/usr/include/coin/ClpPrimalColumnSteepest.hpp

/* $Id: ClpPrimalColumnSteepest.hpp 1525 2010-02-26 17:27:59Z mjs $ */
// Copyright (C) 2002, International Business Machines
// Corporation and others.  All Rights Reserved.
#ifndef ClpPrimalColumnSteepest_H
#define ClpPrimalColumnSteepest_H

#include "ClpPrimalColumnPivot.hpp"
#include <bitset>

//#############################################################################
class CoinIndexedVector;


/** Primal Column Pivot Steepest Edge Algorithm Class

See Forrest-Goldfarb paper for algorithm

*/


class ClpPrimalColumnSteepest : public ClpPrimalColumnPivot {

public:

     ///@name Algorithmic methods
     //@{

     /** Returns pivot column, -1 if none.
         The Packed CoinIndexedVector updates has cost updates - for normal LP
         that is just +-weight where a feasibility changed.  It also has
         reduced cost from last iteration in pivot row
         Parts of operation split out into separate functions for
         profiling and speed
     */
     virtual int pivotColumn(CoinIndexedVector * updates,
                             CoinIndexedVector * spareRow1,
                             CoinIndexedVector * spareRow2,
                             CoinIndexedVector * spareColumn1,
                             CoinIndexedVector * spareColumn2);
     /// For quadratic or funny nonlinearities
     int pivotColumnOldMethod(CoinIndexedVector * updates,
                              CoinIndexedVector * spareRow1,
                              CoinIndexedVector * spareRow2,
                              CoinIndexedVector * spareColumn1,
                              CoinIndexedVector * spareColumn2);
     /// Just update djs
     void justDjs(CoinIndexedVector * updates,
                  CoinIndexedVector * spareRow2,
                  CoinIndexedVector * spareColumn1,
                  CoinIndexedVector * spareColumn2);
     /// Update djs doing partial pricing (dantzig)
     int partialPricing(CoinIndexedVector * updates,
                        CoinIndexedVector * spareRow2,
                        int numberWanted,
                        int numberLook);
     /// Update djs, weights for Devex using djs
     void djsAndDevex(CoinIndexedVector * updates,
                      CoinIndexedVector * spareRow2,
                      CoinIndexedVector * spareColumn1,
                      CoinIndexedVector * spareColumn2);
     /// Update djs, weights for Steepest using djs
     void djsAndSteepest(CoinIndexedVector * updates,
                         CoinIndexedVector * spareRow2,
                         CoinIndexedVector * spareColumn1,
                         CoinIndexedVector * spareColumn2);
     /// Update djs, weights for Devex using pivot row
     void djsAndDevex2(CoinIndexedVector * updates,
                       CoinIndexedVector * spareRow2,
                       CoinIndexedVector * spareColumn1,
                       CoinIndexedVector * spareColumn2);
     /// Update djs, weights for Steepest using pivot row
     void djsAndSteepest2(CoinIndexedVector * updates,
                          CoinIndexedVector * spareRow2,
                          CoinIndexedVector * spareColumn1,
                          CoinIndexedVector * spareColumn2);
     /// Update weights for Devex
     void justDevex(CoinIndexedVector * updates,
                    CoinIndexedVector * spareRow2,
                    CoinIndexedVector * spareColumn1,
                    CoinIndexedVector * spareColumn2);
     /// Update weights for Steepest
     void justSteepest(CoinIndexedVector * updates,
                       CoinIndexedVector * spareRow2,
                       CoinIndexedVector * spareColumn1,
                       CoinIndexedVector * spareColumn2);
     /// Updates two arrays for steepest
     void transposeTimes2(const CoinIndexedVector * pi1, CoinIndexedVector * dj1,
                          const CoinIndexedVector * pi2, CoinIndexedVector * dj2,
                          CoinIndexedVector * spare, double scaleFactor);

     /// Updates weights - part 1 - also checks accuracy
     virtual void updateWeights(CoinIndexedVector * input);

     /// Checks accuracy - just for debug
     void checkAccuracy(int sequence, double relativeTolerance,
                        CoinIndexedVector * rowArray1,
                        CoinIndexedVector * rowArray2);

     /// Initialize weights
     void initializeWeights();

