org.moeaframework.algorithm
Class EpsilonProgressContinuation

java.lang.Object
  org.moeaframework.algorithm.PeriodicAction
      org.moeaframework.algorithm.AdaptiveTimeContinuation
          org.moeaframework.algorithm.EpsilonProgressContinuation

All Implemented Interfaces:

Algorithm, EvolutionaryAlgorithm

public class EpsilonProgressContinuation
extends AdaptiveTimeContinuation

Extends AdaptiveTimeContinuation to trigger restarts using ε-progress. ε-progress measures search progress by counting the number of significant improvements, as measured by the number of unoccupied ε-boxes filled during a fixed time window.

References:

1. Hadka, D. and Reed, P. "Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework." Evolutionary Computation, 21(2):231-259, 2013.

Nested Class Summary

Nested classes/interfaces inherited from class org.moeaframework.algorithm.PeriodicAction

PeriodicAction.FrequencyType

Field Summary

Fields inherited from class org.moeaframework.algorithm.PeriodicAction

algorithm, frequency, frequencyType, iteration, lastInvocation

Constructor Summary

EpsilonProgressContinuation(EpsilonBoxEvolutionaryAlgorithm algorithm, int windowSize, int maxWindowSize, double populationRatio, int minimumPopulationSize, int maximumPopulationSize, Selection selection, Variation variation)
Decorates the specified algorithm with ε-progress triggered time continuation.

Method Summary

protected RestartType	check() Performs a check to determine if a restart should occur.
EpsilonBoxDominanceArchive	getArchive() Returns the current non-dominated archive of the best solutions generated by this evolutionary algorithm, or null if no archive is used.
Serializable	getState() Returns a Serializable object representing the internal state of this algorithm.
protected void	restart(RestartType type) Performs a restart.
void	setState(Object objState) Sets the internal state of of this algorithm.

Methods inherited from class org.moeaframework.algorithm.AdaptiveTimeContinuation

addRestartListener, doAction, getPopulation, removeRestartListener

Methods inherited from class org.moeaframework.algorithm.PeriodicAction

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

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.moeaframework.core.Algorithm

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

Constructor Detail

EpsilonProgressContinuation

public EpsilonProgressContinuation(EpsilonBoxEvolutionaryAlgorithm algorithm,
                                   int windowSize,
                                   int maxWindowSize,
                                   double populationRatio,
                                   int minimumPopulationSize,
                                   int maximumPopulationSize,
                                   Selection selection,
                                   Variation variation)

Decorates the specified algorithm with ε-progress triggered time continuation.

Parameters:

algorithm - the algorithm being decorated

windowSize - the number of iterations between invocations of check

maxWindowSize - the maximum number of iterations allowed since the last restart before forcing a restart

populationRatio - the population-to-archive ratio

minimumPopulationSize - the minimum size of the population

maximumPopulationSize - the maximum size of the population

selection - the selection operator for selecting solutions from the archive during a restart

variation - the variation operator for mutating solutions selected from the archive during a restart

Method Detail

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 EvolutionaryAlgorithm

Overrides:

getArchive in class AdaptiveTimeContinuation

Returns:

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

check

protected RestartType check()

Description copied from class: AdaptiveTimeContinuation

Performs a check to determine if a restart should occur. Returns RestartType.NONE if no restart should occur; or RestartType.HARD if the population-to-archive ratio exceeds populationRatio by more than 25% or the number of fitness evaluations since the last restart exceeds maxWindowSize.

Overrides:

check in class AdaptiveTimeContinuation

Returns:

RestartType.NONE if no restart should occur; or RestartType.HARD if the population-to-archive ratio exceeds populationRatio by more than 25% or if the number of fitness evaluations since the last restart exceeds maxWindowSize

restart

protected void restart(RestartType type)

Description copied from class: AdaptiveTimeContinuation

Performs a restart. If the type is RestartType.HARD, the population is emptied, resized and filled with solutions selected and mutated from the archive. If the type is RestartType.SOFT, the population is not emptied; new solutions are only added to fill any empty slots.

Overrides:

restart in class AdaptiveTimeContinuation

Parameters:

type - the type of restart

getState

public Serializable getState()
                      throws NotSerializableException

Description copied from interface: Algorithm

Returns a Serializable object representing the internal state of this algorithm.

Specified by:

getState in interface Algorithm

Overrides:

getState in class AdaptiveTimeContinuation

Returns:

a Serializable object representing the internal state of this algorithm

Throws:

NotSerializableException - if this algorithm does not support serialization

setState

public void setState(Object objState)
              throws NotSerializableException

Description copied from interface: Algorithm

Sets the internal state of of this algorithm.

Specified by:

setState in interface Algorithm

Overrides:

setState in class AdaptiveTimeContinuation

Parameters:

objState - the internal state of this algorithm

Throws:

NotSerializableException - if this algorithm does not support serialization