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+// Name:     CglRedSplit2Param.hpp
+// Author:   Giacomo Nannicini
+//           Singapore University of Technology and Design
+//           Singapore
+//           email: nannicini@sutd.edu.sg
+// Date:     03/09/09
+//-----------------------------------------------------------------------------
+// Copyright (C) 2010, Giacomo Nannicini and others.  All Rights Reserved.
+
+#ifndef CglRedSplit2Param_H
+#define CglRedSplit2Param_H
+
+#include "CglParam.hpp"
+#include <vector>
+
+  /**@name CglRedSplit2 Parameters */
+  //@{
+
+  /** Class collecting parameters the Reduced-and-split cut generator.
+
+      An important thing to note is that the cut generator allows for
+      the selection of a number of strategies that can be combined
+      together. By default, a selection that typically yields a good
+      compromise between speed and cut strenght is made. The selection
+      can be changed by resetting the default choices (see the
+      functions whose name starts with "reset") or by setting the
+      parameter use_default_strategies to false in the
+      constructors. After this, the chosen strategies can be added to
+      the list by using the functions whose name starts with
+      "add". All strategies will be combined together: if we choose 3
+      row selection strategies, 2 column selection strategies, and 2
+      possible numbers of rows, we end up with a total of 3*2*2
+      combinations.
+
+      For a detailed explanation of the parameters and their meaning,
+      see the paper by Cornuejols and Nannicini: "Practical strategies
+      for generating rank-1 split cuts in mixed-integer linear
+      programming", on Mathematical Programming Computation.
+
+      Parameters of the generator are listed below. 
+
+      - MAXDYN: Maximum ratio between largest and smallest non zero 
+                coefficients in a cut. See method setMAXDYN().
+      - EPS_ELIM: Precision for deciding if a coefficient is zero when 
+                  eliminating slack variables. See method setEPS_ELIM().
+      - MINVIOL: Minimum violation for the current basic solution in 
+                 a generated cut. See method setMINVIOL().
+      - EPS_RELAX_ABS: Absolute relaxation of cut rhs.
+      - EPS_RELAX_REL: Relative relaxation of cut rhs.
+      - MAX_SUPP_ABS: Maximum cut support (absolute).
+      - MAX_SUPP_REL: Maximum cut support (relative): the formula to 
+                      compute maximum cut support is 
+		      MAX_SUPP_ABS + ncol*MAX_SUPP_REL.
+      - USE_INTSLACKS: Use integer slacks to generate cuts. (not implemented).
+                       See method setUSE_INTSLACKS().
+      - normIsZero: Norm of a vector is considered zero if smaller than
+                    this value. See method setNormIsZero(). 
+      - minNormReduction: a cut is generated if the new norm of the row on the
+                          continuous nonbasics is reduced by at least
+			  this factor (relative reduction).
+      - away: Look only at basic integer variables whose current value
+              is at least this value from being integer. See method setAway().
+      - maxSumMultipliers: maximum sum (in absolute value) of row multipliers
+      - normalization: normalization factor for the norm of lambda in the
+                       coefficient reduction algorithm (convex min problem)
+      - numRowsReduction: Maximum number of rows in the linear system for
+                          norm reduction.
+      - columnSelectionStrategy: parameter to select which columns should be
+                                 used for coefficient reduction.
+      - rowSelectionStrategy: parameter to select which rows should be
+                              used for coefficient reduction.
+      - timeLimit: Time limit (in seconds) for cut generation.
+      - maxNumCuts: Maximum number of cuts that can be returned at each pass;
+                    we could generate more cuts than this number (see below)
+      - maxNumComputedCuts: Maximum number of cuts that can be computed
+                            by the generator at each pass
+      - maxNonzeroesTab : Rows of the simplex tableau with more than
+                          this number of nonzeroes will not be
+                          considered for reduction. Only works if
+                          RS_FAST_* are defined in CglRedSplit2.
+      - skipGomory: Skip traditional Gomory cuts, i.e. GMI cuts arising from
+                    a single row of the tableau (instead of a combination).
+                    Default is 1 (true), because we assume that they are 
+		    generated by a traditional Gomory generator anyway. 
