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Modifications 22/02/2007

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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@183 331e1502-861f-0410-8da2-ba01fb791d7f
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legrand 2007-02-22 15:38:01 +00:00
commit 8312d91a84
19 changed files with 930 additions and 805 deletions
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339
branches/paradiseo-moeo-1.0/src/MOEO.h
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@ -31,250 +31,253 @@
* operator '<' et '>' ???
* !!!!!!!!!!!!!!!!!!!!!!!
*/
template < class MOEOObjectiveVector, class MOEOFitness, class MOEODiversity >
class MOEO : public EO < MOEOFitness >
template < class MOEOObjectiveVector, class MOEOFitness, class MOEODiversity > class MOEO:public EO <
MOEOFitness
>
{
public:
/** the objective vector type of a solution */
typedef MOEOObjectiveVector ObjectiveVector;
typedef MOEOObjectiveVector ObjectiveVector;
/** the fitness type of a solution */
typedef MOEOFitness Fitness;
typedef MOEOFitness Fitness;
/** the diversity type of a solution */
typedef MOEODiversity Diversity;
typedef MOEODiversity Diversity;
/**
* Ctor
*/
MOEO()
{
// default values for every parameters
objectiveVectorValue = ObjectiveVector();
fitnessValue = Fitness();
diversityValue = Diversity();
// invalidate all
invalidate();
}
MOEO ()
{
// default values for every parameters
objectiveVectorValue = ObjectiveVector ();
fitnessValue = Fitness ();
diversityValue = Diversity ();
// invalidate all
invalidate ();
}
/**
* Virtual dtor
*/
virtual ~MOEO() {};
virtual ~ MOEO ()
{
};
/**
* Returns the objective vector of the current solution
*/
ObjectiveVector objectiveVector() const
{
if ( invalidObjectiveVector() )
{
throw std::runtime_error("invalid objective vector");
}
return objectiveVectorValue;
}
ObjectiveVector objectiveVector () const
{
if (invalidObjectiveVector ())
{
throw std::runtime_error ("invalid objective vector");
}
return objectiveVectorValue;
}
/**
* Sets the objective vector of the current solution
* @param _objectiveVectorValue the new objective vector
*/
void objectiveVector(const ObjectiveVector & _objectiveVectorValue)
{
objectiveVectorValue = _objectiveVectorValue;
invalidObjectiveVectorValue = false;
}
void objectiveVector (const ObjectiveVector & _objectiveVectorValue)
{
objectiveVectorValue = _objectiveVectorValue;
invalidObjectiveVectorValue = false;
}
/**
* Sets the objective vector as invalid
*/
void invalidateObjectiveVector()
{
invalidObjectiveVectorValue = true;
}
void invalidateObjectiveVector ()
{
invalidObjectiveVectorValue = true;
}
/**
* Returns true if the objective vector is invalid, false otherwise
*/
bool invalidObjectiveVector() const
{
return invalidObjectiveVectorValue;
}
bool invalidObjectiveVector () const
{
return invalidObjectiveVectorValue;
}
/**
* Returns the fitness value of the current solution
*/
Fitness fitness() const
{
if ( invalidFitness() )
{
throw std::runtime_error("invalid fitness");
}
return fitnessValue;
}
Fitness fitness () const
{
if (invalidFitness ())
{
throw std::runtime_error ("invalid fitness");
}
return fitnessValue;
}
/**
* Sets the fitness value of the current solution
* @param _fitnessValue the new fitness value
*/
void fitness(const Fitness & _fitnessValue)
{
fitnessValue = _fitnessValue;
invalidFitnessValue = false;
}
void fitness (const Fitness & _fitnessValue)
{
fitnessValue = _fitnessValue;
invalidFitnessValue = false;
}
/**
* Sets the fitness value as invalid
*/
void invalidateFitness()
{
invalidFitnessValue = true;
}
void invalidateFitness ()
{
invalidFitnessValue = true;
}
/**
* Returns true if the fitness value is invalid, false otherwise
*/
bool invalidFitness() const
{
return invalidFitnessValue;
}
bool invalidFitness () const
{
return invalidFitnessValue;
}
/**
* Returns the diversity value of the current solution
*/
Diversity diversity() const
{
if ( invalidDiversity() )
{
throw std::runtime_error("invalid diversity");
}
return diversityValue;
}
Diversity diversity () const
{
if (invalidDiversity ())
{
throw std::runtime_error ("invalid diversity");
}
return diversityValue;
}
/**
* Sets the diversity value of the current solution
* @param _diversityValue the new diversity value
*/
void diversity(const Diversity & _diversityValue)
{
diversityValue = _diversityValue;
invalidDiversityValue = false;
}
void diversity (const Diversity & _diversityValue)
{
diversityValue = _diversityValue;
invalidDiversityValue = false;
}
/**
* Sets the diversity value as invalid
*/
void invalidateDiversity()
{
invalidDiversityValue = true;
}
void invalidateDiversity ()
{
invalidDiversityValue = true;
}
/**
* Returns true if the diversity value is invalid, false otherwise
*/
bool invalidDiversity() const
{
return invalidDiversityValue;
}
bool invalidDiversity () const
{
return invalidDiversityValue;
}
/**
* Sets the objective vector, the fitness value and the diversity value as invalid
*/
void invalidate()
{
invalidateObjectiveVector();
invalidateFitness();
invalidateDiversity();
}
void invalidate ()
{
invalidateObjectiveVector ();
invalidateFitness ();
invalidateDiversity ();
}
/**
* Returns true if the fitness value is invalid, false otherwise
*/
bool invalid() const
{
return invalidObjectiveVector();
}
*/
bool invalid () const
{
return invalidObjectiveVector ();
}
/**
* Return the class id (the class name as a std::string)
*/
virtual std::string className() const
{
return "MOEO";
}
virtual std::string className () const
{
return "MOEO";
}
/**
* Writing object
* @param _os output stream
*/
virtual void printOn(std::ostream & _os) const
{
if ( invalidObjectiveVector() )
{
_os << "INVALID\t";
}
else
{
_os << objectiveVectorValue << '\t';
}
}
virtual void printOn (std::ostream & _os) const
{
if (invalidObjectiveVector ())
{
_os << "INVALID\t";
}
else
{
_os << objectiveVectorValue << '\t';
}
}
/**
* Reading object
* @param _is input stream
*/
virtual void readFrom(std::istream & _is)
{
std::string objectiveVector_str;
int pos = _is.tellg();
_is >> objectiveVector_str;
if (objectiveVector_str == "INVALID")
{
invalidateObjectiveVector();
}
else
{
invalidObjectiveVectorValue = false;
_is.seekg(pos); // rewind
_is >> objectiveVectorValue;
}
}
*/
virtual void readFrom (std::istream & _is)
{
std::string objectiveVector_str;
int pos = _is.tellg ();
_is >> objectiveVector_str;
if (objectiveVector_str == "INVALID")
{
invalidateObjectiveVector ();
}
else
{
invalidObjectiveVectorValue = false;
_is.seekg (pos); // rewind
_is >> objectiveVectorValue;
}
}
private:
/** the objective vector of this solution */
ObjectiveVector objectiveVectorValue;
ObjectiveVector objectiveVectorValue;
/** true if the objective vector is invalid */
bool invalidObjectiveVectorValue;
bool invalidObjectiveVectorValue;
/** the fitness value of this solution */
Fitness fitnessValue;
Fitness fitnessValue;
/** true if the fitness value is invalid */
bool invalidFitnessValue;
bool invalidFitnessValue;
/** the diversity value of this solution */
Diversity diversityValue;
Diversity diversityValue;
/** true if the diversity value is invalid */
bool invalidDiversityValue;
bool invalidDiversityValue;
};
#endif /*MOEO_H_*/
#endif /*MOEO_H_ */

