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diff --git a/thirdparty/linux/include/coin/CbcHeuristicGreedy.hpp b/thirdparty/linux/include/coin/CbcHeuristicGreedy.hpp
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+/* $Id: CbcHeuristicGreedy.hpp 1585 2011-01-11 19:04:34Z forrest $ */
+// Copyright (C) 2005, International Business Machines
+// Corporation and others.  All Rights Reserved.
+// This code is licensed under the terms of the Eclipse Public License (EPL).
+
+#ifndef CbcHeuristicGreedy_H
+#define CbcHeuristicGreedy_H
+
+#include "CbcHeuristic.hpp"
+/** Greedy heuristic classes
+ */
+
+class CbcHeuristicGreedyCover : public CbcHeuristic {
+public:
+
+    // Default Constructor
+    CbcHeuristicGreedyCover ();
+
+    /* Constructor with model - assumed before cuts
+       Initial version does not do Lps
+    */
+    CbcHeuristicGreedyCover (CbcModel & model);
+
+    // Copy constructor
+    CbcHeuristicGreedyCover ( const CbcHeuristicGreedyCover &);
+
+    // Destructor
+    ~CbcHeuristicGreedyCover ();
+
+    /// Clone
+    virtual CbcHeuristic * clone() const;
+    /// Assignment operator
+    CbcHeuristicGreedyCover & operator=(const CbcHeuristicGreedyCover& rhs);
+    /// Create C++ lines to get to current state
+    virtual void generateCpp( FILE * fp) ;
+
+    /// update model (This is needed if cliques update matrix etc)
+    virtual void setModel(CbcModel * model);
+
+    using CbcHeuristic::solution ;
+    /** returns 0 if no solution, 1 if valid solution.
+        Sets solution values if good, sets objective value (only if good)
+        We leave all variables which are at one at this node of the
+        tree to that value and will
+        initially set all others to zero.  We then sort all variables in order of their cost
+        divided by the number of entries in rows which are not yet covered.  We randomize that
+        value a bit so that ties will be broken in different ways on different runs of the heuristic.
+        We then choose the best one and set it to one and repeat the exercise.
+
+    */
+    virtual int solution(double & objectiveValue,
+                         double * newSolution);
+    /// Validate model i.e. sets when_ to 0 if necessary (may be NULL)
+    virtual void validate() ;
+    /// Resets stuff if model changes
+    virtual void resetModel(CbcModel * model);
+    /* Algorithm
+       0 - use current upper bounds
+       1 - use original upper bounds
+       If 10 added perturb ratios more
+       if 100 added round up all >=0.5
+    */
+    inline int algorithm() const {
+        return algorithm_;
+    }
+    inline void setAlgorithm(int value) {
+        algorithm_ = value;
+    }
+    // Only do this many times
+    inline int numberTimes() const {
+        return numberTimes_;
+    }
+    inline void setNumberTimes(int value) {
+        numberTimes_ = value;
+    }
+
+protected:
+    /// Guts of constructor from a CbcModel
+    void gutsOfConstructor(CbcModel * model);
+    // Data
+
+    // Original matrix by column
+    CoinPackedMatrix matrix_;
+    // original number of rows
+    int originalNumberRows_;
+    /* Algorithm
+       0 - use current upper bounds
+       1 - use original upper bounds
+       If 10 added perturb ratios more
+    */
+    int algorithm_;
+    /// Do this many times
+    int numberTimes_;
+
+};
+
+
+class CbcHeuristicGreedyEquality : public CbcHeuristic {
+public:
+
+    // Default Constructor
+    CbcHeuristicGreedyEquality ();
+
+    /* Constructor with model - assumed before cuts
+       Initial version does not do Lps
+    */
+    CbcHeuristicGreedyEquality (CbcModel & model);
+
+    // Copy constructor
+    CbcHeuristicGreedyEquality ( const CbcHeuristicGreedyEquality &);
+
+    // Destructor
+    ~CbcHeuristicGreedyEquality ();
+
+    /// Clone
+    virtual CbcHeuristic * clone() const;
+    /// Assignment operator
+    CbcHeuristicGreedyEquality & operator=(const CbcHeuristicGreedyEquality& rhs);
+    /// Create C++ lines to get to current state
+    virtual void generateCpp( FILE * fp) ;
+
+    /// update model (This is needed if cliques update matrix etc)
+    virtual void setModel(CbcModel * model);
+
+    using CbcHeuristic::solution ;
+    /** returns 0 if no solution, 1 if valid solution.
+        Sets solution values if good, sets objective value (only if good)
+        We leave all variables which are at one at this node of the
+        tree to that value and will
+        initially set all others to zero.  We then sort all variables in order of their cost
+        divided by the number of entries in rows which are not yet covered.  We randomize that
+        value a bit so that ties will be broken in different ways on different runs of the heuristic.
