diff --git a/branches/paradiseo-moeo-1.0/src/distance/moeoDistance.h b/branches/paradiseo-moeo-1.0/src/distance/moeoDistance.h
index 0b55890c0..61b8fb670 100644
--- a/branches/paradiseo-moeo-1.0/src/distance/moeoDistance.h
+++ b/branches/paradiseo-moeo-1.0/src/distance/moeoDistance.h
@@ -13,9 +13,7 @@
 #ifndef MOEODISTANCE_H_
 #define MOEODISTANCE_H_
 
-#include <math.h>
 #include <eoFunctor.h>
-#include <utils/eoRealBounds.h>
 
 /**
  * The base class for distance computation.
@@ -25,203 +23,32 @@ class moeoDistance : public eoBF < const MOEOT &, const MOEOT &, const Type >
 {
 public:
 
-
     /**
-        * Nothing to do
-        * @param _pop the population
-        */
+     * Nothing to do
+     * @param _pop the population
+     */
     virtual void setup(const eoPop < MOEOT > & _pop)
     {}
 
+
     /**
      * Nothing to do
      * @param _min lower bound
      * @param _max upper bound
      * @param _obj the objective index
      */
-    virtual void setup(double _min, double _max, unsigned _obj)
+    virtual void setup(double _min, double _max, unsigned int _obj)
     {}
 
 
     /**
-        * Nothing to do
-        * @param _realInterval the eoRealInterval object
-        * @param _obj the objective index
-        */
-    virtual void setup(eoRealInterval _realInterval, unsigned _obj)
+     * Nothing to do
+     * @param _realInterval the eoRealInterval object
+     * @param _obj the objective index
+     */
+    virtual void setup(eoRealInterval _realInterval, unsigned int _obj)
     {}
 
 };
 