203
branches/paradiseo-moeo-1.0/src/moeoArchive.h
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@ -14,141 +14,148 @@
#define MOEOARCHIVE_H_
#include <eoPop.h>
#include <moeoObjectiveVectorComparator.h>
/**
* An archive is a secondary population that stores non-dominated solutions.
* An archive is a secondary population that stores non-dominated solutions
*/
template < class MOEOT >
class moeoArchive : public eoPop < MOEOT >
template < class MOEOT > class moeoArchive:public eoPop < MOEOT >
{
public:
using std::vector < MOEOT > :: size;
using std::vector < MOEOT > :: operator[];
using std::vector < MOEOT > :: back;
using std::vector < MOEOT > :: pop_back;
using std::vector < MOEOT >::size;
using std::vector < MOEOT >::operator[];
using std::vector < MOEOT >::back;
using std::vector < MOEOT >::pop_back;
/**
* The type of an objective vector for a solution
*/
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Default ctor.
* The moeoObjectiveVectorComparator used to compare solutions is based on Pareto dominance
*/
moeoArchive() : eoPop < MOEOT >(), comparator(paretoComparator)
{}
moeoArchive ():eoPop < MOEOT > (), comparator (paretoComparator)
{
}
/**
* Ctor
* @param _comparator the moeoObjectiveVectorComparator used to compare solutions
*/
moeoArchive(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator) : eoPop < MOEOT >(), comparator(_comparator)
{}
moeoArchive (moeoObjectiveVectorComparator < ObjectiveVector > &_comparator):eoPop < MOEOT > (),
comparator
(_comparator)
{
}
/**
* Returns true if the current archive dominates _objectiveVector according to the moeoObjectiveVectorComparator given in the constructor
* @param _objectiveVector the objective vector to compare with the current archive
*/
bool dominates (const ObjectiveVector & _objectiveVector) const
{
for (unsigned i = 0; i<size(); i++)
{
if ( comparator(operator[](i).fitness(), _objectiveVector) == 1 )
{
return true;
}
}
return false;
}
bool dominates (const ObjectiveVector & _objectiveVector) const
{
for (unsigned i = 0; i < size (); i++)
{
if (comparator (operator[](i).fitness (), _objectiveVector) == 1)
{
return true;
}
}
return false;
}
/**
* Returns true if the current archive already contains a solution with the same objective values than _objectiveVector
* @param _objectiveVector the objective vector to compare with the current archive
*/
bool contains (const ObjectiveVector & _objectiveVector) const
{
for (unsigned i = 0; i<size(); i++)
{
if (operator[](i).fitness() == _objectiveVector)
{
return true;
}
}
return false;
}
bool contains (const ObjectiveVector & _objectiveVector) const
{
for (unsigned i = 0; i < size; i++)
{
if (operator[](i).fitness () == _objectiveVector)
{
return true;
}
}
return false;
}
/**
* Updates the archive with a given individual _moeo
* @param _moeo the given individual
*/
void update (const MOEOT & _moeo)
{
// first step: removing the dominated solutions from the archive
for (unsigned j=0; j<size();)
{
// if _moeo dominates the jth solution contanied in the archive
if ( comparator(_moeo.objectiveVector(), operator[](j).objectiveVector())==1 )
{
operator[](j) = back();
pop_back();
}
else if (_moeo.objectiveVector() == operator[](j).objectiveVector())
{
operator[](j) = back();
pop_back();
}
else
{
j++;
}
}
// second step: is _moeo dominated?
bool dom = false;
for (unsigned j=0; j<size(); j++)
{
// if the jth solution contanied in the archive dominates _moeo
if ( comparator(operator[](j).objectiveVector(), _moeo.objectiveVector()) == 1 )
{
dom = true;
break;
}
}
if (!dom)
{
push_back(_moeo);
}
}
void update (const MOEOT & _moeo)
{
// first step: removing the dominated solutions from the archive
for (unsigned j = 0; j < size ();)
{
// if _moeo.fitness() dominates operator[](j).fitness()
//if ( comparator(_moeo.fitness(), operator[](j).fitness())==1 )
if (comparator
(_moeo.objectiveVector (), operator[](j).objectiveVector ()) == 1)
{
operator[](j) = back ();
pop_back ();
}
//else if (_moeo.fitness() == operator[](j).fitness())
else if (_moeo.objectiveVector () == operator[](j).objectiveVector ())
{
operator[](j) = back ();
pop_back ();
}
else
{
j++;
}
}
// second step: is _moeo dominated?
bool dom = false;
for (unsigned j = 0; j < size (); j++)
{
// if operator[](j).fitness() dominates _moeo.fitness()
//if ( comparator(operator[](j).fitness(), _moeo.fitness())==1 )
if (comparator
(operator[](j).objectiveVector (), _moeo.objectiveVector ()) == 1)
{
dom = true;
break;
}
}
if (!dom)
{
push_back (_moeo);
}
}
/**
* Updates the archive with a given population _pop
* @param _pop the given population
*/
void update (const eoPop < MOEOT > & _pop)
{
for (unsigned i=0; i<_pop.size(); i++)
{
update(_pop[i]);
}
}
void update (const eoPop < MOEOT > &_pop)
{
for (unsigned i = 0; i < _pop.size (); i++)
{
update (_pop[i]);
}
}
private:
/** The moeoObjectiveVectorComparator used to compare solutions */
moeoObjectiveVectorComparator < ObjectiveVector > & comparator;
moeoObjectiveVectorComparator < ObjectiveVector > &comparator;
/** A moeoObjectiveVectorComparator based on Pareto dominance (used as default) */
moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;
moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;
};
#endif /*MOEOARCHIVE_H_ */

31
branches/paradiseo-moeo-1.0/src/moeoArchiveFitnessSavingUpdater.h
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@ -24,8 +24,7 @@
/**
* This class allows to save the fitnesses of solutions contained in an archive into a file at each generation.
*/
template <class EOT>
class moeoArchiveFitnessSavingUpdater : public eoUpdater
template < class EOT > class moeoArchiveFitnessSavingUpdater:public eoUpdater
{
public:
@ -35,21 +34,25 @@ public:
* @param _filename target filename
* @param _id own ID
*/
moeoArchiveFitnessSavingUpdater (moeoArchive<EOT> & _arch, const std::string & _filename = "Res/Arch", int _id = -1) : arch(_arch), filename(_filename), id(_id), counter(0)
{}
moeoArchiveFitnessSavingUpdater (moeoArchive < EOT > &_arch, const std::string & _filename = "Res/Arch", int _id = -1):arch (_arch), filename (_filename), id (_id),
counter
(0)
{
}
/**
* Saves the fitness of the archive's members into the file
*/
void operator()() {
void operator () ()
{
char buff[MAX_BUFFER_SIZE];
if (id == -1)
sprintf (buff, "%s.%u", filename.c_str(), counter ++);
sprintf (buff, "%s.%u", filename.c_str (), counter++);
else
sprintf (buff, "%s.%u.%u", filename.c_str(), id, counter ++);
std::ofstream f(buff);
sprintf (buff, "%s.%u.%u", filename.c_str (), id, counter++);
std::ofstream f (buff);
for (unsigned i = 0; i < arch.size (); i++)
f << arch[i].objectiveVector() << std::endl;
f << arch[i].objectiveVector () << std::endl;
f.close ();
}
@ -57,14 +60,14 @@ public:
private:
/** local archive */
moeoArchive<EOT> & arch;
moeoArchive < EOT > &arch;
/** target filename */
std::string filename;
std::string filename;
/** own ID */
int id;
int id;
/** counter */
unsigned counter;
unsigned counter;
};
#endif /*MOEOARCHIVEFITNESSSAVINGUPDATER_H_*/
#endif /*MOEOARCHIVEFITNESSSAVINGUPDATER_H_ */

