moeoFastNonDominatedSortingFitnessAssignment< MOEOT > Class Template Reference

Fitness assignment sheme based on Pareto-dominance count proposed in: N. More...

#include <moeoFastNonDominatedSortingFitnessAssignment.h>

Inheritance diagram for moeoFastNonDominatedSortingFitnessAssignment< MOEOT >:

List of all members.

Public Types
typedef MOEOT::ObjectiveVector	ObjectiveVector
	the objective vector type of the solutions
Public Member Functions
	moeoFastNonDominatedSortingFitnessAssignment ()
	Default ctor.
	moeoFastNonDominatedSortingFitnessAssignment (moeoObjectiveVectorComparator< ObjectiveVector > &_comparator)
	Ctor where you can choose your own way to compare objective vectors.
void	operator() (eoPop< MOEOT > &_pop)
	Sets the fitness values for every solution contained in the population _pop.
void	updateByDeleting (eoPop< MOEOT > &_pop, ObjectiveVector &_objVec)
	Warning: NOT IMPLEMENTED, DO NOTHING ! Updates the fitness values of the whole population _pop by taking the deletion of the objective vector _objVec into account.
Private Member Functions
void	oneObjective (eoPop< MOEOT > &_pop)
	Sets the fitness values for mono-objective problems.
void	twoObjectives (eoPop< MOEOT > &_pop)
	Sets the fitness values for bi-objective problems with a complexity of O(n log n), where n stands for the population size.
void	mObjectives (eoPop< MOEOT > &_pop)
	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.
Private Attributes
moeoObjectiveVectorComparator< ObjectiveVector > &	comparator
	Functor to compare two objective vectors.
moeoParetoObjectiveVectorComparator< ObjectiveVector >	paretoComparator
	Functor to compare two objective vectors according to Pareto dominance relation.

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Detailed Description

template<class MOEOT>
class moeoFastNonDominatedSortingFitnessAssignment< MOEOT >

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.

Definition at line 29 of file moeoFastNonDominatedSortingFitnessAssignment.h.

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Constructor & Destructor Documentation

template<class MOEOT>

moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::moeoFastNonDominatedSortingFitnessAssignment

(

moeoObjectiveVectorComparator< ObjectiveVector > &

_comparator

)

[inline]

Ctor where you can choose your own way to compare objective vectors.

Parameters:

_comparator

the functor used to compare objective vectors

Definition at line 48 of file moeoFastNonDominatedSortingFitnessAssignment.h.

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Member Function Documentation

template<class MOEOT>

void moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::operator()

(

eoPop< MOEOT > &

_pop

)

[inline, virtual]

Sets the fitness values for every solution contained in the population _pop.

Parameters:

_pop

the population

Implements eoUF< eoPop< MOEOT > &, void >.

Definition at line 56 of file moeoFastNonDominatedSortingFitnessAssignment.h.

References moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::mObjectives(), and moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::oneObjective().

template<class MOEOT>

void moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::updateByDeleting	(	eoPop< MOEOT > &	_pop,
		ObjectiveVector &	_objVec
	)			[inline, virtual]

Warning:

NOT IMPLEMENTED, DO NOTHING ! Updates the fitness values of the whole population _pop by taking the deletion of the objective vector _objVec into account.

Parameters:

	_pop	the population
	_objVec	the objective vector

Warning:

NOT IMPLEMENTED, DO NOTHING !

Implements moeoFitnessAssignment< MOEOT >.

Definition at line 100 of file moeoFastNonDominatedSortingFitnessAssignment.h.

template<class MOEOT>

void moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::oneObjective

(

eoPop< MOEOT > &

_pop

)

[inline, private]

Sets the fitness values for mono-objective problems.

Parameters:

_pop

the population

Definition at line 120 of file moeoFastNonDominatedSortingFitnessAssignment.h.

Referenced by moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::operator()().

template<class MOEOT>

void moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::twoObjectives

(

eoPop< MOEOT > &

_pop

)

[inline, private]

Sets the fitness values for bi-objective problems with a complexity of O(n log n), where n stands for the population size.

Parameters:

_pop

the population

Definition at line 136 of file moeoFastNonDominatedSortingFitnessAssignment.h.

template<class MOEOT>

void moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::mObjectives

(

eoPop< MOEOT > &

_pop

)

[inline, private]

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.

Parameters:

_pop

the population

Definition at line 146 of file moeoFastNonDominatedSortingFitnessAssignment.h.

References moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::comparator.

Referenced by moeoFastNonDominatedSortingFitnessAssignment< MOEOT >::operator()().

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The documentation for this class was generated from the following file:

• moeoFastNonDominatedSortingFitnessAssignment.h

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