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// Copyright (C) 2004, International Business Machines
// Corporation and others.  All Rights Reserved.
#ifndef CbcTreeLocal_H
#define CbcTreeLocal_H

//#############################################################################
/*  This implements (approximately) local branching as in the 2002 paper by
    Matteo Fischetti and Andrea Lodi.

    The very simple version of the algorithm for problems with 
    0-1 variables and continuous is as follows:

    Obtain a feasible solution (one can be passed in).

    Add a cut which limits search to a k neighborhood of this solution.
    (At most k 0-1 variables may change value)
    Do branch and bound on this problem.

    If finished search and proven optimal then we can reverse cut so
    any solutions must be at least k+1 away from solution and we can 
    add a new cut limiting search to a k neighborhood of new solution
    repeat.

    If finished search and no new solution then the simplest version
    would reverse last cut and complete search.  The version implemented 
    here can use time and node limits and can widen search (increase effective k)
    .... and more

*/

#include "CbcTree.hpp"
#include "CbcNode.hpp"
#include "OsiRowCut.hpp"
class CbcModel;


class CbcTreeLocal : public CbcTree {

public:

  // Default Constructor 
  CbcTreeLocal ();

  /* Constructor with solution.
     If solution NULL no solution, otherwise must be integer
     range is initial upper bound (k) on difference from given solution.
     typeCuts -
              0 means just 0-1 cuts and will need to refine 0-1 solution
              1 uses weaker cuts on all integer variables
     maxDiversification is maximum number of range widenings to try
     timeLimit is seconds in subTree
     nodeLimit is nodes in subTree
     refine is whether to see if we can prove current solution is optimal
     when we fix all 0-1 (in case typeCuts==0 and there are general integer variables)
     if false then no refinement but reverse cuts weaker
  */
  CbcTreeLocal (CbcModel * model,const double * solution ,int range=10,
                   int typeCuts=0,int maxDiversification=0,
                   int timeLimit=1000000, int nodeLimit=1000000,bool refine=true);
  // Copy constructor 
  CbcTreeLocal ( const CbcTreeLocal & rhs);

  // = operator
  CbcTreeLocal & operator=(const CbcTreeLocal & rhs);
   
  virtual ~CbcTreeLocal();

  virtual CbcTree * clone() const;
  virtual void generateCpp( FILE * fp) ;


  virtual CbcNode * top() const;

  virtual void push(CbcNode * x);

  virtual void pop() ;



  int createCut(const double * solution, OsiRowCut & cut);

  virtual bool empty() ;

  virtual void endSearch() ;
  void reverseCut(int state, double bias=0.0);
  void deleteCut(OsiRowCut & cut);
  void passInSolution(const double * solution, double solutionValue);
  // range i.e. k
  inline int range() const
  { return range_;}
  // setrange i.e. k
  inline void setRange(int value)
  { range_ = value;}
  // Type of cuts - 0=just 0-1, 1=all
  inline int typeCuts() const
  { return typeCuts_;}
  // Type of cuts - 0=just 0-1, 1=all
  inline void setTypeCuts(int value)
  { typeCuts_ = value;}
  // maximum number of diversifications
  inline int maxDiversification() const
  { return maxDiversification_;}
  // maximum number of diversifications
  inline void setMaxDiversification(int value)
  { maxDiversification_ = value;}
  // time limit per subtree
  inline int timeLimit() const
  { return timeLimit_;}
  // time limit per subtree
  inline void setTimeLimit(int value)
  { timeLimit_ = value;}
  // node limit for subtree
  inline int nodeLimit() const
  { return nodeLimit_;}
  // node limit for subtree
  inline void setNodeLimit(int value)
  { nodeLimit_ = value;}
  // Whether to do refinement step
  inline bool refine() const
  { return refine_;}
  // Whether to do refinement step
  inline void setRefine(bool yesNo)
    { refine_ = yesNo;}

private:
  // Node for local cuts
  CbcNode * localNode_;
  // best solution
  double * bestSolution_;
  // saved solution
  double * savedSolution_;
  // solution number at start of pass
  int saveNumberSolutions_;
  /* Cut.  If zero size then no solution yet.  Otherwise is left hand branch */
  OsiRowCut cut_;
  // This cut fixes all 0-1 variables
  OsiRowCut fixedCut_;
  // Model
  CbcModel * model_;
  // Original lower bounds
  double * originalLower_;
  // Original upper bounds
  double * originalUpper_;
  // range i.e. k
  int range_;
  // Type of cuts - 0=just 0-1, 1=all
  int typeCuts_;
  // maximum number of diversifications
  int maxDiversification_;
  // current diversification
  int diversification_;
  // Whether next will be strong diversification
  bool nextStrong_;
  // Current rhs
  double rhs_;
  // Save allowable gap
  double savedGap_;
  // Best solution
  double bestCutoff_;
  // time limit per subtree
  int timeLimit_;
  // time when subtree started
  int startTime_;
  // node limit for subtree
  int nodeLimit_;
  // node count when subtree started
  int startNode_;
  // -1 not started, 0 == stop on first solution, 1 don't stop on first, 2 refinement step
  int searchType_;
  // Whether to do refinement step
  bool refine_;

};
#endif

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