28
branches/paradiseo-moeo-1.0/src/moeoArchiveUpdater.h
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@ -18,37 +18,39 @@
#include <moeoArchive.h>
/**
* This class allows to update the archive at each generation with newly found non-dominated solutions.
* This class allows to update the archive at each generation with newly found non-dominated solutions
*/
template < class EOT >
class moeoArchiveUpdater : public eoUpdater
template < class EOT > class moeoArchiveUpdater:public eoUpdater
{
public:
/**
* Ctor
* @param _arch an archive of non-dominated solutions
* @param _pop the main population
*/
moeoArchiveUpdater(moeoArchive <EOT> & _arch, const eoPop<EOT> & _pop) : arch(_arch), pop(_pop)
{}
moeoArchiveUpdater (moeoArchive < EOT > &_arch,
const eoPop < EOT > &_pop):arch (_arch), pop (_pop)
{
}
/**
* Updates the archive with newly found non-dominated solutions contained in the main population
*/
void operator()() {
arch.update(pop);
void operator () ()
{
arch.update (pop);
}
private:
/** the archive of non-dominated solutions */
moeoArchive<EOT> & arch;
moeoArchive < EOT > &arch;
/** the main population */
const eoPop<EOT> & pop;
const eoPop < EOT > &pop;
};
#endif /*MOEOARCHIVEUPDATER_H_*/
#endif /*MOEOARCHIVEUPDATER_H_ */

52
branches/paradiseo-moeo-1.0/src/moeoCombinedLS.h
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@ -19,53 +19,53 @@
/**
* This class allows to embed a set of local searches that are sequentially applied,
* and so working and updating the same archive of non-dominated solutions.
* and so working and updating the same archive of non-dominated solutions
*/
template < class MOEOT >
class moeoCombinedLS : public moeoLS < MOEOT >
template < class MOEOT > class moeoCombinedLS:public moeoLS < MOEOT >
{
public:
/**
* Ctor
* @param _eval the full evaluator of a solution
* @param _first_mols the first multi-objective local search to add
* @param _first_ls the first multi-objective local search to add
*/
moeoCombinedLS(moeoEvalFunc < MOEOT > & _eval, moeoLS < MOEOT > & _first_mols) : eval (_eval)
{
combinedLS.push_back (& _first_mols);
}
moeoCombinedLS (moeoEvalFunc < MOEOT > &_eval, moeoLS < MOEOT > &_first_ls):eval
(_eval)
{
combinedLS.push_back (&_first_ls);
}
/**
* Adds a new local search to combine
* @param _mols the multi-objective local search to add
* @param _ls the multi-objective local search to add
*/
void add(moeoLS < MOEOT > & _mols)
{
combinedMOLS.push_back(& _mols);
}
void add (moeoLS < MOEOT > &_ls)
{
combinedMOLS.push_back (&_ls);
}
/**
* Gives a new solution in order to explore the neigborhood.
* The new non-dominated solutions are added to the archive
* @param _moeo the solution
* @param _eo the solution
* @param _arch the archive of non-dominated solutions
*/
void operator () (const MOEOT & _moeo, moeoArchive < MOEOT > & _arch)
{
eval(const_cast < MOEOT & > (_moeo));
for (unsigned i=0; i<combinedLS.size(); i++)
combinedLS[i] -> operator()(_moeo, _arch);
}
void operator () (const MOEOT & _eo, moeoArchive < MOEOT > &_arch)
{
eval (const_cast < MOEOT & >(_eo));
for (unsigned i = 0; i < combinedLS.size (); i++)
combinedLS[i]->operator ()(_eo, _arch);
}
private:
/** the full evaluator of a solution */
moeoEvalFunc < MOEOT > & eval;
moeoEvalFunc < MOEOT > &eval;
/** the vector that contains the combined LS */
std::vector< moeoLS < MOEOT > * > combinedLS;
std::vector < moeoLS < MOEOT > *>combinedLS;
};
#endif /*MOEOCOMBINEDLS_H_*/
#endif /*MOEOCOMBINEDLS_H_ */

154
branches/paradiseo-moeo-1.0/src/moeoComparator.h
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@ -14,20 +14,24 @@
#define MOEOCOMPARATOR_H_
#include <eoFunctor.h>
#include <eoPop.h>
/**
* Functor allowing to compare two solutions.
* Functor allowing to compare two solutions
*/
template < class MOEOT >
class moeoComparator : public eoBF < const MOEOT &, const MOEOT &, const bool >
{};
template < class MOEOT > class moeoComparator:public eoBF < const MOEOT &, const MOEOT &,
const bool >
{
public:
// virtual const bool operator () (const MOEOT & _moeo1, const MOEOT & _moeo){}
};
/**
* Functor allowing to compare two solutions according to their first objective value, then their second, and so on.
* Functor allowing to compare two solutions according to their first objective value, then their second, and so on
*/
template < class MOEOT >
class moeoObjectiveComparator : public moeoComparator < MOEOT >
template < class MOEOT > class moeoObjectiveComparator:public moeoComparator <
MOEOT >
{
public:
/**
@ -35,56 +39,56 @@ public:
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
return _moeo1.objectiveVector() < _moeo2.objectiveVector();
}
const bool operator () (const MOEOT & _moeo1, const MOEOT & _moeo2)
{
return _moeo1.objectiveVector () < _moeo2.objectiveVector ();
}
};
/**
* Functor allowing to compare two solutions according to their fitness values.
* Functor allowing to compare two solutions according to their fitness values
*/
template < class MOEOT >
class moeoFitnessComparator : public moeoComparator < MOEOT >
{
public:
/**
* Returns true if the fitness value of _moeo1 is smaller than the fitness value of _moeo2
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
return _moeo1.fitness() < _moeo2.fitness();
}
};
//template < class MOEOT >
//class moeoFitnessComparator : public moeoComparator < MOEOT >
//{
//public:
// /**
// * Returns true if the fitness value of _moeo1 is smaller than the fitness value of _moeo2
// * @param _moeo1 the first solution
// * @param _moeo2 the second solution
// */
// const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
// {
// return _moeo1.fitness() < _moeo2.fitness();
// }
//};
//
//
///**
// * Functor allowing to compare two solutions according to their diversity values
// */
//template < class MOEOT >
//class moeoDiversityComparator : public moeoComparator < MOEOT >
//{
//public:
// /**
// * Returns true if the diversity value of _moeo1 is smaller than the diversity value of _moeo2
// * @param _moeo1 the first solution
// * @param _moeo2 the second solution
// */
// const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
// {
// return _moeo1.diversity() < _moeo2.diversity();
// }
//};
/**
* Functor allowing to compare two solutions according to their diversity values.
* Functor allowing to compare two solutions according to their fitness values, then according to their diversity values
*/
template < class MOEOT >
class moeoDiversityComparator : public moeoComparator < MOEOT >
{
public:
/**
* Returns true if the diversity value of _moeo1 is smaller than the diversity value of _moeo2
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
return _moeo1.diversity() < _moeo2.diversity();
}
};
/**
* Functor allowing to compare two solutions according to their fitness values, then according to their diversity values.
*/
template < class MOEOT >
class moeoFitnessThenDiversityComparator : public moeoComparator < MOEOT >
template < class MOEOT > class moeoFitnessThenDiversityComparator:public moeoComparator <
MOEOT >
{
public:
/**
@ -92,25 +96,25 @@ public:
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
if (_moeo1.fitness() == _moeo2.fitness())
{
return _moeo1.diversity() < _moeo2.diversity();
}
else
{
return _moeo1.fitness() < _moeo2.fitness();
}
}
const bool operator () (const MOEOT & _moeo1, const MOEOT & _moeo2)
{
if (_moeo1.fitness () == _moeo2.fitness ())
{
return _moeo1.diversity () < _moeo2.diversity ();
}
else
{
return _moeo1.fitness () < _moeo2.fitness ();
}
}
};
/**
* Functor allowing to compare two solutions according to their diversity values, then according to their fitness values.
* Functor allowing to compare two solutions according to their diversity values, then according to their fitness values
*/
template < class MOEOT >
class moeoDiversityThenFitnessComparator : public moeoComparator < MOEOT >
template < class MOEOT > class moeoDiversityThenFitnessComparator:public moeoComparator <
MOEOT >
{
public:
/**
@ -118,22 +122,22 @@ public:
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
if (_moeo1.diversity() == _moeo2.diversity())
{
return _moeo1.fitness() < _moeo2.fitness();
}
else
{
return _moeo1.diversity() < _moeo2.diversity();
}
}
const bool operator () (const MOEOT & _moeo1, const MOEOT & _moeo2)
{
if (_moeo1.diversity () == _moeo2.diversity ())
{
return _moeo1.fitness () < _moeo2.fitness ();
}
else
{
return _moeo1.diversity () < _moeo2.diversity ();
}
}
};
/**
* Functor allowing to compare two solutions according to Pareto dominance relation. => USEFULL ???
* Functor allowing to compare two solutions according to Pareto dominance relation => USEFULL ???
*
template < class MOEOT >
class moeoParetoDominanceComparator : public moeoComparator < MOEOT >
@ -178,4 +182,4 @@ public:
};
*/
#endif /*MOEOCOMPARATOR_H_*/
#endif /*MOEOCOMPARATOR_H_ */