-
-/**
- * The base class for double distance computation with normalized objective values (i.e. between 0 and 1).
- */
-template < class MOEOT , class Type = double >
-class moeoNormalizedDistance : public moeoDistance < MOEOT , Type >
-{
-public:
-
-    /** the objective vector type of the solutions */
-    typedef typename MOEOT::ObjectiveVector ObjectiveVector;
-
-
-    /**
-     * Default ctr
-     */
-    moeoNormalizedDistance()
-    {
-        bounds.resize(ObjectiveVector::Traits::nObjectives());
-        // initialize bounds in case someone does not want to use them
-        for (unsigned i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
-        {
-            bounds[i] = eoRealInterval(0,1);
-        }
-    }
-
-    /**
-     * Returns a very small value that can be used to avoid extreme cases (where the min bound == the max bound)
-     */
-    static double tiny()
-    {
-        return 1e-6;
-    }
-
-
-    /**
-     * Sets the lower and the upper bounds for every objective using extremes values for solutions contained in the population _pop
-     * @param _pop the population
-     */
-    virtual void setup(const eoPop < MOEOT > & _pop)
-    {
-        double min, max;
-        for (unsigned i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
-        {
-            min = _pop[0].objectiveVector()[i];
-            max = _pop[0].objectiveVector()[i];
-            for (unsigned j=1; j<_pop.size(); j++)
-            {
-                min = std::min(min, _pop[j].objectiveVector()[i]);
-                max = std::max(max, _pop[j].objectiveVector()[i]);
-            }
-            // setting of the bounds for the objective i
-            setup(min, max, i);
-        }
-    }
-
-
-    /**
-        * Sets the lower bound (_min) and the upper bound (_max) for the objective _obj
-        * @param _min lower bound
-        * @param _max upper bound
-        * @param _obj the objective index
-        */
-    virtual void setup(double _min, double _max, unsigned _obj)
-    {
-        if (_min == _max)
-        {
-            _min -= tiny();
-            _max += tiny();
-        }
-        bounds[_obj] = eoRealInterval(_min, _max);
-    }
-
-
-    /**
-        * Sets the lower bound and the upper bound for the objective _obj using a eoRealInterval object
-        * @param _realInterval the eoRealInterval object
-        * @param _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;
-
-};
-
-
-/**
- * A class allowing to compute an euclidian distance between two solutions in the objective space with normalized objective values (i.e. between 0 and 1).
- * A distance value then lies between 0 and sqrt(nObjectives).
- */
-template < class MOEOT >
-class moeoEuclideanDistance : public moeoNormalizedDistance < MOEOT >
-{
-public:
-
-    /** the objective vector type of the solutions */
-    typedef typename MOEOT::ObjectiveVector ObjectiveVector;
-
-
-    /**
-     * Returns the euclidian distance between _moeo1 and _moeo2 in the objective space
-     * @param _moeo1 the first solution
-     * @param _moeo2 the second solution
-     */
-    const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
-    {
-        double result = 0.0;
-        double tmp1, tmp2;
-        for (unsigned i=0; i<ObjectiveVector::nObjectives(); i++)
-        {
-            tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
-            tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
-            result += (tmp1-tmp2) * (tmp1-tmp2);
-        }
-        return sqrt(result);
-    }
-
-
-private:
-
-    /** the bounds for every objective */
-    using moeoNormalizedDistance < MOEOT > :: bounds;
-
-};
-
-/**
- * A class allowing to compute the Manhattan distance between two solutions in the objective space normalized objective values (i.e. between 0 and 1).
- * A distance value then lies between 0 and nObjectives.
- */
-template < class MOEOT >
-class moeoManhattanDistance : public moeoNormalizedDistance < MOEOT >
-{
-public:
-
-    /** the objective vector type of the solutions */
-    typedef typename MOEOT::ObjectiveVector ObjectiveVector;
-
-
-    /**
-     * Returns the Manhattan distance between _moeo1 and _moeo2 in the objective space
-     * @param _moeo1 the first solution
-     * @param _moeo2 the second solution
-     */
-    const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
-    {
-        double result = 0.0;
-        double tmp1, tmp2;
-        for (unsigned i=0; i<ObjectiveVector::nObjectives(); i++)
-        {
-            tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
-            tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
-            result += fabs(tmp1-tmp2);
-        }
-        return result;
-    }
-
-
-private:
-
-    /** the bounds for every objective */
-    using moeoNormalizedDistance < MOEOT > :: bounds;
-
-};
-
 #endif /*MOEODISTANCE_H_*/
diff --git a/branches/paradiseo-moeo-1.0/src/distance/moeoDistanceMatrix.h b/branches/paradiseo-moeo-1.0/src/distance/moeoDistanceMatrix.h
index ed6c088ce..b9a9e924e 100644
--- a/branches/paradiseo-moeo-1.0/src/distance/moeoDistanceMatrix.h
+++ b/branches/paradiseo-moeo-1.0/src/distance/moeoDistanceMatrix.h
@@ -13,6 +13,7 @@
 #ifndef MOEODISTANCEMATRIX_H_
 #define MOEODISTANCEMATRIX_H_
 
