org.moeaframework.algorithm
Class EpsilonMOEA

java.lang.Object
  org.moeaframework.algorithm.AbstractAlgorithm
      org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm
          org.moeaframework.algorithm.EpsilonMOEA

All Implemented Interfaces:

Algorithm, EpsilonBoxEvolutionaryAlgorithm, EvolutionaryAlgorithm

public class EpsilonMOEA
extends AbstractEvolutionaryAlgorithm
implements EpsilonBoxEvolutionaryAlgorithm

Implementation of the ε-MOEA algorithm. The ε-MOEA is a steady-state algorithm, meaning only one individual in the population is evolved per step, and uses an ε-dominance archive to maintain a well-spread set of Pareto-optimal solutions.

References:

1. Deb et al. "A Fast Multi-Objective Evolutionary Algorithm for Finding Well-Spread Pareto-Optimal Solutions." KanGAL Report No 2003002. Feb 2003.

Field Summary

Fields inherited from class org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

archive, initialization, population

Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm

initialized, numberOfEvaluations, problem, terminated

Constructor Summary

EpsilonMOEA(Problem problem, Population population, EpsilonBoxDominanceArchive archive, Selection selection, Variation variation, Initialization initialization)
Constructs the ε-MOEA algorithm with the specified components.

EpsilonMOEA(Problem problem, Population population, EpsilonBoxDominanceArchive archive, Selection selection, Variation variation, Initialization initialization, DominanceComparator dominanceComparator)
Constructs the ε-MOEA algorithm with the specified components.

Method Summary

protected void	addToPopulation(Solution newSolution) Adds the new solution to the population if is non-dominated with the current population, removing either a randomly-selected dominated solution or a non-dominated solution.
EpsilonBoxDominanceArchive	getArchive() Returns the current non-dominated archive of the best solutions generated by this evolutionary algorithm, or null if no archive is used.
void	iterate() Performs one iteration of the algorithm.

Methods inherited from class org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

getPopulation, getResult, getState, initialize, setState

Methods inherited from class org.moeaframework.algorithm.AbstractAlgorithm

evaluate, evaluateAll, evaluateAll, finalize, getNumberOfEvaluations, getProblem, isInitialized, isTerminated, step, terminate

Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.moeaframework.core.EvolutionaryAlgorithm

getPopulation

Methods inherited from interface org.moeaframework.core.Algorithm

evaluate, getNumberOfEvaluations, getProblem, getResult, getState, isTerminated, setState, step, terminate

Constructor Detail

EpsilonMOEA

public EpsilonMOEA(Problem problem,
                   Population population,
                   EpsilonBoxDominanceArchive archive,
                   Selection selection,
                   Variation variation,
                   Initialization initialization)

Constructs the ε-MOEA algorithm with the specified components.

Parameters:

problem - the problem being solved

population - the population used to store solutions

archive - the archive used to store the result

selection - the selection operator

variation - the variation operator

initialization - the initialization method

EpsilonMOEA

public EpsilonMOEA(Problem problem,
                   Population population,
                   EpsilonBoxDominanceArchive archive,
                   Selection selection,
                   Variation variation,
                   Initialization initialization,
                   DominanceComparator dominanceComparator)

Constructs the ε-MOEA algorithm with the specified components.

Parameters:

problem - the problem being solved

population - the population used to store solutions

archive - the archive used to store the result

selection - the selection operator

variation - the variation operator

initialization - the initialization method

dominanceComparator - the dominance comparator used by the addToPopulation(org.moeaframework.core.Solution) method

Method Detail

iterate

public void iterate()

Description copied from class: AbstractAlgorithm

Performs one iteration of the algorithm. This method should be overridden by implementations to perform each logical iteration of the algorithm.

Specified by:

iterate in class AbstractAlgorithm

addToPopulation

protected void addToPopulation(Solution newSolution)

Adds the new solution to the population if is non-dominated with the current population, removing either a randomly-selected dominated solution or a non-dominated solution.

Parameters:

newSolution - the new solution being added to the population

getArchive

public EpsilonBoxDominanceArchive getArchive()

Description copied from interface: EvolutionaryAlgorithm

Returns the current non-dominated archive of the best solutions generated by this evolutionary algorithm, or null if no archive is used.

Specified by:

getArchive in interface EpsilonBoxEvolutionaryAlgorithm

Specified by:

getArchive in interface EvolutionaryAlgorithm

Overrides:

getArchive in class AbstractEvolutionaryAlgorithm

Returns:

the current non-dominated archive of the best solutions generated by this evolutionary algorithm, or null if no archive is used