Uses of Interface
org.cicirello.search.operators.MutationOperator

Packages that use MutationOperator

Package	Description
org.cicirello.search.evo	This package includes classes and interfaces directly related to implementing evolutionary algorithms.
org.cicirello.search.operators	This package includes classes and interfaces for defining various operators required by simulated annealing and other metaheuristics, such as mutation operators, along with other related classes and interfaces.
org.cicirello.search.operators.bits	This package includes classes that implement operators that create, mutate, etc, BitVectors.
org.cicirello.search.operators.integers	This package includes classes that implement operators that create, mutate, etc, integer valued representations.
org.cicirello.search.operators.permutations	This package includes classes that implement local search and evolutionary operators for permutations, such as mutation operators, crossover operators, and initializers.
org.cicirello.search.operators.reals	This package includes classes that implement operators that create, mutate, etc, the the inputs to functions with real-valued input parameters (represented with type double), such as is required to solve function optimization problems using simulated annealing or other metaheuristics.

Uses of MutationOperator in org.cicirello.search.evo

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

Modifier	Constructor	Description
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, 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)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm.
	AdaptiveEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, CrossoverOperator<T> crossover, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount, 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, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	AdaptiveMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, 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.Double<T> f, SelectionOperator selection)	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, int eliteCount)	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, int eliteCount, 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.Double<T> f, SelectionOperator selection, 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)	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, int eliteCount)	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, int eliteCount, 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, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection)	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.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount)	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.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, int eliteCount, 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.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection, 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.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection)	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.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount)	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.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, int eliteCount, 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.
	GenerationalEvolutionaryAlgorithmMutuallyExclusiveOperators(int n, MutationOperator<T> mutation, double mutationRate, CrossoverOperator<T> crossover, double crossoverRate, Initializer<T> initializer, FitnessFunction.Integer<T> f, SelectionOperator selection, 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.
	GenerationalMutationOnlyEvolutionaryAlgorithm(int n, MutationOperator<T> mutation, double mutationRate, Initializer<T> initializer, FitnessFunction.Double<T> f, SelectionOperator selection)	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, int eliteCount)	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, int eliteCount, ProgressTracker<T> tracker)	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, 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)	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, int eliteCount)	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, int eliteCount, 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, ProgressTracker<T> tracker)	Constructs and initializes the evolutionary algorithm with mutation only.

Uses of MutationOperator in org.cicirello.search.operators

Subinterfaces of MutationOperator in org.cicirello.search.operators

Modifier and Type	Interface	Description
interface	IterableMutationOperator<T>	Implement the IterableMutationOperator interface to define a mutation operator that enables iterating systematically over the neighbors of a candidate solution, like one would do in a hill climber.
interface	UndoableMutationOperator<T>	Implement the UndoableMutationOperator interface to implement a mutation operator for use in simulated annealing, and other metaheuristics, that require a way to generate random neighbors of a candidate solution, and which supports an undo method.

Classes in org.cicirello.search.operators that implement MutationOperator

Modifier and Type	Class	Description
final class	HybridMutation<T>	A HybridMutation enables using multiple mutation operators for the search, such that each time the HybridMutation.mutate(T) method is called, a randomly chosen mutation operator is applied to the candidate solution.
final class	HybridUndoableMutation<T>	A HybridMutation enables using multiple mutation operators for the search, such that each time the HybridUndoableMutation.mutate(T) method is called, a randomly chosen mutation operator is applied to the candidate solution.
final class	WeightedHybridMutation<T>	A WeightedHybridMutation enables using multiple mutation operators for the search, such that each time the WeightedHybridMutation.mutate(T) method is called, a randomly chosen mutation operator is applied to the candidate solution.
final class	WeightedHybridUndoableMutation<T>	A WeightedHybridMutation enables using multiple mutation operators for the search, such that each time the WeightedHybridUndoableMutation.mutate(T) method is called, a randomly chosen mutation operator is applied to the candidate solution.

Constructor parameters in org.cicirello.search.operators with type arguments of type MutationOperator

Modifier	Constructor	Description
	HybridMutation(Collection<? extends MutationOperator<T>> mutationOps)	Constructs a HybridMutation from a Collection of MutationOperators.
	WeightedHybridMutation(Collection<? extends MutationOperator<T>> mutationOps, int[] weights)	Constructs a WeightedHybridMutation from a Collection of MutationOperators.