+#include <vector>
 #include <eoFunctor.h>
 #include <distance/moeoDistance.h>
 
@@ -33,10 +34,10 @@ public:
      * @param _size size for every dimension of the matrix
      * @param _distance the distance to use
      */
-    moeoDistanceMatrix (unsigned _size, moeoDistance < MOEOT , Type > & _distance) : distance(_distance)
+    moeoDistanceMatrix (unsigned int _size, moeoDistance < MOEOT , Type > & _distance) : distance(_distance)
     {
         this->resize(_size);
-        for (unsigned i=0; i<_size; i++)
+        for (unsigned int i=0; i<_size; i++)
         {
             this->operator[](i).resize(_size);
         }
@@ -53,10 +54,10 @@ public:
         distance.setup(_pop);
         // 2 - compute distances
         this->operator[](0).operator[](0) = Type();
-        for (unsigned i=0; i<size(); i++)
+        for (unsigned int i=0; i<size(); i++)
         {
             this->operator[](i).operator[](i) = Type();
-            for (unsigned j=0; j<i; j++)
+            for (unsigned int j=0; j<i; j++)
             {
                 this->operator[](i).operator[](j) = distance(_pop[i], _pop[j]);
                 this->operator[](j).operator[](i) = this->operator[](i).operator[](j);
diff --git a/branches/paradiseo-moeo-1.0/src/distance/moeoEuclideanDistance.h b/branches/paradiseo-moeo-1.0/src/distance/moeoEuclideanDistance.h
new file mode 100644
index 000000000..2d8d8ec49
--- /dev/null
+++ b/branches/paradiseo-moeo-1.0/src/distance/moeoEuclideanDistance.h
@@ -0,0 +1,58 @@
+// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
+
+//-----------------------------------------------------------------------------
+// moeoEuclideanDistance.h
+// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
+/*
+    This library...
+
+    Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
+ */
+//-----------------------------------------------------------------------------
+
+#ifndef MOEOEUCLIDEANDISTANCE_H_
+#define MOEOEUCLIDEANDISTANCE_H_
+
+#include <math.h>
+#include <distance/moeoNormalizedDistance.h>
+
+/**
+ * A class allowing to compute an euclidian distance between two solutions in the objective space with normalized objective values (i.e. between 0 and 1).
+ * A distance value then lies between 0 and sqrt(nObjectives).
+ */
+template < class MOEOT >
+class moeoEuclideanDistance : public moeoNormalizedDistance < MOEOT >
+{
+public:
+
+    /** the objective vector type of the solutions */
+    typedef typename MOEOT::ObjectiveVector ObjectiveVector;
+
+
+    /**
+     * Returns the euclidian distance between _moeo1 and _moeo2 in the objective space
+     * @param _moeo1 the first solution
+     * @param _moeo2 the second solution
+     */
+    const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
+    {
+        double result = 0.0;
+        double tmp1, tmp2;
+        for (unsigned int i=0; i<ObjectiveVector::nObjectives(); i++)
+        {
+            tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
+            tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
+            result += (tmp1-tmp2) * (tmp1-tmp2);
+        }
+        return sqrt(result);
+    }
+
+
+private:
+
+    /** the bounds for every objective */
+    using moeoNormalizedDistance < MOEOT > :: bounds;
+
+};
+
+#endif /*MOEOEUCLIDEANDISTANCE_H_*/
diff --git a/branches/paradiseo-moeo-1.0/src/distance/moeoManhattanDistance.h b/branches/paradiseo-moeo-1.0/src/distance/moeoManhattanDistance.h
new file mode 100644
index 000000000..f4c145fe7
--- /dev/null
+++ b/branches/paradiseo-moeo-1.0/src/distance/moeoManhattanDistance.h
@@ -0,0 +1,58 @@
+// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
+
+//-----------------------------------------------------------------------------
+// moeoManhattanDistance.h
+// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
+/*
+    This library...
+
+    Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
+ */
+//-----------------------------------------------------------------------------
+
+#ifndef MOEOMANHATTANDISTANCE_H_
+#define MOEOMANHATTANDISTANCE_H_
+
+#include <math.h>
+#include <distance/moeoNormalizedDistance.h>
+
+/**
+ * A class allowing to compute the Manhattan distance between two solutions in the objective space normalized objective values (i.e. between 0 and 1).
+ * A distance value then lies between 0 and nObjectives.
+ */
+template < class MOEOT >
+class moeoManhattanDistance : public moeoNormalizedDistance < MOEOT >
+{
+public:
+
+    /** the objective vector type of the solutions */
+    typedef typename MOEOT::ObjectiveVector ObjectiveVector;
+
+
+    /**
+     * Returns the Manhattan distance between _moeo1 and _moeo2 in the objective space
+     * @param _moeo1 the first solution
+     * @param _moeo2 the second solution
+     */
+    const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
+    {
+        double result = 0.0;
+        double tmp1, tmp2;
+        for (unsigned int i=0; i<ObjectiveVector::nObjectives(); i++)
+        {
+            tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
+            tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
+            result += fabs(tmp1-tmp2);
+        }
+        return result;
+    }
+
+
+private:
+
+    /** the bounds for every objective */
+    using moeoNormalizedDistance < MOEOT > :: bounds;
+
+};
+
+#endif /*MOEOMANHATTANDISTANCE_H_*/
diff --git a/branches/paradiseo-moeo-1.0/src/distance/moeoNormalizedDistance.h b/branches/paradiseo-moeo-1.0/src/distance/moeoNormalizedDistance.h
new file mode 100644
index 000000000..ee1a2caa8
--- /dev/null
+++ b/branches/paradiseo-moeo-1.0/src/distance/moeoNormalizedDistance.h
@@ -0,0 +1,112 @@
+// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
+
+//-----------------------------------------------------------------------------
+// moeoNormalizedDistance.h
+// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
+/*
+    This library...
+
+    Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
+ */
+//-----------------------------------------------------------------------------
+
+#ifndef MOEONORMALIZEDDISTANCE_H_
+#define MOEONORMALIZEDDISTANCE_H_
+
+#include <vector>
+#include <utils/eoRealBounds.h>
+#include <distance/moeoDistance.h>
+
+/**
+ * The base class for double distance computation with normalized objective values (i.e. between 0 and 1).
+ */
+template < class MOEOT , class Type = double >
+class moeoNormalizedDistance : public moeoDistance < MOEOT , Type >
+{
+public:
+
+    /** the objective vector type of the solutions */
+    typedef typename MOEOT::ObjectiveVector ObjectiveVector;
+
+
+    /**
+     * Default ctr
+     */
+    moeoNormalizedDistance()
+    {
+        bounds.resize(ObjectiveVector::Traits::nObjectives());
+        // initialize bounds in case someone does not want to use them
+        for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
+        {
+            bounds[i] = eoRealInterval(0,1);
+        }
+    }
+
+
+    /**
+     * Returns a very small value that can be used to avoid extreme cases (where the min bound == the max bound)
+     */
+    static double tiny()
+    {
+        return 1e-6;
+    }
+
+
+    /**
+     * Sets the lower and the upper bounds for every objective using extremes values for solutions contained in the population _pop
+     * @param _pop the population
+     */
+    virtual void setup(const eoPop < MOEOT > & _pop)
+    {
+        double min, max;
+        for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
+        {
+            min = _pop[0].objectiveVector()[i];
+            max = _pop[0].objectiveVector()[i];
+            for (unsigned int j=1; j<_pop.size(); j++)
+            {
+                min = std::min(min, _pop[j].objectiveVector()[i]);
+                max = std::max(max, _pop[j].objectiveVector()[i]);
+            }
+            // setting of the bounds for the objective i
+            setup(min, max, i);
+        }
+    }
+
+
+    /**
+     * Sets the lower bound (_min) and the upper bound (_max) for the objective _obj
+     * @param _min lower bound
+     * @param _max upper bound
+     * @param _obj the objective index
+     */
+    virtual void setup(double _min, double _max, unsigned int _obj)
+    {
+        if (_min == _max)
+        {
+            _min -= tiny();
+            _max += tiny();
+        }
+        bounds[_obj] = eoRealInterval(_min, _max);
+    }
+
+
+    /**
+     * Sets the lower bound and the upper bound for the objective _obj using a eoRealInterval object
+     * @param _realInterval the eoRealInterval object
+     * @param _obj the objective index
+     */
+    virtual void setup(eoRealInterval _realInterval, unsigned int _obj)
+    {
+        bounds[_obj] = _realInterval;
+    }
+
+
+protected:
+
+    /** the bounds for every objective (bounds[i] = bounds for the objective i) */
+    std::vector < eoRealInterval > bounds;
+
+};
+
+#endif /*MOEONORMALIZEDDISTANCE_H_*/