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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@210 331e1502-861f-0410-8da2-ba01fb791d7f
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liefooga 2007-04-10 13:34:32 +00:00
commit 528a149107
27 changed files with 1891 additions and 344 deletions
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12
branches/paradiseo-moeo-1.0/src/metric/moeoNormalizedSolutionVsSolutionBinaryMetric.h
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@ -27,7 +27,7 @@ class moeoNormalizedSolutionVsSolutionBinaryMetric : public moeoSolutionVsSoluti
{
public:
/** very small value to avoid the extreme case where the min bound = the max bound */
/** very small value to avoid the extreme case where the min bound == the max bound */
const static double tiny = 1e-6;
@ -46,15 +46,13 @@ public:
* _max upper bound
* _obj the objective index
*/
virtual void setup(double _min, double _max, unsigned _obj)
void setup(double _min, double _max, unsigned _obj)
{
/*
if (min = max)
if (_min == _max)
{
min -= tiny;
max += tiny;
_min -= tiny;
_max += tiny;
}
*/
bounds[_obj] = eoRealInterval(_min, _max);
}

221
branches/paradiseo-moeo-1.0/src/metric/moeoVectorVsSolutionBinaryMetric.h
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@ -1,221 +0,0 @@
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoVectorVsSolutionBinaryMetric.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOVECTORVSSOLUTIONBINARYMETRIC_H_
#define MOEOVECTORVSSOLUTIONBINARYMETRIC_H_
#include <metric/moeoMetric.h>
#include <metric/moeoNormalizedSolutionVsSolutionBinaryMetric.h>
/**
* 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.
*/
template < class ObjectiveVector, class R >
class moeoVectorVsSolutionBinaryMetric : public moeoBinaryMetric < const std::vector < ObjectiveVector > &, const ObjectiveVector &, R >
{
public:
/**
* Default ctor
* @param _metric the binary metric for the performance comparison between two solutions's objective vectors using normalized values
*/
moeoVectorVsSolutionBinaryMetric(moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > * _metric) : metric(_metric)
{}
/**
* Returns the value of the metric comparing the set _v to an objective vector _o
* _v a vector of objective vectors
* _o an objective vector
*/
double operator()(const std::vector < ObjectiveVector > & _v, const ObjectiveVector & _o)
{
// 1 - set the bounds for every objective
setBounds(_v, _o);
// 2 - compute every indicator value
computeValues(_v, _o);
// 3 - resulting value
return result();
}
protected:
/** the binary metric for the performance comparison between two solutions's objective vectors using normalized values */
moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > * metric;
/** the indicator values : values[i] = I(_v[i], _o) */
vector < double > values;
/**
* Sets the bounds for every objective using the min and the max value
* _v a vector of objective vectors
* _o an objective vector
*/
void setBounds(const std::vector < ObjectiveVector > & _v, const ObjectiveVector & _o)
{
double min, max;
for (unsigned i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
{
min = _o[i];
max = _o[i];
for (unsigned j=0; j<_v.size(); j++)
{
min = std::min(min, _v[j][i]);
max = std::max(max, _v[j][i]);
}
// setting of the bounds for the objective i
(*metric).setup(min, max, i);
}
}
/**
* Compute every indicator value : values[i] = I(_v[i], _o)
* _v a vector of objective vectors
* _o an objective vector
*/
void computeValues(const std::vector < ObjectiveVector > & _v, const ObjectiveVector & _o)
{
values.clear();
values.resize(_v.size());
for (unsigned i=0; i<_v.size(); i++)
{
values[i] = (*metric)(_v[i], _o);
}
}
/**
* Returns the global result that combines the I-values
*/
virtual double result() = 0;
};
/**
* Minimum version of binary metric dedicated to the performance comparison between a vector of objective vectors and a single solution's objective vector.
*/
template < class ObjectiveVector >
class moeoMinimumVectorVsSolutionBinaryMetric : public moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double >
{
public:
/**
* Ctor
* @param _metric the binary metric for the performance comparison between two solutions's objective vectors using normalized values
*/
moeoMinimumVectorVsSolutionBinaryMetric(moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > * _metric) : moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double > (_metric)
{}
private:
/** the indicator values : values[i] = I(_v[i], _o) */
using moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double >::values;
/**
* Returns the minimum binary indicator values computed
*/
double result()
{
return *std::min_element(values.begin(), values.end());
}
};
/**
* Additive version of binary metric dedicated to the performance comparison between a vector of objective vectors and a single solution's objective vector.
*/
template < class ObjectiveVector >
class moeoAdditiveVectorVsSolutionBinaryMetric : public moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double >
{
public:
/**
* Ctor
* @param _metric the binary metric for the performance comparison between two solutions's objective vectors using normalized values
*/
moeoAdditiveVectorVsSolutionBinaryMetric(moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > * _metric) : moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double > (_metric)
{}
private:
/** the indicator values : values[i] = I(_v[i], _o) */
using moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double >::values;
/**
* Returns the sum of the binary indicator values computed
*/
double result()
{
double result = 0;
for (unsigned i=0; i<values.size(); i++)
{
result += values[i];
}
return result;
}
};
/**
* Exponential version of binary metric dedicated to the performance comparison between a vector of objective vectors
* and a single solution's objective vector.
*
* ********** Do we have to care about the max absolute indicator value ? ********************
*
*/
template < class ObjectiveVector >
class moeoExponentialVectorVsSolutionBinaryMetric : public moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double >
{
public:
/**
* Ctor
* @param _metric the binary metric for the performance comparison between two solutions's objective vectors using normalized values
*/
moeoExponentialVectorVsSolutionBinaryMetric(moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > * _metric, const double _kappa) :
moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double > (_metric), kappa(_kappa)
{}
private:
/** scaling factor kappa */
double kappa;
/** the indicator values : values[i] = I(_v[i], _o) */
using moeoVectorVsSolutionBinaryMetric < ObjectiveVector, double >::values;
/**
* Returns a kind of sum of the binary indicator values computed that amplifies the influence of dominating objective vectors over dominated ones
*/
double result()
{
double result = 0;
for (unsigned i=0; i<values.size(); i++)
{
result += exp(-values[i] / kappa);
}
return result;
}
};
#endif /*MOEOVECTORVSSOLUTIONBINARYMETRIC_H_*/