32
branches/paradiseo-moeo-1.0/src/moeoDiversityAssignment.h
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@ -17,10 +17,32 @@
#include <eoPop.h>
/**
* Functor that sets the diversity values of a whole population.
* Functor that sets the diversity values of a whole population
*/
template < class MOEOT >
class moeoDiversityAssignment : public eoUF < eoPop < MOEOT > &, void >
{};
template < class MOEOT > class moeoDiversityAssignment:public eoUF < eoPop < MOEOT > &,
void >
{
};
#endif /*MOEODIVERSITYASSIGNMENT_H_*/
/**
* moeoDummyDiversityAssignment is a moeoDiversityAssignment which gives 0 as the diversity for the whole population.
*/
template < class MOEOT > class moeoDummyDiversityAssignment:public moeoDiversityAssignment <
MOEOT >
{
// main operator
void operator () (eoPop < MOEOT > &_pop)
{
for (int idx = 0; idx < _pop.size (); idx++)
{
// set the diversity to 0
_pop[idx].diversity (0);
}
}
};
#endif /*MOEODIVERSITYASSIGNMENT_H_ */

9
branches/paradiseo-moeo-1.0/src/moeoEA.h
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@ -16,10 +16,11 @@
#include <eoAlgo.h>
/**
* Abstract class for multi-objective evolutionary algorithms.
* Abstract class for multi-objective evolutionary algorithms
*/
template < class MOEOT >
class moeoEA : public eoAlgo < MOEOT > {};
template < class MOEOT > class moeoEA:public eoAlgo < MOEOT >
{
};
#endif /*MOEOEA_H_*/
#endif /*MOEOEA_H_ */

7
branches/paradiseo-moeo-1.0/src/moeoEvalFunc.h
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@ -18,7 +18,8 @@
/*
* Functor that evaluates one MOEO by setting all its objective values.
*/
template < class MOEOT >
class moeoEvalFunc : public eoEvalFunc< MOEOT > {};
template < class MOEOT > class moeoEvalFunc:public eoEvalFunc < MOEOT >
{
};
#endif /*MOEOEVALFUNC_H_*/
#endif /*MOEOEVALFUNC_H_ */

