org.moeaframework.algorithm
Class IBEA

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

All Implemented Interfaces:

Algorithm, EvolutionaryAlgorithm

public class IBEA
extends AbstractEvolutionaryAlgorithm

Implementation of the Indicator-Based Evolutionary Algorithm (IBEA). Instead of using Pareto dominance to evaluate the quality of solutions, IBEA uses an indicator function (typically hypervolume but other indicator functions can be specified).

References:

1. Zitzler, E. and S. Kunzli (2004). Indicator-Based Selection in Multiobjective Search. Parallel Problem Solving from Nature (PPSN VIII), pp. 832-842.

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

IBEA(Problem problem, NondominatedPopulation archive, Initialization initialization, Variation variation, IndicatorFitnessEvaluator fitnessEvaluator)
Constructs a new IBEA instance.

Method Summary

protected void	initialize() Performs any initialization that is required by this algorithm.
protected void	iterate() Performs one iteration of the algorithm.

Methods inherited from class org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

getArchive, getPopulation, getResult, getState, 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.Algorithm

evaluate, getNumberOfEvaluations, getProblem, isTerminated, step, terminate

Constructor Detail

IBEA

public IBEA(Problem problem,
            NondominatedPopulation archive,
            Initialization initialization,
            Variation variation,
            IndicatorFitnessEvaluator fitnessEvaluator)

Constructs a new IBEA instance.

Parameters:

problem - the problem

archive - the external archive; or null if no external archive is used

initialization - the initialization operator

variation - the variation operator

fitnessEvaluator - the indicator fitness evaluator to use (e.g., hypervolume additive-epsilon indicator)

Method Detail

initialize

protected void initialize()

Description copied from class: AbstractAlgorithm

Performs any initialization that is required by this algorithm. This method is called automatically by the first invocation of AbstractAlgorithm.step(), but may also be called manually prior to any invocations of step. Implementations should always invoke super.initialize() to ensure the hierarchy is initialized correctly.

Overrides:

initialize in class AbstractEvolutionaryAlgorithm

iterate

protected 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