+        We then choose the best one and set it to one and repeat the exercise.
+
+    */
+    virtual int solution(double & objectiveValue,
+                         double * newSolution);
+    /// Validate model i.e. sets when_ to 0 if necessary (may be NULL)
+    virtual void validate() ;
+    /// Resets stuff if model changes
+    virtual void resetModel(CbcModel * model);
+    /* Algorithm
+       0 - use current upper bounds
+       1 - use original upper bounds
+       If 10 added perturb ratios more
+       if 100 added round up all >=0.5
+    */
+    inline int algorithm() const {
+        return algorithm_;
+    }
+    inline void setAlgorithm(int value) {
+        algorithm_ = value;
+    }
+    // Fraction of rhs to cover before branch and cut
+    inline void setFraction(double value) {
+        fraction_ = value;
+    }
+    inline double fraction() const {
+        return fraction_;
+    }
+    // Only do this many times
+    inline int numberTimes() const {
+        return numberTimes_;
+    }
+    inline void setNumberTimes(int value) {
+        numberTimes_ = value;
+    }
+protected:
+    /// Guts of constructor from a CbcModel
+    void gutsOfConstructor(CbcModel * model);
+    // Data
+
+    // Original matrix by column
+    CoinPackedMatrix matrix_;
+    // Fraction of rhs to cover before branch and cut
+    double fraction_;
+    // original number of rows
+    int originalNumberRows_;
+    /* Algorithm
+       0 - use current upper bounds
+       1 - use original upper bounds
+       If 10 added perturb ratios more
+    */
+    int algorithm_;
+    /// Do this many times
+    int numberTimes_;
+
+};
+
+/** Greedy heuristic for SOS and L rows (and positive elements)
+ */
+
+class CbcHeuristicGreedySOS : public CbcHeuristic {
+public:
+
+    // Default Constructor
+    CbcHeuristicGreedySOS ();
+
+    /* Constructor with model - assumed before cuts
+       Initial version does not do Lps
+    */
+    CbcHeuristicGreedySOS (CbcModel & model);
+
+    // Copy constructor
+    CbcHeuristicGreedySOS ( const CbcHeuristicGreedySOS &);
+
+    // Destructor
+    ~CbcHeuristicGreedySOS ();
+
+    /// Clone
+    virtual CbcHeuristic * clone() const;
+    /// Assignment operator
+    CbcHeuristicGreedySOS & operator=(const CbcHeuristicGreedySOS& rhs);
+    /// Create C++ lines to get to current state
+    virtual void generateCpp( FILE * fp) ;
+
+    /// update model (This is needed if cliques update matrix etc)
+    virtual void setModel(CbcModel * model);
+
+    using CbcHeuristic::solution ;
+    /** returns 0 if no solution, 1 if valid solution.
+        Sets solution values if good, sets objective value (only if good)
+        We leave all variables which are at one at this node of the
+        tree to that value and will
+        initially set all others to zero.  We then sort all variables in order of their cost
+        divided by the number of entries in rows which are not yet covered.  We randomize that
+        value a bit so that ties will be broken in different ways on different runs of the heuristic.
+        We then choose the best one and set it to one and repeat the exercise.
+
+    */
+    virtual int solution(double & objectiveValue,
+                         double * newSolution);
+    /// Validate model i.e. sets when_ to 0 if necessary (may be NULL)
+    virtual void validate() ;
+    /// Resets stuff if model changes
+    virtual void resetModel(CbcModel * model);
+    /* Algorithm
+       Bits
+       1 bit - use current model, otherwise original
+       2 - use current solution as starting point, otherwise pure greedy
+       4 - as 2 but use merit not merit/size
+       8 - use duals to modify greedy
+       16 - use duals on GUB/SOS in special way
+    */
+    inline int algorithm() const {
+        return algorithm_;
+    }
+    inline void setAlgorithm(int value) {
+        algorithm_ = value;
+    }
+    // Only do this many times
+    inline int numberTimes() const {
+        return numberTimes_;
+    }
+    inline void setNumberTimes(int value) {
+        numberTimes_ = value;
+    }
+
+protected:
+    /// Guts of constructor from a CbcModel
+    void gutsOfConstructor(CbcModel * model);
+    // Data
+
+    // Original RHS - if -1.0 then SOS otherwise <= value
+    double * originalRhs_;
+    // Original matrix by column
+    CoinPackedMatrix matrix_;
+    // original number of rows
+    int originalNumberRows_;
+    /* Algorithm
+    */
+    int algorithm_;
+    /// Do this many times
+    int numberTimes_;
+
+};
+
+
+#endif
+