251
branches/paradiseo-moeo-1.0/src/moeoFastNonDominatedSortingFitnessAssignment.h
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@ -14,163 +14,170 @@
#define MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_
#include <eoPop.h>
#include <moeoComparator.h>
#include <moeoFitnessAssignment.h>
#include <moeoComparator.h>
#include <moeoObjectiveVectorComparator.h>
/**
* Fitness assignment sheme based on Pareto-dominance count proposed in:
* *N. Srinivas, K. Deb, "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms", Evolutionary Computation vol. 2, no. 3, pp. 221-248 (1994)*
* and in:
* *K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, "A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II", IEEE Transactions on Evolutionary Computation, vol. 6, no. 2 (2002)*.
* Fitness assignment sheme based on Pareto-dominance count proposed in
* N. Srinivas, K. Deb, "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms", Evolutionary Computation vol. 2, no. 3, pp. 221-248 (1994)
* and in
* K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, "A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II", IEEE Transactions on Evolutionary Computation, vol. 6, no. 2 (2002).
* This strategy is, for instance, used in NSGA and NSGA-II.
*/
template < class MOEOT >
class moeoFastNonDominatedSortingFitnessAssignment : public moeoParetoBasedFitnessAssignment < MOEOT >
template < class MOEOT > class moeoFastNonDominatedSortingFitnessAssignment:public moeoParetoBasedFitnessAssignment <
MOEOT
>
{
public:
/**
* Ctor
*/
moeoFastNonDominatedSortingFitnessAssignment() {}
moeoFastNonDominatedSortingFitnessAssignment ()
{
}
/**
* Computes fitness values for every solution contained in the population _pop
* @param _pop the population
*/
void operator()(eoPop < MOEOT > & _pop)
{
// number of objectives for the problem under consideration
unsigned nObjectives = MOEOT::ObjectiveVector::nObjectives();
if (nObjectives == 1)
{
// one objective
oneObjective(_pop);
}
else if (nObjectives == 2)
{
// two objectives (the two objectives function is still to implement)
mObjectives(_pop);
}
else if (nObjectives > 2)
{
// more than two objectives
mObjectives(_pop);
}
else
{
// problem with the number of objectives
throw std::runtime_error("Problem with the number of objectives in moeoFastNonDominatedSortingFitnessAssignment");
}
}
void operator () (eoPop < MOEOT > &_pop)
{
// number of objectives for the problem under consideration
unsigned nObjectives = MOEOT::ObjectiveVector::nObjectives ();
if (nObjectives == 1)
{
// one objective
oneObjective (_pop);
}
else if (nObjectives == 2)
{
// two objectives (the two objectives function is still to do)
mObjectives (_pop);
}
else if (nObjectives > 2)
{
// more than two objectives
mObjectives (_pop);
}
else
{
// problem with the number of objectives
throw std::
runtime_error
("Problem with the number of objectives in moeoFastNonDominatedSortingFitnessAssignment");
}
}
private:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/** Functor to compare two objective vectors according to Pareto dominance relation */
moeoParetoObjectiveVectorComparator < ObjectiveVector > comparator;
moeoParetoObjectiveVectorComparator < ObjectiveVector > comparator;
/** Functor to compare two solutions on the first objective, then on the second, and so on */
moeoObjectiveComparator < MOEOT > objComparator;
moeoObjectiveComparator < MOEOT > objComparator;
/**
* Sets the fitness values for mono-objective problems
* @param _pop the population
*/
void oneObjective (eoPop < MOEOT > & _pop)
{
std::sort(_pop.begin(), _pop.end(), objComparator);
for (unsigned i=0; i<_pop.size(); i++)
{
_pop[i].fitness(i+1);
}
}
void oneObjective (eoPop < MOEOT > &_pop)
{
std::sort (_pop.begin (), _pop.end (), objComparator);
for (unsigned i = 0; i < _pop.size (); i++)
{
_pop[i].fitness (i + 1);
}
}
/**
* Sets the fitness values for bi-objective problems with a complexity of O(n log n), where n stands for the population size
* @param _pop the population
*/
void twoObjectives (eoPop < MOEOT > & _pop)
{
//... TO DO !
}
void twoObjectives (eoPop < MOEOT > &_pop)
{
//... TO DO !
}
/**
* Sets the fitness values for problems with more than two objectives with a complexity of O(n² log n), where n stands for the population size
* @param _pop the population
*/
void mObjectives (eoPop < MOEOT > & _pop)
{
// S[i] = indexes of the individuals dominated by _pop[i]
std::vector < std::vector<unsigned> > S(_pop.size());
// n[i] = number of individuals that dominate the individual _pop[i]
std::vector < unsigned > n(_pop.size(), 0);
// fronts: F[i] = indexes of the individuals contained in the ith front
std::vector < std::vector<unsigned> > F(_pop.size()+1);
// used to store the number of the first front
F[1].reserve(_pop.size());
// flag to comparae solutions
int comparatorFlag;
for (unsigned p=0; p<_pop.size(); p++)
{
for (unsigned q=0; q<_pop.size(); q++)
{
// comparison of the 2 solutions according to Pareto dominance
comparatorFlag = comparator(_pop[p].objectiveVector(), _pop[q].objectiveVector());
// if p dominates q
if (comparatorFlag == 1)
{
// add q to the set of solutions dominated by p
S[p].push_back(q);
}
// if q dominates p
else if (comparatorFlag == -1)
{
// increment the domination counter of p
n[p]++;
}
}
// if no individual dominates p
if (n[p] == 0)
{
// p belongs to the first front
_pop[p].fitness(1);
F[1].push_back(p);
}
}
// front counter
unsigned counter=1;
unsigned p,q;
while (! F[counter].empty())
{
// used to store the number of the next front
F[counter+1].reserve(_pop.size());
for (unsigned i=0; i<F[counter].size(); i++)
{
p = F[counter][i];
for (unsigned j=0; j<S[p].size(); j++)
{
q = S[p][j];
n[q]--;
// if no individual dominates q anymore
if (n[q] == 0)
{
// q belongs to the next front
_pop[q].fitness(counter+1);
F[counter+1].push_back(q);
}
}
}
counter++;
}
}
void mObjectives (eoPop < MOEOT > &_pop)
{
// S[i] = indexes of the individuals dominated by _pop[i]
std::vector < std::vector < unsigned >>S (_pop.size ());
// n[i] = number of individuals that dominate the individual _pop[i]
std::vector < unsigned >n (_pop.size (), 0);
// fronts: F[i] = indexes of the individuals contained in the ith front
std::vector < std::vector < unsigned >>F (_pop.size () + 1);
// used to store the number of the first front
F[1].reserve (_pop.size ());
// flag to comparae solutions
int comparatorFlag;
for (unsigned p = 0; p < _pop.size (); p++)
{
for (unsigned q = 0; q < _pop.size (); q++)
{
// comparison of the 2 solutions according to Pareto dominance
comparatorFlag =
comparator (_pop[p].objectiveVector (),
_pop[q].objectiveVector ());
// if p dominates q
if (comparatorFlag == 1)
{
// add q to the set of solutions dominated by p
S[p].push_back (q);
}
// if q dominates p
else if (comparatorFlag == -1)
{
// increment the domination counter of p
n[p]++;
}
}
// if no individual dominates p
if (n[p] == 0)
{
// p belongs to the first front
_pop[p].fitness (1);
F[1].push_back (p);
}
}
// front counter
unsigned counter = 1;
unsigned p, q;
while (!F[counter].empty ())
{
// used to store the number of the next front
F[counter + 1].reserve (_pop.size ());
for (unsigned i = 0; i < F[counter].size (); i++)
{
p = F[counter][i];
for (unsigned j = 0; j < S[p].size (); j++)
{
q = S[p][j];
n[q]--;
// if no individual dominates q anymore
if (n[q] == 0)
{
// q belongs to the next front
_pop[q].fitness (counter + 1);
F[counter + 1].push_back (q);
}
}
}
counter++;
}
}
};
#endif /*MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_*/
#endif /*MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_ */

45
branches/paradiseo-moeo-1.0/src/moeoFitnessAssignment.h
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@ -17,35 +17,46 @@
#include <eoPop.h>
/**
* Functor that sets the fitness values of a whole population.
* Functor that sets the fitness values of a whole population
*/
template < class MOEOT >
class moeoFitnessAssignment : public eoUF < eoPop < MOEOT > &, void >
{};
template < class MOEOT > class moeoFitnessAssignment:public eoUF < eoPop < MOEOT > &,
void >
{
};
/**
* moeoScalarFitnessAssignment is a moeoFitnessAssignment for scalar strategies.
* moeoScalarFitnessAssignment is a moeoFitnessAssignment for scalar strategies
*/
template < class MOEOT >
class moeoScalarFitnessAssignment : public moeoFitnessAssignment < MOEOT >
{};
template < class MOEOT > class moeoScalarFitnessAssignment:public moeoFitnessAssignment <
MOEOT >
{
};
/**
* moeoCriterionBasedFitnessAssignment is a moeoFitnessAssignment for criterion-based strategies.
* moeoCriterionBasedFitnessAssignment is a moeoFitnessAssignment for criterion-based strategies
*/
template < class MOEOT >
class moeoCriterionBasedFitnessAssignment : public moeoFitnessAssignment < MOEOT >
{};
template < class MOEOT > class moeoCriterionBasedFitnessAssignment:public moeoFitnessAssignment <
MOEOT >
{
};
/**
* moeoParetoBasedFitnessAssignment is a moeoFitnessAssignment for Pareto-based strategies.
* moeoParetoBasedFitnessAssignment is a moeoFitnessAssignment for Pareto-based strategies
*/
template < class MOEOT >
class moeoParetoBasedFitnessAssignment : public moeoFitnessAssignment < MOEOT >
{};
template < class MOEOT > class moeoParetoBasedFitnessAssignment:public moeoFitnessAssignment <
MOEOT >
{
void operator () (eoPop < MOEOT > &_pop)
{
// do nothing for the moment ...
}
};
#endif /*MOEOFITNESSASSIGNMENT_H_*/
#endif /*MOEOFITNESSASSIGNMENT_H_ */

