModel & babSolver);
2732// four ways of calling
2733int callCbc(const char * input2, OsiClpSolverInterface& solver1);
2734int callCbc(const char * input2);
2735int callCbc(const std::string input2, OsiClpSolverInterface& solver1);
2736int callCbc(const std::string input2) ;
2737// When we want to load up CbcModel with options first
2738void CbcMain0 (CbcModel & babSolver);
2739int CbcMain1 (int argc, const char *argv[], CbcModel & babSolver);
2740// two ways of calling
2741int callCbc(const char * input2, CbcModel & babSolver);
2742int callCbc(const std::string input2, CbcModel & babSolver);
2743// And when CbcMain0 already called to initialize
2744int callCbc1(const char * input2, CbcModel & babSolver);
2745int callCbc1(const std::string input2, CbcModel & babSolver);
2746// And when CbcMain0 already called to initialize (with call back) (see CbcMain1 for whereFrom)
2747int callCbc1(const char * input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2748int callCbc1(const std::string input2, CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2749int CbcMain1 (int argc, const char *argv[], CbcModel & babSolver, int (CbcModel * currentSolver, int whereFrom));
2750// For uniform setting of cut and heuristic options
2751void setCutAndHeuristicOptions(CbcModel & model);
2752#endif
2753
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