// Copyright (C) 2004, International Business Machines // Corporation and others. All Rights Reserved. #ifndef CglDuplicateRow_H #define CglDuplicateRow_H #include #include "CglCutGenerator.hpp" class CglStored; /** DuplicateRow Cut Generator Class */ class CglDuplicateRow : public CglCutGenerator { public: /**@name Generate Cuts */ //@{ /** Fix variables and find duplicate/dominated rows for the model of the solver interface, si. This is a very simple minded idea but I (JJF) am using it in a project so thought I might as well add it. It should really be called before first solve and I may modify CBC to allow for that. This is designed for problems with few rows and many integer variables where the rhs are <= or == and all coefficients and rhs are small integers. If effective rhs is K then we can fix all variables with coefficients > K to their lower bounds (effective rhs just means original with variables with nonzero lower bounds subtracted out). If one row is a subset of another and the effective rhs are same we can fix some variables and then the two rows are identical. The generator marks identical rows so can be taken out in solve */ virtual void generateCuts( const OsiSolverInterface & si, OsiCuts & cs, const CglTreeInfo info = CglTreeInfo()) const; /** Fix variables and find duplicate/dominated rows for the model of the solver interface, si. This is a very simple minded idea but I (JJF) am using it in a project so thought I might as well add it. It should really be called before first solve and I may modify CBC to allow for that. This is designed for problems with few rows and many integer variables where the rhs are <= or == and all coefficients and rhs are small integers. If effective rhs is K then we can fix all variables with coefficients > K to their lower bounds (effective rhs just means original with variables with nonzero lower bounds subtracted out). If one row is a subset of another and the effective rhs are same we can fix some variables and then the two rows are identical. This version does deletions and fixings and may return stored cuts for dominated columns */ CglStored * outDuplicates( OsiSolverInterface * solver); //@} /**@name Get information on size of problem */ //@{ /// Get duplicate row list, -1 means still in, -2 means out (all fixed), k>= means same as row k inline const int * duplicate() const { return duplicate_;} /// Size of dynamic program inline int sizeDynamic() const { return sizeDynamic_;} /// Number of rows in original problem inline int numberOriginalRows() const { return matrix_.getNumRows();} //@} /**@name Get information on size of problem */ //@{ /// logLevel inline int logLevel() const { return logLevel_;} inline void setLogLevel(int value) { logLevel_ = value;} //@} /**@name We only check for duplicates amongst rows with effective rhs <= this */ //@{ /// Get inline int maximumRhs() const { return maximumRhs_;} /// Set inline void setMaximumRhs(int value) { maximumRhs_=value;} //@} /**@name We only check for dominated amongst groups of columns whose size <= this */ //@{ /// Get inline int maximumDominated() const { return maximumDominated_;} /// Set inline void setMaximumDominated(int value) { maximumDominated_=value;} //@} /**@name gets and sets */ //@{ /// Get mode inline int mode() const { return mode_;} /// Set mode inline void setMode(int value) { mode_=value;} //@} /**@name Constructors and destructors */ //@{ /// Default constructor CglDuplicateRow (); /// Useful constructor CglDuplicateRow (OsiSolverInterface * solver); /// Copy constructor CglDuplicateRow ( const CglDuplicateRow & rhs); /// Clone virtual CglCutGenerator * clone() const; /// Assignment operator CglDuplicateRow & operator=( const CglDuplicateRow& rhs); /// Destructor virtual ~CglDuplicateRow (); /// Create C++ lines to get to current state virtual std::string generateCpp( FILE * fp); /// This can be used to refresh any inforamtion virtual void refreshSolver(OsiSolverInterface * solver); //@} protected: // Protected member data /**@name Protected member data */ //@{ /// Matrix CoinPackedMatrix matrix_; /// Matrix by row CoinPackedMatrix matrixByRow_; /// Possible rhs (if 0 then not possible) int * rhs_; /// Marks duplicate rows mutable int * duplicate_; /// To allow for <= rows int * lower_; /// Stored cuts if we found dominance cuts mutable CglStored * storedCuts_; /// Check dominated columns if less than this number of candidates int maximumDominated_; /// Check duplicates if effective rhs <= this int maximumRhs_; /// Size of dynamic program mutable int sizeDynamic_; /// 1 do rows, 2 do columns, 3 do both int mode_; /// Controls print out int logLevel_; //@} }; #endif