11
branches/paradiseo-moeo-1.0/src/moeoGenerationalReplacement.h
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@ -17,9 +17,12 @@
#include <moeoGenerationalReplacement.h>
/**
* Generational replacement: only the new individuals are preserved.
* Generational replacement: only the new individuals are preserved
*/
template < class MOEOT >
class moeoGenerationalReplacement : public moeoReplacement < MOEOT >, public eoGenerationalReplacement < MOEOT > {};
template < class MOEOT > class moeoGenerationalReplacement:public moeoReplacement < MOEOT >,
public eoGenerationalReplacement <
MOEOT >
{
};
#endif /*MOEOGENERATIONALREPLACEMENT_H_*/
#endif /*MOEOGENERATIONALREPLACEMENT_H_ */

50
branches/paradiseo-moeo-1.0/src/moeoHybridLS.h
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@ -24,8 +24,7 @@
* This class allows to apply a multi-objective local search to a number of selected individuals contained in the archive
* at every generation until a stopping criteria is verified.
*/
template < class MOEOT >
class moeoHybridLS : public eoUpdater
template < class MOEOT > class moeoHybridLS:public eoUpdater
{
public:
@ -33,42 +32,45 @@ public:
* Ctor
* @param _term stopping criteria
* @param _select selector
* @param _mols a multi-objective local search
* @param _ls a multi-objective local search
* @param _arch the archive
*/
eoHybridLS (eoContinue < MOEOT > & _term, eoSelect < MOEOT > & _select, moeoLS < MOEOT > & _mols, moeoArchive < MOEOT > & _arch) : term(_term), select(_select), mols(_mols), arch(_arch)
{}
eoHybridLS (eoContinue < MOEOT > &_term, eoSelect < MOEOT > &_select, moeoLS < MOEOT > &_ls, moeoArchive < MOEOT > &_arch):term (_term), select (_select), ls (_ls),
arch
(_arch)
{
}
/**
* Applies the multi-objective local search to selected individuals contained in the archive if the stopping criteria is not verified
*/
void operator () ()
{
if (! cont (arch))
{
// selection of solutions
eoPop < MOEOT > selectedSolutions;
select(arch, selectedSolutions);
// apply the local search to every selected solution
for (unsigned i=0; i<selectedSolutions.size(); i++)
{
mols(selectedSolutions[i], arch);
}
}
}
void operator () ()
{
if (!cont (arch))
{
// selection of solutions
eoPop < MOEOT > selectedSolutions;
select (arch, selectedSolutions);
// apply the local search to every selected solution
for (unsigned i = 0; i < selectedSolutions.size (); i++)
{
ls (selectedSolutions[i], arch);
}
}
}
private:
/** stopping criteria*/
eoContinue < MOEOT > & term;
eoContinue < MOEOT > &term;
/** selector */
eoSelect < MOEOT > & select;
eoSelect < MOEOT > &select;
/** multi-objective local search */
moeoLS < MOEOT > & mols;
moeoLS < MOEOT > &ls;
/** archive */
moeoArchive < MOEOT > & arch;
moeoArchive < MOEOT > &arch;
};
#endif /*MOEOHYBRIDLS_H_*/
#endif /*MOEOHYBRIDLS_H_ */

9
branches/paradiseo-moeo-1.0/src/moeoLS.h
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@ -20,8 +20,9 @@
* Abstract class for local searches applied to multi-objective optimization.
* Starting from only one solution, it produces a set of new non-dominated solutions.
*/
template < class MOEOT >
class moeoLS: public eoBF < const MOEOT &, moeoArchive < MOEOT > &, void >
{};
template < class MOEOT > class moeoLS:public eoBF < const MOEOT &, moeoArchive < MOEOT > &,
void >
{
};
#endif /*MOEOLS_H_*/
#endif /*MOEOLS_H_ */

