Package org.opt4j.optimizer.ea

Class ElitismSelector

java.lang.Object

org.opt4j.optimizer.ea.ElitismSelector

All Implemented Interfaces:

Selector

public class ElitismSelector
extends Object
implements Selector

The ElitismSelector is a single objective elitism select. If a multi-objective problem is optimized, the objectives are summed up to a single value.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
protected class	ElitismSelector.FitnessComparator	Comparator that sorts the Individuals based on their fitness values.

Field Summary

Fields

Modifier and Type	Field	Description
protected Map<Individual,Double>	fitness
protected Random	random

Constructor Summary

Constructors

Constructor	Description
ElitismSelector(Rand random)	Constructs an ElitismSelector.

Method Summary

Modifier and Type	Method	Description
protected void	calculateFitness(Collection<Individual> population)	Calculates the fitness of the Individuals: the sum of all double values (these always have to be minimized) of the objectives.
Collection<Individual>	getLames(int lambda, Collection<Individual> population)	Selects a subset of lambda Individuals and returns it as a new Collection.
Collection<Individual>	getParents(int mu, Collection<Individual> population)	Selects a subset of Individuals and returns it as a new Collection.
void	init(int maxsize)	Sets the maximal number of Individuals.

Methods inherited from class java.lang.Object

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

Field Detail

random

protected final Random random

fitness

protected final Map<Individual,Double> fitness

Constructor Detail

ElitismSelector

@Inject
public ElitismSelector(Rand random)

Constructs an ElitismSelector.

Parameters:

random - the random number generator

Method Detail

getLames

public Collection<Individual> getLames(int lambda,
                                       Collection<Individual> population)

Description copied from interface: Selector

Selects a subset of lambda Individuals and returns it as a new Collection. These individuals can be erased in the next generation.

Specified by:

getLames in interface Selector

Parameters:

lambda - the number of lames to select

population - the list of individuals

Returns:

the worst lambda individuals

getParents

public Collection<Individual> getParents(int mu,
                                         Collection<Individual> population)

Description copied from interface: Selector

Selects a subset of Individuals and returns it as a new Collection. These so called parents can be used to form the next generation.

Specified by:

getParents in interface Selector

Parameters:

mu - the number of parents to select

population - the list of individuals

Returns:

the parents

calculateFitness

protected void calculateFitness(Collection<Individual> population)

Calculates the fitness of the Individuals: the sum of all double values (these always have to be minimized) of the objectives.

Parameters:

population -

init

public void init(int maxsize)

Description copied from interface: Selector

Sets the maximal number of Individuals.

Specified by:

init in interface Selector

Parameters:

maxsize - the number of individuals