+  */
+  //@}
+
+class CglRedSplit2Param : public CglParam {
+
+public:
+  /** Enumerations for parameters */
+
+  /** Row selection strategies; same names as in the paper */
+  enum RowSelectionStrategy{
+    /* Pick rows that introduce the fewest nonzeroes on integer nonbasics */
+    RS1, 
+    /* Pick rows that introduce the fewest nonzeroes on the set of working
+       continuous nonbasics */
+    RS2,
+    /* Pick rows that introduce the fewest nonzeroes on both integer and
+       working continuous nonbasics */
+    RS3,
+    /* Same as RS0 but with greedy algorithm */
+    RS4,
+    /* Same as RS1 but with greedy algorithm */
+    RS5,
+    /* Same as RS2 but with greedy algorithm */
+    RS6,
+    /* Pick rows with smallest angle in the space of integer and working
+       continuous nonbasics */
+    RS7,
+    /* Pick rows with smallest angle in the space of working
+       continuous nonbasics */
+    RS8,
+    /* Use all strategies */
+    RS_ALL,
+    /* Use best ones - that is, RS8 and RS7 */
+    RS_BEST
+  };
+
+  /** Column selection strategies; again, look them up in the paper. */
+  enum ColumnSelectionStrategy{
+    /* C-3P */
+    CS1, CS2, CS3,
+    /* C-5P */
+    CS4, CS5, CS6, CS7, CS8,
+    /* I-2P-2/3 */
+    CS9, CS10,
+    /* I-2P-4/5 */
+    CS11, CS12,
+    /* I-2P-1/2 */
+    CS13, CS14,
+    /* I-3P */
+    CS15, CS16, CS17,
+    /* I-4P */
+    CS18, CS19, CS20, CS21,
+    /* Use all strategies up to this point */
+    CS_ALL,
+    /* Use best strategies (same effect as CS_ALL, because it turns out that
+       using all strategies is the best thing to do) */
+    CS_BEST,
+    /* Optimize over all continuous nonbasic columns; this does not give
+       good results, but we use it for testing Lift & Project + RedSplit */
+    CS_ALLCONT,
+    /* Lift & Project specific strategy: only select variables which
+       are nonbasic in the tableau but are basic in the point to cut
+       off.  This strategy cannot be used outside L&P. It is not very
+       effective even with L&P, but is left here for testing.*/
+    CS_LAP_NONBASICS
+  };
+
+  /** Scaling strategies for new nonbasic columns for Lift & Project;
+   *  "factor" is the value of columnScalingBoundLAP_ */
+  enum ColumnScalingStrategy{
+    /* No scaling */
+    SC_NONE,
+    /* Multiply by |xbar[i]| where xbar[i] is the value of the 
+       corresponding component of the point that we want to cut off */
+    SC_LINEAR,
+    /* Multiply by min(factor,|xbar[i]|) */
+    SC_LINEAR_BOUNDED,
+    /* Multiply by min(factor,log(|xbar[i]|)) */
+    SC_LOG_BOUNDED,
+    /* Multiply all new nonbasics by factor */
+    SC_UNIFORM,
+    /* Multiply only nonzero coefficients by factor */
+    SC_UNIFORM_NZ
+  };
+
+  /**@name Set/get methods */
+  //@{
+  /** Set away, the minimum distance from being integer used for selecting 
+      rows for cut generation;  all rows whose pivot variable should be 
+      integer but is more than away from integrality will be selected; 
+      Default: 0.005 */
+  virtual void setAway(double value);
+  /// Get value of away
+  inline double getAway() const {return away_;}
+
+  /** Set the value of EPS_ELIM, epsilon for values of coefficients when 
+      eliminating slack variables;
+      Default: 0.0 */
+  void setEPS_ELIM(double value);
+  /** Get the value of EPS_ELIM */
+  double getEPS_ELIM() const {return EPS_ELIM;}
+  
+  /** Set EPS_RELAX_ABS */
+  virtual void setEPS_RELAX_ABS(double eps_ra);
+  /** Get value of EPS_RELAX_ABS */
+  inline double getEPS_RELAX_ABS() const {return EPS_RELAX_ABS;}
+
+  /** Set EPS_RELAX_REL */
+  virtual void setEPS_RELAX_REL(double eps_rr);
+  /** Get value of EPS_RELAX_REL */
+  inline double getEPS_RELAX_REL() const {return EPS_RELAX_REL;}
+
+  // Set the maximum ratio between largest and smallest non zero 
+  // coefficients in a cut. Default: 1e6.
