Package org.jgap.impl

Provides stock implementations of the various sub-components that can be plugged-in or custom implemented.

See:
Description

Class Summary

AveragingCrossoverOperator	The averaging crossover operator randomly selects two Chromosomes from the population and "mates" them by randomly picking a gene and then swapping that gene and all subsequent genes between the two Chromosomes.
BestChromosomesSelector	Implementation of a NaturalSelector that takes the top n chromosomes into the next generation. n can be specified.
BooleanGene	A Gene implementation that supports two possible values (alleles) for each gene: true and false.
BulkFitnessOffsetRemover	Takes away the fitness offset of the population to evolve.
CauchyRandomGenerator	Cauchy probability density function (cumulative distribution function).
ChainOfSelectors	Ordered chain of NaturalSelectors.
ChromosomePool	Provides a pooling mechanism for Chromosome instances so that discarded Chromosome instances can be recycled, thus saving memory and the overhead of constructing new ones from scratch each time.
CompositeGene	Ordered container for multiple genes Has the same interface as a single gene and could be used accordingly.
CrossoverOperator	The crossover operator randomly selects two Chromosomes from the population and "mates" them by randomly picking a gene and then swapping that gene and all subsequent genes between the two Chromosomes.
DefaultCloneHandler	Default clone handler supporting IApplicationData as well as implementations of Cloneable (for the latter: in case the clone-method is accessible via reflection).
DefaultCompareToHandler	Default implementation for comparing Comparables.
DefaultConfiguration	The DefaultConfiguration class simplifies the JGAP configuration process by providing default configuration values for many of the configuration settings.
DefaultCrossoverRateCalculator	Default implementation of a dynamic CrossoverRateCalculator.
DefaultInitializer	Default implementation for initializing Chromosomes.
DefaultMutationRateCalculator	Default implementation of a mutation rate calculcator.
DoubleGene	A Gene implementation that supports a double values for its allele.
FittestPopulationMerger	A implementation of the IPopulationMerger interface that merges two populations as specified based on the fitness function, that is, the n fittest chromosomes are returned in the new population, where n is supplied by parameter.
FixedBinaryGene	A Gene implementation that supports two possible values (alleles, 1 and 0) with a fixed length of alleles.
GABreeder	Breeder for genetic algorithms.
GaussianMutationOperator	This genetic operator performs Gaussian mutation across all genes in a Chromosome.
GaussianRandomGenerator	Gaussian deviation serving as basis for randomly finding a number.
GreedyCrossover	The Greedy Crossover is a specific type of crossover.
IntegerGene	A Gene implementation that supports an integer values for its allele.
InversionOperator	The inversion operator randomly selects one chromosomes from the population and inverses it by randomly picking a splitting locus on which to swap the first part with the last part of the chromosome.
JGAPFactory	Central factory for creating default objects to use, e.g. random generators.
MapGene	Creates a gene instance in which individual alleles have both a label (key) and a value with a distinct meaning.
MutationOperator	The mutation operator runs through the genes in each of the Chromosomes in the population and mutates them in statistical accordance to the given mutation rate.
MutipleIntegerGene	Extension of IntegerGene.
NumberGene	Base class for all Genes based on numbers.
Pool	A simple, generic pool class that can be used to pool any kind of object.
RangedSwappingMutationOperator	Swaps the genes instead of mutating them.
SeededRandomGenerator	The seeded random generator uses the java.util.Random class to provide a simple implementation of the RandomGenerator interface with a custom seed number for repeatable results.
SetGene	ATTENTION: This class is preliminary and subject of future adaptations!
StandardPostSelector	Implementation of a NaturalSelector that is suited for being processed after genetic operators have been executed.
StockRandomGenerator	The stock random generator uses the java.util.Random class to provide a simple implementation of the RandomGenerator interface.
StringGene	A Gene implementation that supports a string for its allele.
SwappingMutationOperator	Swaps the genes instead of mutating them.
ThresholdSelector	Implementation of a NaturalSelector that ensures a certain threshold of the best chromosomes are taken to the next generation.
TournamentSelector	Implementation of a NaturalSelector that plays tournaments to determine the chromosomes to be taken to the next generation.
TwoWayMutationOperator	Considers two levels of mutation.
WeightedRouletteSelector	A basic implementation of NaturalSelector that models a roulette wheel.

Package org.jgap.impl Description

Provides stock implementations of the various sub-components that can be plugged-in or custom implemented.