Package org.moeaframework.algorithm.single

Class GeneticAlgorithm

java.lang.Object

org.moeaframework.algorithm.AbstractAlgorithm

org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

org.moeaframework.algorithm.single.SingleObjectiveEvolutionaryAlgorithm

org.moeaframework.algorithm.single.GeneticAlgorithm

All Implemented Interfaces:

Algorithm, Configurable, EvolutionaryAlgorithm, Stateful

public class GeneticAlgorithm
extends SingleObjectiveEvolutionaryAlgorithm

Single-objective genetic algorithm (GA) implementation with elitism. A single elite individual is retained in each generation.

References:

1. John Holland. "Adaptation in Natural and Artificial Systems." MIT Press, ISBN: 9780262082136.

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
GeneticAlgorithm(Problem problem)	Constructs a new instance of the genetic algorithm (GA) with default settings.
GeneticAlgorithm(Problem problem, int initialPopulationSize, AggregateObjectiveComparator comparator, Initialization initialization, Variation variation)	Constructs a new instance of the genetic algorithm (GA).

Method Summary

Modifier and Type	Method	Description
NondominatedPopulation	getResult()	Returns the current best-known result.
protected void	initialize()	Performs any initialization that is required by this algorithm.
void	iterate()	Performs one iteration of the algorithm.
void	loadState(ObjectInputStream stream)	Loads the state of this object from the stream.
void	setComparator(AggregateObjectiveComparator comparator)	Sets the aggregate objective comparator that scalarizes multiple objectives into a single fitness value.
void	setVariation(Variation variation)	Replaces the variation operator to be used by this algorithm.
void	updateEliteSolution()	Update the elite solution.

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

applyConfiguration, getComparator, getConfiguration, setInitialPopulationSize

Methods inherited from class org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

getArchive, getInitialization, getInitialPopulationSize, getPopulation, getVariation, saveState, setArchive, setInitialization, setPopulation

Methods inherited from class org.moeaframework.algorithm.AbstractAlgorithm

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

Constructor Details

GeneticAlgorithm

public GeneticAlgorithm(Problem problem)

Constructs a new instance of the genetic algorithm (GA) with default settings.

Parameters:

problem - the problem

GeneticAlgorithm

public GeneticAlgorithm(Problem problem,
 int initialPopulationSize,
 AggregateObjectiveComparator comparator,
 Initialization initialization,
 Variation variation)

Constructs a new instance of the genetic algorithm (GA).

Parameters:

problem - the problem

initialPopulationSize - the initial population size

comparator - the aggregate objective comparator

initialization - the initialization method

variation - the variation operator

Method Details

initialize

protected void initialize()

Description copied from class: AbstractAlgorithm

Performs any initialization that is required by this algorithm. This method is called automatically on the first invocation of AbstractAlgorithm.step(). Implementations should always invoke super.initialize() to ensure the algorithm is initialized correctly.

Overrides:

initialize in class AbstractEvolutionaryAlgorithm

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

updateEliteSolution

public void updateEliteSolution()

Update the elite solution.

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

setVariation

public void setVariation(Variation variation)

Description copied from class: AbstractEvolutionaryAlgorithm

Replaces the variation operator to be used by this algorithm.

Overrides:

setVariation in class AbstractEvolutionaryAlgorithm

Parameters:

variation - the variation operator

setComparator

public void setComparator(AggregateObjectiveComparator comparator)

Description copied from class: SingleObjectiveEvolutionaryAlgorithm

Sets the aggregate objective comparator that scalarizes multiple objectives into a single fitness value.

Overrides:

setComparator in class SingleObjectiveEvolutionaryAlgorithm

Parameters:

comparator - the aggregate objective comparator

loadState

public void loadState(ObjectInputStream stream)
               throws IOException,
ClassNotFoundException

Description copied from interface: Stateful

Loads the state of this object from the stream. The order for reading objects from the stream must match the order they are written to the stream in Stateful.saveState(ObjectOutputStream).

Specified by:

loadState in interface Stateful

Overrides:

loadState in class AbstractEvolutionaryAlgorithm

Parameters:

stream - the stream

Throws:

IOException - if an I/O error occurred

ClassNotFoundException - if the stream referenced a class that is not defined