+  virtual void setMAXDYN(double value);
+  /** Get the value of MAXDYN */
+  inline double getMAXDYN() const {return MAXDYN;}
+
+  /** Set the value of MINVIOL, the minimum violation for the current 
+      basic solution in a generated cut. Default: 1e-3 */
+  virtual void setMINVIOL(double value);
+  /** Get the value of MINVIOL */
+  inline double getMINVIOL() const {return MINVIOL;}
+
+  /** Maximum absolute support of the cutting planes. Default: INT_MAX.
+      Aliases for consistency with our naming scheme. */
+  inline void setMAX_SUPP_ABS(int value) {setMAX_SUPPORT(value);}
+  inline int getMAX_SUPP_ABS() const {return MAX_SUPPORT;}
+
+  /** Maximum relative support of the cutting planes. Default: 0.0.
+      The maximum support is MAX_SUPP_ABS + MAX_SUPPREL*ncols. */
+  inline void setMAX_SUPP_REL(double value); 
+  inline double getMAX_SUPP_REL() const {return MAX_SUPP_REL;}
+
+  /** Set the value of USE_INTSLACKS. Default: 0 */
+  virtual void setUSE_INTSLACKS(int value);
+  /** Get the value of USE_INTSLACKS */
+  inline int getUSE_INTSLACKS() const {return USE_INTSLACKS;}
+
+  /** Set the value of normIsZero, the threshold for considering a norm to be 
+      0; Default: 1e-5 */
+  virtual void setNormIsZero(double value);
+  /** Get the value of normIsZero */
+  inline double getNormIsZero() const {return normIsZero_;}
+
+  /** Set the value of minNormReduction; Default: 0.1 */
+  virtual void setMinNormReduction(double value);
+  /** Get the value of normIsZero */
+  inline double getMinNormReduction() const {return minNormReduction_;}
+
+  /** Set the value of maxSumMultipliers; Default: 10 */
+  virtual void setMaxSumMultipliers(int value);
+  /** Get the value of maxSumMultipliers */
+  inline int getMaxSumMultipliers() const {return maxSumMultipliers_;}
+
+  /** Set the value of normalization; Default: 0.0001 */
+  virtual void setNormalization(double value);
+  /** Get the value of normalization */
+  inline double getNormalization() const {return normalization_;}
+
+  /** Set the value of numRowsReduction, max number of rows that are used
+   *  for each row reduction step. In particular, the linear system will
+   *  involve a numRowsReduction*numRowsReduction matrix */
+  virtual void addNumRowsReduction(int value);
+  /// get the value
+  inline std::vector<int> getNumRowsReduction() const {return numRowsReduction_;}
+  /// reset
+  inline void resetNumRowsReduction() {numRowsReduction_.clear();}
+
+  /** Add the value of columnSelectionStrategy */
+  virtual void addColumnSelectionStrategy(ColumnSelectionStrategy value);
+  /// get the value
+  inline std::vector<ColumnSelectionStrategy> getColumnSelectionStrategy() const {return columnSelectionStrategy_;}
+  /// reset
+  inline void resetColumnSelectionStrategy(){columnSelectionStrategy_.clear();}
+
+  /** Set the value for rowSelectionStrategy, which changes the way we choose
+   *  the rows for the reduction step */
+  virtual void addRowSelectionStrategy(RowSelectionStrategy value);
+  /// get the value
+  inline std::vector<RowSelectionStrategy> getRowSelectionStrategy() const {return rowSelectionStrategy_;};
+  /// reset
+  inline void resetRowSelectionStrategy() {rowSelectionStrategy_.clear();}
+
+  /** Set the value of numRowsReductionLAP, max number of rows that are used
+   *  for each row reduction step during Lift & Project. 
