## Package org.apache.commons.math.genetics

This package provides Genetic Algorithms components and implementations.

See:
Description

Interface Summary
CrossoverPolicy: Policy used to create a pair of new chromosomes by performing a crossover operation on a source pair of chromosomes.
Fitness: Fitness of a chromosome.
MutationPolicy: Algorithm used to mutate a chrommosome.
PermutationChromosome<T>: Interface indicating that the chromosome represents a permutation of objects.
Population: A collection of chromosomes that facilitates generational evolution.
SelectionPolicy: Algorithm used to select a chromosome pair from a population.
StoppingCondition: Algorithm used to determine when to stop evolution.

Class Summary
AbstractListChromosome<T>: Chromosome represented by an immutable list of a fixed length.
BinaryChromosome: Chromosome represented by a vector of 0s and 1s.
BinaryMutation: Mutation for `BinaryChromosome`s.
Chromosome: Individual in a population.
ChromosomePair: A pair of `Chromosome` objects.
ElitisticListPopulation: Population of chromosomes which uses elitism (certain percentace of the best chromosomes is directly copied to the next generation).
FixedGenerationCount: Stops after a fixed number of generations.
GeneticAlgorithm: Implementation of a genetic algorithm.
ListPopulation: Population of chromosomes represented by a `List`.
OnePointCrossover<T>: One point crossover policy.
RandomKey<T>: Random Key chromosome is used for permutation representation.
RandomKeyMutation: Mutation operator for `RandomKey`s.
TournamentSelection: Tournament selection scheme.

Exception Summary
InvalidRepresentationException: Exception indicating that the representation of a chromosome is not valid.

## Package org.apache.commons.math.genetics Description

This package provides Genetic Algorithms components and implementations.

Copyright (c) 2003-2013 Apache Software Foundation