273
branches/paradiseo-moeo-1.0/src/moeoObjectiveVector.h
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@ -24,52 +24,54 @@
* but it can be replaced at will by any other class that implements the static functions defined therein.
* Some static funtions to access to the traits characteristics are re-defined in order not to write a lot of typedef's.
*/
template < class ObjectiveVectorTraits >
class moeoObjectiveVector
template < class ObjectiveVectorTraits > class moeoObjectiveVector
{
public:
/** The traits of objective vectors */
typedef ObjectiveVectorTraits Traits;
typedef ObjectiveVectorTraits Traits;
/**
* Parameters setting (for the objective vector of any solution)
* @param _nObjectives the number of objectives
* @param _bObjectives the min/max vector (true = min / false = max)
*/
static void setup(unsigned _nObjectives, std::vector < bool > & _bObjectives)
{
ObjectiveVectorTraits::setup(_nObjectives, _bObjectives);
}
static void setup (unsigned _nObjectives,
std::vector < bool > &_bObjectives)
{
ObjectiveVectorTraits::setup (_nObjectives, _bObjectives);
}
/**
* Returns the number of objectives
*/
static unsigned nObjectives()
{
return ObjectiveVectorTraits::nObjectives();
}
static unsigned nObjectives ()
{
return ObjectiveVectorTraits::nObjectives ();
}
/**
* Returns true if the _ith objective have to be minimized
* @param _i the index
*/
static bool minimizing(unsigned _i) {
return ObjectiveVectorTraits::minimizing(_i);
}
static bool minimizing (unsigned _i)
{
return ObjectiveVectorTraits::minimizing (_i);
}
/**
* Returns true if the _ith objective have to be maximized
* @param _i the index
*/
static bool maximizing(unsigned _i) {
return ObjectiveVectorTraits::maximizing(_i);
}
static bool maximizing (unsigned _i)
{
return ObjectiveVectorTraits::maximizing (_i);
}
};
@ -77,122 +79,159 @@ public:
* This class allows to represent a solution in the objective space (phenotypic representation) by a std::vector of doubles,
* i.e. that an objective value is represented using a double, and this for any objective.
*/
template < class ObjectiveVectorTraits >
class moeoObjectiveVectorDouble : public moeoObjectiveVector < ObjectiveVectorTraits >, public std::vector < double >
template < class ObjectiveVectorTraits > class moeoObjectiveVectorDouble:public moeoObjectiveVector < ObjectiveVectorTraits >,
public std::vector <
double >
{
public:
using std::vector< double >::size;
using std::vector< double >::operator[];
public:
using
std::vector < double >::size;
using
std::vector < double >::operator[];
/**
* Ctor
*/
moeoObjectiveVectorDouble() : std::vector < double > (ObjectiveVectorTraits::nObjectives(), 0.0) {}
moeoObjectiveVectorDouble ():
std::vector < double >(ObjectiveVectorTraits::nObjectives (), 0.0)
{
}
/**
* Ctor from a vector of doubles
* @param _v the std::vector < double >
*/
moeoObjectiveVectorDouble(std::vector <double> & _v) : std::vector < double > (_v) {}
moeoObjectiveVectorDouble (std::vector < double >&_v):
std::vector < double >(_v)
{
}
/**
* Returns true if the current objective vector dominates _other according to the Pareto dominance relation
* (but it's better to use a moeoObjectiveVectorComparator object to compare solutions)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool dominates(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
moeoParetoObjectiveVectorComparator < moeoObjectiveVectorDouble<ObjectiveVectorTraits> > comparator;
return comparator(*this, _other)==1;
}
bool
dominates (const moeoObjectiveVectorDouble < ObjectiveVectorTraits >
&_other) const
{
moeoParetoObjectiveVectorComparator <
moeoObjectiveVectorDouble <
ObjectiveVectorTraits > >
comparator;
return
comparator (*this, _other) == 1;
}
/**
* Returns true if the current objective vector is equal to _other (according to a tolerance value)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator==(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
for (unsigned i=0; i < size(); i++)
{
if ( fabs(operator[](i) - _other[i]) > ObjectiveVectorTraits::tolerance() )
{
return false;
}
}
return true;
}
bool
operator== (const moeoObjectiveVectorDouble < ObjectiveVectorTraits >
&_other) const
{
for (unsigned i = 0; i < size (); i++)
{
if (fabs (operator[](i) - _other[i]) >
ObjectiveVectorTraits::tolerance ())
{
return false;
}
}
return
true;
}
/**
* Returns true if the current objective vector is different than _other (according to a tolerance value)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator!=(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
return ! operator==(_other);
}
bool
operator!= (const moeoObjectiveVectorDouble < ObjectiveVectorTraits >
&_other) const
{
return !
operator== (_other);
}
/**
* Returns true if the current objective vector is smaller than _other on the first objective, then on the second, and so on
* (can be usefull for sorting/printing)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator<(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
for (unsigned i=0; i < size(); i++)
{
if ( fabs(operator[](i) - _other[i]) > ObjectiveVectorTraits::tolerance() )
{
if (operator[](i) < _other[i])
{
return true;
}
else
{
return false;
}
}
}
*/
bool
operator< (const moeoObjectiveVectorDouble < ObjectiveVectorTraits >
&_other) const
{
for (unsigned i = 0; i < size (); i++)
{
if (fabs (operator[](i) - _other[i]) >
ObjectiveVectorTraits::tolerance ())
{
if (operator[](i) < _other[i])
{
return true;
}
else
{
return false;
}
}
}
}
return false;
}
/**
* Returns true if the current objective vector is greater than _other on the first objective, then on the second, and so on
* (can be usefull for sorting/printing)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator>(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
return _other < *this;
}
bool
operator> (const moeoObjectiveVectorDouble < ObjectiveVectorTraits >
&_other) const
{
return
_other < *
this;
}
/**
* Returns true if the current objective vector is smaller than or equal to _other on the first objective, then on the second, and so on
* (can be usefull for sorting/printing)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator<=(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
return operator==(_other) || operator<(_other);
}
bool
operator<= (const moeoObjectiveVectorDouble < ObjectiveVectorTraits >
&_other) const
{
return
operator== (_other) ||
operator< (_other);
}
/**
* Returns true if the current objective vector is greater than or equal to _other on the first objective, then on the second, and so on
* (can be usefull for sorting/printing)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator>=(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
return operator==(_other) || operator>(_other);
}
bool
operator>= (const moeoObjectiveVectorDouble < ObjectiveVectorTraits >
&_other) const
{
return
operator== (_other) ||
operator> (_other);
}
};
@ -203,13 +242,15 @@ public:
* @param _objectiveVector the objective vector to write
*/
template < class ObjectiveVectorTraits >
std::ostream & operator<<(std::ostream & _os, const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _objectiveVector)
std::ostream & operator<< (std::ostream & _os,
const moeoObjectiveVectorDouble <
ObjectiveVectorTraits > &_objectiveVector)
{
for (unsigned i=0; i<_objectiveVector.size(); i++)
{
_os << _objectiveVector[i] << ' ';
}
return _os;
for (unsigned i = 0; i < _objectiveVector.size (); i++)
{
_os << _objectiveVector[i] << ' ';
}
return _os;
}
/**
@ -218,14 +259,16 @@ std::ostream & operator<<(std::ostream & _os, const moeoObjectiveVectorDouble <
* @param _objectiveVector the objective vector to read
*/
template < class ObjectiveVectorTraits >
std::istream & operator>>(std::istream & _is, moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _objectiveVector)
std::istream & operator>> (std::istream & _is,
moeoObjectiveVectorDouble <
ObjectiveVectorTraits > &_objectiveVector)
{
_objectiveVector = moeoObjectiveVectorDouble < ObjectiveVectorTraits > ();
for (unsigned i=0; i<_objectiveVector.size(); i++)
{
_is >> _objectiveVector[i];
}
return _is;
_objectiveVector = moeoObjectiveVectorDouble < ObjectiveVectorTraits > ();
for (unsigned i = 0; i < _objectiveVector.size (); i++)
{
_is >> _objectiveVector[i];
}
return _is;
}
#endif /*MOEOOBJECTIVEVECTOR_H_*/
#endif /*MOEOOBJECTIVEVECTOR_H_ */

112
branches/paradiseo-moeo-1.0/src/moeoObjectiveVectorComparator.h
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@ -20,70 +20,74 @@
* Abstract class allowing to compare 2 objective vectors.
* The template argument ObjectiveVector have to be a moeoObjectiveVector.
*/
template < class ObjectiveVector >
class moeoObjectiveVectorComparator : public eoBF < const ObjectiveVector &, const ObjectiveVector &, int >
{};
template < class ObjectiveVector > class moeoObjectiveVectorComparator:public eoBF < const ObjectiveVector &, const ObjectiveVector &,
int >
{
};
/**
* This functor class allows to compare 2 objective vectors according to Pareto dominance.
* This functor class allows to compare 2 objective vectors according to Pareto dominance
*/
template < class ObjectiveVector >
class moeoParetoObjectiveVectorComparator : public moeoObjectiveVectorComparator < ObjectiveVector >
template < class ObjectiveVector > class moeoParetoObjectiveVectorComparator:public moeoObjectiveVectorComparator <
ObjectiveVector
>
{
public:
/**
* Returns 1 if _objectiveVector1 dominates _objectiveVector2, -1 if _objectiveVector2 dominates _objectiveVector1 and 0 if no one dominates the other
* @param _objectiveVector1 the first objective vector
* @param _objectiveVector2 the second objective vector
*/
int operator()(const ObjectiveVector & _objectiveVector1, const ObjectiveVector & _objectiveVector2)
{
bool dom1 = false;
bool dom2 = false;
for (unsigned i=0; i<ObjectiveVector::nObjectives(); i++)
{
// first, we have to check if the 2 objective values are not equal for the ith objective
if ( fabs(_objectiveVector1[i] - _objectiveVector2[i]) > ObjectiveVector::Traits::tolerance() )
{
// if the ith objective have to be minimized...
if (ObjectiveVector::minimizing(i))
{
if (_objectiveVector1[i] > _objectiveVector2[i])
{
dom2 = true; //_objectiveVector2[i] is better than _objectiveVector1[i]
}
else // _objectiveVector1[i] < _objectiveVector2[i]
{
dom1 = true; //_objectiveVector1[i] is better than _objectiveVector2[i]
}
}
// if the ith objective have to be maximized...
else if (ObjectiveVector::maximizing(i))
{
if (_objectiveVector1[i] > _objectiveVector2[i])
{
dom1 = true; //_objectiveVector1[i] is better than _objectiveVector2[i]
}
else // _objectiveVector1[i] < _objectiveVector2[i]
{
dom2 = true; //_objectiveVector2[i] is better than _objectiveVector1[i]
}
}
}
}
if (dom1 == dom2)
{
return 0; // no one dominates the other
}
if (dom1)
{
return 1; //_objectiveVector1 dominates _objectiveVector2
}
return -1; //_objectiveVector2 dominates _objectiveVector1
}
*/
int operator () (const ObjectiveVector & _objectiveVector1,
const ObjectiveVector & _objectiveVector2)
{
bool dom1 = false;
bool dom2 = false;
for (unsigned i = 0; i < ObjectiveVector::nObjectives (); i++)
{
// first, we have to check if the 2 objective values are not equal for the ith objective
if (fabs (_objectiveVector1[i] - _objectiveVector2[i]) >
ObjectiveVector::Traits::tolerance ())
{
// if the ith objective have to be minimized...
if (ObjectiveVector::minimizing (i))
{
if (_objectiveVector1[i] > _objectiveVector2[i])
{
dom2 = true; //_objectiveVector2[i] is better than _objectiveVector1[i]
}
else // _objectiveVector1[i] < _objectiveVector2[i]
{
dom1 = true; //_objectiveVector1[i] is better than _objectiveVector2[i]
}
}
// if the ith objective have to be maximized...
else if (ObjectiveVector::maximizing (i))
{
if (_objectiveVector1[i] > _objectiveVector2[i])
{
dom1 = true; //_objectiveVector1[i] is better than _objectiveVector2[i]
}
else // _objectiveVector1[i] < _objectiveVector2[i]
{
dom2 = true; //_objectiveVector2[i] is better than _objectiveVector1[i]
}
}
}
}
if (dom1 == dom2)
{
return 0; // no one dominates the other
}
if (dom1)
{
return 1; //_objectiveVector1 dominates _objectiveVector2
}
return -1; //_objectiveVector2 dominates _objectiveVector1
}
};
#endif /*MOEOOBJECTIVEVECTORCOMPARATOR_H_*/
#endif /*MOEOOBJECTIVEVECTORCOMPARATOR_H_ */