+   *  In particular, the linear system will involve a 
+   *  numRowsReduction*numRowsReduction matrix */
+  virtual void addNumRowsReductionLAP(int value);
+  /// get the value
+  inline std::vector<int> getNumRowsReductionLAP() const {return numRowsReductionLAP_;}
+  /// reset
+  inline void resetNumRowsReductionLAP() {numRowsReductionLAP_.clear();}
+
+  /** Add the value of columnSelectionStrategyLAP */
+  virtual void addColumnSelectionStrategyLAP(ColumnSelectionStrategy value);
+  /// get the value
+  inline std::vector<ColumnSelectionStrategy> getColumnSelectionStrategyLAP() const {return columnSelectionStrategyLAP_;}
+  /// reset
+  inline void resetColumnSelectionStrategyLAP(){columnSelectionStrategyLAP_.clear();}
+
+  /** Set the value for rowSelectionStrategyLAP, which changes the way we 
+   *  choose the rows for the reduction step */
+  virtual void addRowSelectionStrategyLAP(RowSelectionStrategy value);
+  /// get the value
+  inline std::vector<RowSelectionStrategy> getRowSelectionStrategyLAP() const {return rowSelectionStrategyLAP_;};
+  /// reset
+  inline void resetRowSelectionStrategyLAP() {rowSelectionStrategyLAP_.clear();}
+
+  /** Set the value for columnScalingStrategyLAP, which sets the way nonbasic
+   *  columns that are basic in the fractional point to cut off are scaled */
+  virtual void setColumnScalingStrategyLAP(ColumnScalingStrategy value);
+  /// get the value
+  inline ColumnScalingStrategy getColumnScalingStrategyLAP() const {return columnScalingStrategyLAP_; };
+
+  /** Set the value for the bound in the column scaling factor */
+  virtual void setColumnScalingBoundLAP(double value);
+  /// get the value
+  inline double getColumnScalingBoundLAP() const {return columnScalingBoundLAP_;};
+
+  /** Set the value of the time limit for cut generation (in seconds) */
+  virtual void setTimeLimit(double value);
+  /// get the value
+  inline double getTimeLimit() const {return timeLimit_;}
+
+  /** Set the value for the maximum number of cuts that can be returned */
+  virtual void setMaxNumCuts(int value);
+  /// get the value
+  inline int getMaxNumCuts() const {return maxNumCuts_;}
+
+  /** Set the value for the maximum number of cuts that can be computed */
+  virtual void setMaxNumComputedCuts(int value);
+  /// get the value
+  inline int getMaxNumComputedCuts() const {return maxNumComputedCuts_;}
+
+  /** Set the value for the maximum number of nonzeroes in a row of
+   * the simplex tableau for the row to be considered */
+  virtual void setMaxNonzeroesTab(int value);
+  /// get the value
+  inline int getMaxNonzeroesTab() const {return maxNonzeroesTab_;}
+
+  /** Set the value of skipGomory: should we skip simple Gomory cuts,
+   *  i.e. GMI cuts derived from a single row of the simple tableau?
+   *  This is 1 (true) by default: we only generate cuts from linear
+   *  combinations of at least two rows. */
+  virtual void setSkipGomory(int value);
+  /// get the value
+  inline int getSkipGomory() const {return skipGomory_;}
+
+  //@}
+
+  /**@name Constructors and destructors */
+  //@{
+  /// Default constructor. If use_default_strategies is true, we add
+  /// to the list of strategies the default ones. If is false, the
+  /// list of strategies is left empty (must be populated before usage!).
+  CglRedSplit2Param(bool use_default_strategies = true,
+		    double eps = 1e-12,
+		    double eps_coeff = 1e-11,
+		    double eps_elim = 0.0,
+		    double eps_relax_abs = 1e-11,
+		    double eps_relax_rel = 1e-13,
+		    double max_dyn = 1e6,
+		    double min_viol = 1e-3,
+		    int max_supp_abs = 1000,
+		    double max_supp_rel = 0.1,
+		    int use_int_slacks = 0,
+		    double norm_zero = 1e-5,
+		    double minNormReduction = 0.1,
+		    int maxSumMultipliers = 10,
+		    double normalization = 0.0001,
+		    double away = 0.005,
+		    double timeLimit = 60,
+		    int maxNumCuts = 10000,
+		    int maxNumComputedCuts = 10000,
+		    int maxNonzeroesTab = 1000,
+		    double columnScalingBoundLAP = 5.0,
+		    int skipGomory = 1);
+
+  /// Constructor from CglParam. If use_default_strategies is true, we
+  /// add to the list of strategies the default ones. If is false, the
+  /// list of strategies is left empty (must be populated before
+  /// usage!).
