Package org.moeaframework.algorithm.single

Class DifferentialEvolution

java.lang.Object

org.moeaframework.algorithm.AbstractAlgorithm

org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

org.moeaframework.algorithm.single.SingleObjectiveEvolutionaryAlgorithm

org.moeaframework.algorithm.single.DifferentialEvolution

All Implemented Interfaces:

Extensible, Algorithm, Configurable, EvolutionaryAlgorithm, Stateful

public class DifferentialEvolution
extends SingleObjectiveEvolutionaryAlgorithm

Single-objective differential evolution (DE) algorithm.

References:

1. Rainer Storn and Kenneth Price. "Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces." Journal of Global Optimization, 11(4):341-359, 1997.

Field Summary

Fields inherited from class org.moeaframework.algorithm.single.SingleObjectiveEvolutionaryAlgorithm

comparator

Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm

initialized, numberOfEvaluations, problem, terminated

Constructor Summary

Constructors

Constructor	Description
DifferentialEvolution(Problem problem)	Constructs a new single-objective differential evolution algorithm with default settings.
DifferentialEvolution(Problem problem, int initialPopulationSize, AggregateObjectiveComparator comparator, Initialization initialization, DifferentialEvolutionSelection selection, DifferentialEvolutionVariation variation)	Constructs a new instance of the single-objective differential evolution (DE) algorithm.

Method Summary

Modifier and Type	Method	Description
NondominatedPopulation	getResult()	Returns the current best-known result.
DifferentialEvolutionVariation	getVariation()	Returns the variation operator currently in use by this algorithm.
protected void	iterate()	Performs one iteration of the algorithm.
void	setVariation(DifferentialEvolutionVariation variation)	Replaces the variation operator to be used by this algorithm.

Methods inherited from class org.moeaframework.algorithm.single.SingleObjectiveEvolutionaryAlgorithm

applyConfiguration, getComparator, getConfiguration, setComparator, setInitialPopulationSize

Methods inherited from class org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

getArchive, getInitialization, getInitialPopulationSize, getPopulation, initialize, loadState, saveState, setArchive, setInitialization, setPopulation, setVariation

Methods inherited from class org.moeaframework.algorithm.AbstractAlgorithm

assertNotInitialized, evaluate, getExtensions, getNumberOfEvaluations, getProblem, isInitialized, 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, evaluateAll, evaluateAll, getNumberOfEvaluations, getProblem, isInitialized, isTerminated, run, run, step, terminate

Methods inherited from interface org.moeaframework.algorithm.extension.Extensible

addExtension, getExtensions, removeExtension

Constructor Details

DifferentialEvolution

public DifferentialEvolution(Problem problem)

Constructs a new single-objective differential evolution algorithm with default settings.

Parameters:

problem - the problem

DifferentialEvolution

public DifferentialEvolution(Problem problem,
 int initialPopulationSize,
 AggregateObjectiveComparator comparator,
 Initialization initialization,
 DifferentialEvolutionSelection selection,
 DifferentialEvolutionVariation variation)

Constructs a new instance of the single-objective differential evolution (DE) algorithm.

Parameters:

problem - the problem

initialPopulationSize - the initial population size

comparator - the aggregate objective comparator

initialization - the initialization method

selection - the differential evolution selection operator

variation - the differential evolution variation operator

Method Details

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

getResult

public NondominatedPopulation getResult()

Description copied from interface: Algorithm

Returns the current best-known result.

Specified by:

getResult in interface Algorithm

Overrides:

getResult in class SingleObjectiveEvolutionaryAlgorithm

Returns:

the current best-known result

getVariation

public DifferentialEvolutionVariation getVariation()

Description copied from class: AbstractEvolutionaryAlgorithm

Returns the variation operator currently in use by this algorithm.

Overrides:

getVariation in class AbstractEvolutionaryAlgorithm

Returns:

the variation operator

setVariation

public void setVariation(DifferentialEvolutionVariation variation)

Replaces the variation operator to be used by this algorithm.

Parameters:

variation - the variation operator