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+// Copyright (C) 2007, International Business Machines Corporation and others.
+// All Rights Reserved.
+// This code is published under the Eclipse Public License.
+//
+// Authors :
+// Joao P. Goncalves, International Business Machines Corporation
+//
+// Date : November 12, 2007
+
+#ifndef BonHeuristicDive_HPP
+#define BonHeuristicDive_HPP
+#include "BonOsiTMINLPInterface.hpp"
+#include "BonBonminSetup.hpp"
+#include "CbcHeuristic.hpp"
+
+namespace Bonmin
+{
+ class HeuristicDive : public CbcHeuristic
+ {
+ public:
+ /// Default constructor
+ HeuristicDive();
+
+ /// Constructor with setup
+ HeuristicDive(BonminSetup * setup);
+
+ /// Copy constructor
+ HeuristicDive(const HeuristicDive &copy);
+
+ /// Destructor
+ ~HeuristicDive() {}
+
+ /// Assignment operator
+ HeuristicDive & operator=(const HeuristicDive & rhs);
+
+ /// Clone
+ virtual CbcHeuristic * clone() const = 0;
+
+ /// Resets stuff if model changes
+ virtual void resetModel(CbcModel * model){
+ setModel(model);
+ }
+
+ /** Change setup used for heuristic.*/
+ virtual void setSetup(BonminSetup * setup){
+ setup_ = setup;
+ // Initialize(setup_->options());
+ }
+
+ /// Set percentage of integer variables to fix at bounds
+ void setPercentageToFix(double value)
+ { percentageToFix_ = value; }
+
+ /// Performs heuristic
+ virtual int solution(double &solutionValue, double *betterSolution);
+
+ /// sets internal variables
+ virtual void setInternalVariables(TMINLP2TNLP* minlp) = 0;
+
+ /// Selects the next variable to branch on
+ /** If bestColumn = -1, it means that no variable was found
+ */
+ virtual void selectVariableToBranch(TMINLP2TNLP* minlp,
+ const vector<int> & integerColumns,
+ const double* newSolution,
+ int& bestColumn,
+ int& bestRound) = 0;
+
+ protected:
+ /** Setup to use for local searches (will make copies).*/
+ BonminSetup * setup_;
+
+ /// Percentage of integer variables to fix at bounds
+ double percentageToFix_;
+
+ private:
+ /// How often to do (code can change)
+ int howOften_;
+
+ };
+
+ /// checks if the NLP relaxation of the problem is feasible
+ bool isNlpFeasible(TMINLP2TNLP* minlp, const double primalTolerance);
+
+ /// Adjusts the primalTolerance in case some of the constraints are violated
+ void adjustPrimalTolerance(TMINLP2TNLP* minlp, double & primalTolerance);
+}
+#endif