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authorHarpreet2016-09-03 00:36:51 +0530
committerHarpreet2016-09-03 00:36:51 +0530
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+/* $Id: CoinPresolveDual.hpp 1510 2011-12-08 23:56:01Z lou $ */
+
+// Copyright (C) 2002, International Business Machines
+// Corporation and others. All Rights Reserved.
+// This code is licensed under the terms of the Eclipse Public License (EPL).
+
+#ifndef CoinPresolveDual_H
+#define CoinPresolveDual_H
+
+/*! \class remove_dual_action
+ \brief Attempt to fix variables by bounding reduced costs
+
+ The reduced cost of x_j is d_j = c_j - y*a_j (1). Assume minimization,
+ so that at optimality d_j >= 0 for x_j nonbasic at lower bound, and
+ d_j <= 0 for x_j nonbasic at upper bound.
+
+ For a slack variable s_i, c_(n+i) = 0 and a_(n+i) is a unit vector, hence
+ d_(n+i) = -y_i. If s_i has a finite lower bound and no upper bound, we
+ must have y_i <= 0 at optimality. Similarly, if s_i has no lower bound and a
+ finite upper bound, we must have y_i >= 0.
+
+ For a singleton variable x_j, d_j = c_j - y_i*a_ij. Given x_j with a
+ single finite bound, we can bound d_j greater or less than 0 at
+ optimality, and that allows us to calculate an upper or lower bound on y_i
+ (depending on the bound on d_j and the sign of a_ij).
+
+ Now we have bounds on some subset of the y_i, and we can use these to
+ calculate upper and lower bounds on the d_j, using bound propagation on
+ (1). If we can manage to bound some d_j as strictly positive or strictly
+ negative, then at optimality the corresponding variable must be nonbasic
+ at its lower or upper bound, respectively. If the required bound is lacking,
+ the problem is unbounded.
+*/
+
+class remove_dual_action : public CoinPresolveAction {
+
+ public:
+
+ /// Destructor
+ ~remove_dual_action () ;
+
+ /// Name
+ inline const char *name () const { return ("remove_dual_action") ; }
+
+ /*! \brief Attempt to fix variables by bounding reduced costs
+
+ Always scans all variables. Propagates bounds on reduced costs until there's
+ no change or until some set of variables can be fixed.
+ */
+ static const CoinPresolveAction *presolve(CoinPresolveMatrix *prob,
+ const CoinPresolveAction *next) ;
+
+ /*! \brief Postsolve
+
+ In addition to fixing variables (handled by make_fixed_action), we may
+ need use our own postsolve to restore constraint bounds.
+ */
+ void postsolve (CoinPostsolveMatrix *prob) const ;
+
+ private:
+
+ /// Postsolve (bound restore) instruction
+ struct action {
+ double rlo_ ; ///< restored row lower bound
+ double rup_ ; ///< restored row upper bound
+ int ndx_ ; ///< row index
+ } ;
+
+ /// Constructor with postsolve actions.
+ remove_dual_action(int nactions, const action *actions,
+ const CoinPresolveAction *next)
+ : CoinPresolveAction(next),
+ nactions_(nactions),
+ actions_(actions)
+ {}
+
+ /// Count of bound restore entries
+ const int nactions_ ;
+ /// Bound restore entries
+ const action *actions_ ;
+
+} ;
+#endif
+
+