117
branches/paradiseo-moeo-1.0/src/moeoObjectiveVectorTraits.h
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@ -18,94 +18,105 @@
#include <stdexcept>
/**
* A traits class for moeoObjectiveVector to specify the number of objectives and which ones have to be minimized or maximized.
* A traits class for moeoObjectiveVector to specify the number of objectives and which ones have to be minimized or maximized
*/
class moeoObjectiveVectorTraits
{
public:
/** The tolerance value (used to compare solutions) */
const static double tol = 1e-6;
const static double tol = 1e-6;
/**
* Parameters setting
* @param _nObjectives the number of objectives
* @param _bObjectives the min/max vector (true = min / false = max)
*/
static void setup(unsigned _nObjectives, std::vector < bool > & _bObjectives)
{
// in case the number of objectives was already set to a different value
if ( nObj && (nObj != _nObjectives) ) {
std::cout << "WARNING\n";
std::cout << "WARNING : the number of objectives are changing\n";
std::cout << "ARNING : Make sure all existing objects are destroyed\n";
std::cout << "WARNING\n";
}
// number of objectives
nObj = _nObjectives;
// min/max vector
bObj = _bObjectives;
// in case the number of objectives and the min/max vector size don't match
if (nObj != bObj.size())
throw std::runtime_error("Number of objectives and min/max size don't match in moeoObjectiveVectorTraits::setup");
}
static void setup (unsigned _nObjectives,
std::vector < bool > &_bObjectives)
{
// in case the number of objectives was already set to a different value
if (nObj && (nObj != _nObjectives))
{
std::cout << "WARNING\n";
std::cout << "WARNING : the number of objectives are changing\n";
std::
cout << "WARNING : Make sure all existing objects are destroyed\n";
std::cout << "WARNING\n";
}
// number of objectives
nObj = _nObjectives;
// min/max vector
bObj = _bObjectives;
// in case the number of objectives and the min/max vector size don't match
if (nObj != bObj.size ())
throw std::
runtime_error
("Number of objectives and min/max size don't match in moeoObjectiveVectorTraits::setup");
}
/**
* Returns the number of objectives
*/
static unsigned nObjectives()
{
// in case the number of objectives would not be assigned yet
if (! nObj)
throw std::runtime_error("Number of objectives not assigned in moeoObjectiveVectorTraits");
return nObj;
}
static unsigned nObjectives ()
{
// in case the number of objectives would not be assigned yet
if (!nObj)
throw std::
runtime_error
("Number of objectives not assigned in moeoObjectiveVectorTraits");
return nObj;
}
/**
* Returns true if the _ith objective have to be minimized
* @param _i the index
*/
static bool minimizing(unsigned _i)
{
// in case the min/max vector would not be assigned yet
if (! bObj[_i])
throw std::runtime_error("We don't know if the ith objective have to be minimized or maximized in moeoObjectiveVectorTraits");
// in case there would be a wrong index
if (_i >= bObj.size())
throw std::runtime_error("Wrong index in moeoObjectiveVectorTraits");
return bObj[_i];
}
static bool minimizing (unsigned _i)
{
// in case the min/max vector would not be assigned yet
if (!bObj[_i])
throw std::
runtime_error
("We don't know if the ith objective have to be minimized or maximized in moeoObjectiveVectorTraits");
// in case there would be a wrong index
if (_i >= bObj.size ())
throw std::runtime_error ("Wrong index in moeoObjectiveVectorTraits");
return bObj[_i];
}
/**
* Returns true if the _ith objective have to be maximized
* @param _i the index
*/
static bool maximizing(unsigned _i) {
return (! minimizing(_i));
}
static bool maximizing (unsigned _i)
{
return (!minimizing (_i));
}
/**
* Returns the tolerance value (to compare solutions)
*/
static double tolerance()
{
return tol;
}
static double tolerance ()
{
return tol;
}
private:
/** The number of objectives */
static unsigned nObj;
static unsigned nObj;
/** The min/max vector */
static std::vector < bool > bObj;
static std::vector < bool > bObj;
};
#endif /*MOEOOBJECTIVEVECTORTRAITS_H_*/
#endif /*MOEOOBJECTIVEVECTORTRAITS_H_ */
// The static variables of the moeoObjectiveVectorTraits class need to be allocated
// (maybe it would have been better to put this on a moeoObjectiveVectorTraits.cpp file)
unsigned moeoObjectiveVectorTraits::nObj;
unsigned
moeoObjectiveVectorTraits::nObj;
std::vector < bool > moeoObjectiveVectorTraits::bObj;

9
branches/paradiseo-moeo-1.0/src/moeoReplacement.h
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@ -16,9 +16,10 @@
#include <eoReplacement.h>
/**
* Replacement strategy for multi-objective optimization.
* Replacement strategy for multi-objective optimization
*/
template < class MOEOT >
class moeoReplacement : public eoReplacement < MOEOT > {};
template < class MOEOT > class moeoReplacement:public eoReplacement < MOEOT >
{
};
#endif /*MOEOREPLACEMENT_H_*/
#endif /*MOEOREPLACEMENT_H_ */

7
branches/paradiseo-moeo-1.0/src/moeoSelectOne.h
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@ -16,9 +16,8 @@
#include <eoSelectOne.h>
/**
* Selection strategy for multi-objective optimization that selects only one element from a whole population.
* Selection strategy for multi-objective optimization that selects only one element from a whole population
*/
template < class MOEOT >
class moeoSelectOne : public eoSelectOne < MOEOT > {};
template < class MOEOT > class moeoSelectOne : public eoSelectOne < MOEOT > {};
#endif /*MOEOSELECTONE_H_*/
#endif /*MOEOSELECTONE_H_ */