     /** Save weights - this may initialize weights as well
         mode is -
         1) before factorization
         2) after factorization
         3) just redo infeasibilities
         4) restore weights
         5) at end of values pass (so need initialization)
     */
     virtual void saveWeights(ClpSimplex * model, int mode);
     /// Gets rid of last update
     virtual void unrollWeights();
     /// Gets rid of all arrays
     virtual void clearArrays();
     /// Returns true if would not find any column
     virtual bool looksOptimal() const;
     /// Called when maximum pivots changes
     virtual void maximumPivotsChanged();
     //@}

     /**@name gets and sets */
     //@{
     /// Mode
     inline int mode() const {
          return mode_;
     }
     /** Returns number of extra columns for sprint algorithm - 0 means off.
         Also number of iterations before recompute
     */
     virtual int numberSprintColumns(int & numberIterations) const;
     /// Switch off sprint idea
     virtual void switchOffSprint();

//@}

     /** enums for persistence
     */
     enum Persistence {
          normal = 0x00, // create (if necessary) and destroy
          keep = 0x01 // create (if necessary) and leave
     };

     ///@name Constructors and destructors
     //@{
     /** Default Constructor
         0 is exact devex, 1 full steepest, 2 is partial exact devex
         3 switches between 0 and 2 depending on factorization
         4 starts as partial dantzig/devex but then may switch between 0 and 2.
         By partial exact devex is meant that the weights are updated as normal
         but only part of the nonbasic variables are scanned.
         This can be faster on very easy problems.
     */
     ClpPrimalColumnSteepest(int mode = 3);

     /// Copy constructor
     ClpPrimalColumnSteepest(const ClpPrimalColumnSteepest & rhs);

     /// Assignment operator
     ClpPrimalColumnSteepest & operator=(const ClpPrimalColumnSteepest& rhs);

     /// Destructor
     virtual ~ClpPrimalColumnSteepest ();

     /// Clone
     virtual ClpPrimalColumnPivot * clone(bool copyData = true) const;

     //@}

     ///@name Private functions to deal with devex
     /** reference would be faster using ClpSimplex's status_,
         but I prefer to keep modularity.
     */
     inline bool reference(int i) const {
          return ((reference_[i>>5] >> (i & 31)) & 1) != 0;
     }
     inline void setReference(int i, bool trueFalse) {
          unsigned int & value = reference_[i>>5];
          int bit = i & 31;
          if (trueFalse)
               value |= (1 << bit);
          else
               value &= ~(1 << bit);
     }
     /// Set/ get persistence
     inline void setPersistence(Persistence life) {
          persistence_ = life;
     }
     inline Persistence persistence() const {
          return persistence_ ;
     }

     //@}
     //---------------------------------------------------------------------------

private:
     ///@name Private member data
     // Update weight
     double devex_;
     /// weight array
     double * weights_;
     /// square of infeasibility array (just for infeasible columns)
     CoinIndexedVector * infeasible_;
     /// alternate weight array (so we can unroll)
     CoinIndexedVector * alternateWeights_;
     /// save weight array (so we can use checkpoint)
     double * savedWeights_;
     // Array for exact devex to say what is in reference framework
     unsigned int * reference_;
     /** Status
         0) Normal
         -1) Needs initialization
         1) Weights are stored by sequence number
     */
     int state_;
     /**
         0 is exact devex, 1 full steepest, 2 is partial exact devex
         3 switches between 0 and 2 depending on factorization
         4 starts as partial dantzig/devex but then may switch between 0 and 2.
         5 is always partial dantzig
         By partial exact devex is meant that the weights are updated as normal
         but only part of the nonbasic variables are scanned.
         This can be faster on very easy problems.

         New dubious option is >=10 which does mini-sprint

     */
     int mode_;
     /// Life of weights
     Persistence persistence_;
     /// Number of times switched from partial dantzig to 0/2
     int numberSwitched_;
     // This is pivot row (or pivot sequence round re-factorization)
     int pivotSequence_;
     // This is saved pivot sequence
     int savedPivotSequence_;
     // This is saved outgoing variable
     int savedSequenceOut_;
     // Iteration when last rectified
     int lastRectified_;
     // Size of factorization at invert (used to decide algorithm)
     int sizeFactorization_;
     //@}
};

#endif
coinor-libclp-dev 1.12.0-2.1 / usr / include / coin / ClpPrimalColumnSteepest.hpp