+  CglRedSplit2Param(const CglParam &source,
+		    bool use_default_strategies = true,
+		    double eps_elim = 0.0,
+		    double eps_relax_abs = 1e-11,
+		    double eps_relax_rel = 1e-13,
+		    double max_dyn = 1e6,
+		    double min_viol = 1e-3,
+		    double max_supp_rel = 0.1,
+		    int use_int_slacks = 0,
+		    double norm_zero = 1e-5,
+		    double minNormReduction = 0.1,
+		    int maxSumMultipliers = 10,
+		    double normalization = 0.0001,
+		    double away = 0.005,
+		    double timeLimit = 60,
+		    int maxNumCuts = 10000,
+		    int maxNumComputedCuts = 10000,
+		    int maxNonzeroesTab = 1000,
+		    double columnScalingBoundLAP = 5.0,
+		    int skipGomory = 1);
+
+  /// Copy constructor 
+  CglRedSplit2Param(const CglRedSplit2Param &source);
+
+  /// Clone
+  virtual CglRedSplit2Param* clone() const;
+
+  /// Assignment operator 
+  virtual CglRedSplit2Param& operator=(const CglRedSplit2Param &rhs);
+
+  /// Destructor 
+  virtual ~CglRedSplit2Param();
+  //@}
+
+protected:
+
+  /**@name Parameters */
+  //@{
+
+  /** Epsilon for value of coefficients when eliminating slack variables. 
+      Default: 0.0. */
+  double EPS_ELIM;
+
+  /** Value added to the right hand side of each generated cut to relax it.
+      Default: 1e-11 */
+  double EPS_RELAX_ABS;
+
+  /** For a generated cut with right hand side rhs_val, 
+      EPS_RELAX_EPS * fabs(rhs_val) is used to relax the constraint.
+      Default: 1e-13 */
+  double EPS_RELAX_REL;
+
+  // Maximum ratio between largest and smallest non zero 
+  // coefficients in a cut. Default: 1e6.
+  double MAXDYN;
+
+  /// Minimum violation for the current basic solution in a generated cut.
+  /// Default: 1e-3.
+  double MINVIOL;
+
+  /// Maximum support - relative part of the formula
+  double MAX_SUPP_REL;
+
+  /// Use integer slacks to generate cuts if USE_INTSLACKS = 1. Default: 0.
+  int USE_INTSLACKS;
+
+  /// Norm of a vector is considered zero if smaller than normIsZero;
+  /// Default: 1e-5.
+  double normIsZero_;
+
+  /// Minimum reduction to accept a new row.
+  double minNormReduction_;
+
+  /// Maximum sum of the vector of row multipliers to generate a cut
+  int maxSumMultipliers_;
+
+  /// Normalization factor for the norm of lambda in the quadratic
+  /// minimization problem that is solved during the coefficient reduction step
+  double normalization_;
+
+  /// Use row only if pivot variable should be integer but is more 
+  /// than away_ from being integer. Default: 0.005
+  double away_;
+  
+  /// Maximum number of rows to use for the reduction of a given row.
+  std::vector<int> numRowsReduction_;
+
+  /// Column selection method
+  std::vector<ColumnSelectionStrategy> columnSelectionStrategy_;
+
+  /// Row selection method
+  std::vector<RowSelectionStrategy> rowSelectionStrategy_;
+
+  /// Maximum number of rows to use for the reduction during Lift & Project
+  std::vector<int> numRowsReductionLAP_;
+
+  /// Column selection method for Lift & Project
+  std::vector<ColumnSelectionStrategy> columnSelectionStrategyLAP_;
+
+  /// Row selection method for Lift & Project
+  std::vector<RowSelectionStrategy> rowSelectionStrategyLAP_;
+
+  /// Column scaling strategy for the nonbasics columns that were basic in
+  /// the point that we want to cut off (Lift & Project only)
+  ColumnScalingStrategy columnScalingStrategyLAP_;
+
+  /// Minimum value for column scaling (Lift & Project only)
+  double columnScalingBoundLAP_;
+
+  /// Time limit
+  double timeLimit_;
+
+  /// Maximum number of returned cuts
+  int maxNumCuts_;
+
+  /// Maximum number of computed cuts
+  int maxNumComputedCuts_;
+
+  /// Maximum number of nonzeroes in tableau row for reduction
+  int maxNonzeroesTab_;
+
+  /// Skip simple Gomory cuts
+  int skipGomory_;
+
+  //@}
+};
+
+#endif