Package org.moeaframework.core.indicator

Class WFGNormalizedHypervolume

java.lang.Object

org.moeaframework.core.indicator.NormalizedIndicator

org.moeaframework.core.indicator.WFGNormalizedHypervolume

All Implemented Interfaces:

Indicator

public class WFGNormalizedHypervolume
extends NormalizedIndicator

Fast hypervolume calculation published by the Walking Fish Group (WFG). This version is normalized by the bounds of a reference set.

References:

1. While, Ronald Lyndon et al. “A Fast Way of Calculating Exact Hypervolumes.” IEEE Transactions on Evolutionary Computation 16 (2012): 86-95.

Field Summary

Fields inherited from class org.moeaframework.core.indicator.NormalizedIndicator

problem

Constructor Summary

Constructors

Constructor	Description
WFGNormalizedHypervolume(Problem problem, Normalizer normalizer)	Constructs a hypervolume evaluator for the specified problem using the given normalizer.
WFGNormalizedHypervolume(Problem problem, NondominatedPopulation referenceSet)	Constructs a hypervolume evaluator for the specified problem and reference set.

Method Summary

Modifier and Type	Method	Description
double	evaluate(NondominatedPopulation approximationSet)	Returns the value of this unary quality indicator given the specified non-dominated population.

Methods inherited from class org.moeaframework.core.indicator.NormalizedIndicator

getNormalizedReferenceSet, normalize

Methods inherited from class java.lang.Object

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

Constructor Details

WFGNormalizedHypervolume

public WFGNormalizedHypervolume(Problem problem,
 NondominatedPopulation referenceSet)

Constructs a hypervolume evaluator for the specified problem and reference set. See DefaultNormalizer for details on configuring normalization.

Parameters:

problem - the problem

referenceSet - the reference set

WFGNormalizedHypervolume

public WFGNormalizedHypervolume(Problem problem,
 Normalizer normalizer)

Constructs a hypervolume evaluator for the specified problem using the given normalizer.

Parameters:

problem - the problem

normalizer - a user-provided normalizer

Method Details

evaluate

public double evaluate(NondominatedPopulation approximationSet)

Description copied from interface: Indicator

Returns the value of this unary quality indicator given the specified non-dominated population.

Parameters:

approximationSet - the non-dominated population to be evaluated

Returns:

the value of this quality indicator given the specified non-dominated population