Uses of Interface
org.cicirello.search.evo.ReplacementStrategy

Packages that use ReplacementStrategy

Package	Description
org.cicirello.search.evo	This package includes classes and interfaces directly related to implementing evolutionary algorithms.

Uses of ReplacementStrategy in org.cicirello.search.evo

Classes in org.cicirello.search.evo that implement ReplacementStrategy

Modifier and Type	Class	Description
final class	GenerationalElitistReplacement<T>	GenerationalElitistReplacement keeps the k best-fit distinct members of the current population without application of evolutionary operators, and replaces the other (N-k) members of the population.
final class	GenerationalReplacement<T>	Generational replacement replaces the entire population each generation.

Subinterfaces with type arguments of type ReplacementStrategy in org.cicirello.search.evo

Modifier and Type	Interface	Description
interface	ReplacementStrategy<T>	Implement this interface to provide a replacement strategy for use by genetic algorithms and other forms of evolutionary computation.

Methods in org.cicirello.search.evo that return ReplacementStrategy

Modifier and Type	Method	Description
ReplacementStrategy<T>	GenerationalReplacement.split()

Constructors in org.cicirello.search.evo with parameters of type ReplacementStrategy

Modifier	Constructor	Description
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalDisjointOperatorsEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalDisjointOperatorsEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalDisjointOperatorsEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalDisjointOperatorsEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm for an EA utilizing both a crossover operator and a mutation operator, such that the genetic operators follow a mutually exclusive property where each population member is involved in at most one of those operations in a single generation.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm with mutation only.
	GenerationalMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm with mutation only.
	GenerationalMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement)	Constructs and initializes the evolutionary algorithm with mutation only.
	GenerationalMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, ReplacementStrategy<T> replacement, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm with mutation only.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	GeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Integer<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement, ProgressTracker<BitVector> tracker)	Initializes a genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	MutationOnlyGeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	MutationOnlyGeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement, ProgressTracker<BitVector> tracker)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	MutationOnlyGeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	MutationOnlyGeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement, ProgressTracker<BitVector> tracker)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	MutationOnlyGeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Double<BitVector> f, double mutationRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	MutationOnlyGeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Double<BitVector> f, double mutationRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement, ProgressTracker<BitVector> tracker)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	MutationOnlyGeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Integer<BitVector> f, double mutationRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	MutationOnlyGeneticAlgorithm(int n, Initializer<BitVector> initializer, FitnessFunction.Integer<BitVector> f, double mutationRate, SelectionOperator selection, ReplacementStrategy<BitVector> replacement, ProgressTracker<BitVector> tracker)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.