io.jenetics

Class RouletteWheelSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>

java.lang.Object

io.jenetics.ProbabilitySelector<G,N>

io.jenetics.RouletteWheelSelector<G,N>

All Implemented Interfaces:

Selector<G,N>

Direct Known Subclasses:

StochasticUniversalSelector

public class RouletteWheelSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>
extends ProbabilitySelector<G,N>

The roulette-wheel selector is also known as fitness proportional selector, but in the Jenetics library it is implemented as probability selector. The fitness value f_i is used to calculate the selection probability of individual i.

Since:

1.0

Version:

5.0

Author:

Franz Wilhelmstötter

See Also:

Wikipedia: Roulette wheel selection

Field Summary

Fields inherited from class io.jenetics.ProbabilitySelector

_reverter, _sorted, POPULATION_COMPARATOR

Constructor Summary

Constructors

Modifier	Constructor and Description
	RouletteWheelSelector()
protected	RouletteWheelSelector(boolean sorted)

Method Summary

Modifier and Type	Method and Description
protected double[]	probabilities(Seq<Phenotype<G,N>> population, int count) Return an Probability array, which corresponds to the given Population.
String	toString()

Methods inherited from class io.jenetics.ProbabilitySelector

probabilities, select

Methods inherited from class java.lang.Object

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

Constructor Detail

RouletteWheelSelector

public RouletteWheelSelector()

RouletteWheelSelector

protected RouletteWheelSelector(boolean sorted)

Method Detail

probabilities

protected double[] probabilities(Seq<Phenotype<G,N>> population,
                                 int count)

Description copied from class: ProbabilitySelector

Return an Probability array, which corresponds to the given Population. The probability array and the population must have the same size. The population is not sorted. If a subclass needs a sorted population, the subclass is responsible to sort the population.

The implementer always assumes that higher fitness values are better. The base class inverts the probabilities, by reverting the returned probability array, if the GA is supposed to minimize the fitness function.

Specified by:

probabilities in class ProbabilitySelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>

Parameters:

population - The unsorted population.

count - The number of phenotypes to select. This parameter is not needed for most implementations.

Returns:

Probability array. The returned probability array must have the length population.size() and must sum to one. The returned value is checked with assert(Math.abs(math.sum(probabilities) - 1.0) < 0.0001) in the base class.

toString

public String toString()

Overrides:

toString in class Object