merge ParadisEO-MOEO v-1.0

git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@400 331e1502-861f-0410-8da2-ba01fb791d7f

trunk/paradiseo-moeo/src/metric/moeoAdditiveEpsilonBinaryMetric.h

@@ -0,0 +1,84 @@
+// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
+
+//-----------------------------------------------------------------------------
+// moeoAdditiveEpsilonBinaryMetric.h
+// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
+/*
+    This library...
+
+    Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
+ */
+//-----------------------------------------------------------------------------
+
+#ifndef MOEOADDITIVEEPSILONBINARYMETRIC_H_
+#define MOEOADDITIVEEPSILONBINARYMETRIC_H_
+
+#include <metric/moeoNormalizedSolutionVsSolutionBinaryMetric.h>
+
+/**
+ * Additive epsilon binary metric allowing to compare two objective vectors as proposed in
+ * Zitzler E., Thiele L., Laumanns M., Fonseca C. M., Grunert da Fonseca V.:
+ * Performance Assessment of Multiobjective Optimizers: An Analysis and Review. IEEE Transactions on Evolutionary Computation 7(2), pp.117–132 (2003).
+ */
+template < class ObjectiveVector >
+class moeoAdditiveEpsilonBinaryMetric : public moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double >
+{
+public:
+
+    /**
+     * Returns the minimal distance by which the objective vector _o1 must be translated in all objectives 
+     * so that it weakly dominates the objective vector _o2	
+     * @warning don't forget to set the bounds for every objective before the call of this function
+     * @param _o1 the first objective vector
+     * @param _o2 the second objective vector
+     */
+    double operator()(const ObjectiveVector & _o1, const ObjectiveVector & _o2)
+    {
+        // computation of the epsilon value for the first objective
+        double result = epsilon(_o1, _o2, 0);
+        // computation of the epsilon value for the other objectives
+        double tmp;
+        for (unsigned int i=1; i<ObjectiveVector::Traits::nObjectives(); i++)
+        {
+            tmp = epsilon(_o1, _o2, i);
+            result = std::max(result, tmp);
+        }
+        // returns the maximum epsilon value
+        return result;
+    }
+
+
+private:
+
+    /** the bounds for every objective */
+    using moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > :: bounds;
+
+
+    /**
+     * Returns the epsilon value by which the objective vector _o1 must be translated in the objective _obj 
+     * so that it dominates the objective vector _o2
+     * @param _o1 the first objective vector
+     * @param _o2 the second objective vector
+     * @param _obj the index of the objective
+     */
+    double epsilon(const ObjectiveVector & _o1, const ObjectiveVector & _o2, const unsigned int _obj)
+    {
+        double result;
+        // if the objective _obj have to be minimized
+        if (ObjectiveVector::Traits::minimizing(_obj))
+        {
+            // _o1[_obj] - _o2[_obj]
+            result = ( (_o1[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() ) - ( (_o2[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() );
+        }
+        // if the objective _obj have to be maximized
+        else
+        {
+            // _o2[_obj] - _o1[_obj]
+            result = ( (_o2[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() ) - ( (_o1[_obj] - bounds[_obj].minimum()) / bounds[_obj].range() );
+        }
+        return result;
+    }
+
+};
+
+#endif /*MOEOADDITIVEEPSILONBINARYMETRIC_H_*/