23/02/07 modifications

git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@185 331e1502-861f-0410-8da2-ba01fb791d7f

branches/paradiseo-moeo-1.0/src/metric/moeoAdditiveEpsilonBinaryMetric.h

@@ -16,24 +16,69 @@
 #include <metric/moeoMetric.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 MOEOT >
-class moeoAdditiveEpsilonBinaryMetric : public moeoSolutionVsSolutionBinaryMetric < MOEOT, double >
+template < class ObjectiveVector >
+class moeoAdditiveEpsilonBinaryMetric : public moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double >
 {
 public:
-	
-	/** the objective vector type of a solution */
-	typedef typename MOEOT::ObjectiveVector ObjectiveVector;
-	
-	moeoAdditiveEpsilonBinaryMetric();
-	
-	
-	double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
+			
+	/**
+	 * Returns the maximum epsilon value 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 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 _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_*/

branches/paradiseo-moeo-1.0/src/metric/moeoMetric.h

@@ -62,6 +62,55 @@ class moeoSolutionVsSolutionBinaryMetric : public moeoBinaryMetric < const Objec
 {};
 
 
+/**
+ * Base class for binary metrics dedicated to the performance comparison between two solutions's objective vectors using normalized values.
+ * Then, indicator values lie in the interval [-1,1].
+ * Note that you have to set the bounds for every objective before using the operator().
+ */
+template < class ObjectiveVector, class R >
+class moeoNormalizedSolutionVsSolutionBinaryMetric : public moeoSolutionVsSolutionBinaryMetric < ObjectiveVector, R >
+{
+public:
+
+	/**
+	 * Default ctr for any moeoNormalizedSolutionVsSolutionBinaryMetric object
+	 */
+	moeoNormalizedSolutionVsSolutionBinaryMetric()
+	{
+		bounds.resize(ObjectiveVector::Traits::nObjectives());
+	}
+	
+	
+	/**
+	 * Sets the lower bound (_min) and the upper bound (_max) for the objective _obj
+	 * _min lower bound
+	 * _max upper bound
+	 * _obj the objective index
+	 */
+	virtual void setup(double _min, double _max, unsigned _obj)
+	{
+		bounds[_obj] = eoRealInterval(_min, _max);
+	}
+	
+	/**
+	 * Sets the lower bound and the upper bound for the objective _obj using a eoRealInterval object
+	 * _realInterval the eoRealInterval object
+	 * _obj the objective index
+	 */
+	virtual void setup(eoRealInterval _realInterval, unsigned _obj)
+	{
+		bounds[_obj] = _realInterval;
+	}
+	
+	
+protected:
+
+	/** the bounds for every objective (bounds[i] = bounds for the objective i) */
+	std::vector < eoRealInterval > bounds;
+	
+};
+
+
 /**
  * Base class for binary metrics dedicated to the performance comparison between a Pareto set (a vector of objective vectors) and a single solution's objective vector.
  */