Uses of MutationOperator in org.cicirello.search.operators.bits

Classes in org.cicirello.search.operators.bits that implement MutationOperator

Modifier and Type	Class	Description
final class	BitFlipMutation	This class implements Bit Flip Mutation, the mutation operator commonly used in genetic algorithms, but which can also be used with other metaheuristic search algorithms such as simulated annealing to generate random neighbors.
final class	DefiniteBitFlipMutation	DefiniteBitFlipMutation implements a variation of Bit Flip Mutation.

Uses of MutationOperator in org.cicirello.search.operators.integers

Classes in org.cicirello.search.operators.integers that implement MutationOperator

Modifier and Type	Class	Description
class	RandomValueChangeMutation<T extends IntegerValued>	This mutation operator is for integer valued representations, and replaces an integer value with a different random integer value from the domain.
final class	UndoableRandomValueChangeMutation<T extends IntegerValued>	This mutation operator (supporting the undo operation) is for integer valued representations, and replaces an integer value with a different random integer value from the domain.
class	UndoableUniformMutation<T extends IntegerValued>	This class implements a uniform mutation with support for the UndoableMutationOperator.undo(T) method.
class	UniformMutation<T extends IntegerValued>	This class implements a uniform mutation.

Uses of MutationOperator in org.cicirello.search.operators.permutations

Classes in org.cicirello.search.operators.permutations that implement MutationOperator

Modifier and Type	Class	Description
final class	AdjacentSwapMutation	This class implements an adjacent swap mutation on permutations, where one mutation consists in randomly swapping a pair of adjacent elements.
final class	BlockInterchangeMutation	This class implements a block interchange mutation on permutations, where one mutation consists in swapping two randomly chosen non-overlapping "blocks" (i.e., subsequences).
final class	BlockMoveMutation	This class implements a block move mutation on permutations, where one mutation consists in removing a randomly chosen "block" (i.e., subsequence) and reinserting it at a different randomly chosen index.
final class	CycleAlphaMutation	This class implements the Cycle(α) form of cycle mutation on permutations, where one mutation generates a random permutation cycle.
final class	CycleMutation	This class implements the Cycle(kmax) form of cycle mutation on permutations, where one mutation generates a random permutation cycle.
final class	InsertionMutation	This class implements an insertion mutation on permutations, where one mutation consists in removing a randomly chosen element and reinserting it at a different randomly chosen location.
final class	ReversalMutation	This class implements a reversal mutation on permutations, where one mutation consists in reversing the order of a randomly selected subpermutation.
final class	RotationMutation	This class implements a rotation mutation on permutations, where one mutation consists in a random circular rotation of the permutation.
final class	ScrambleMutation	This class implements a scramble mutation on permutations, where one mutation consists in randomizing the order of a randomly selected subpermutation.
final class	SwapMutation	This class implements a swap mutation on permutations, where one mutation selects two elements uniformly at random and swaps their locations.
final class	ThreeOptMutation	This class implements the classic 3-Opt neighborhood as a mutation operator for permutations.
final class	TwoChangeMutation	This class implements the classic two-change operator as a mutation operator for permutations.
final class	UndoableScrambleMutation	This class implements a scramble mutation on permutations, where one mutation consists in randomizing the order of a randomly selected subpermutation.
final class	UndoableUniformScrambleMutation	This class implements a scramble mutation on permutations, where one mutation consists in randomizing the order of a non-contiguous subset of the permutation elements.
final class	UniformScrambleMutation	This class implements a scramble mutation on permutations, where one mutation consists in randomizing the order of a non-contiguous subset of the permutation elements.
final class	WindowLimitedBlockMoveMutation	This class implements a window-limited version of the BlockMoveMutation mutation operator on permutations.
final class	WindowLimitedInsertionMutation	This class implements a window-limited version of the InsertionMutation mutation operator on permutations.
final class	WindowLimitedReversalMutation	This class implements a window-limited version of the ReversalMutation mutation operator on permutations.
final class	WindowLimitedScrambleMutation	This class implements a window-limited version of the ScrambleMutation mutation operator on permutations.
final class	WindowLimitedSwapMutation	This class implements a window-limited version of the SwapMutation mutation operator on permutations.
final class	WindowLimitedUndoableScrambleMutation	This class implements a window-limited version of the ScrambleMutation mutation operator on permutations.

Uses of MutationOperator in org.cicirello.search.operators.reals

Classes in org.cicirello.search.operators.reals that implement MutationOperator

Modifier and Type	Class	Description
class	CauchyMutation<T extends RealValued>	This class implements Cauchy mutation.
class	GaussianMutation<T extends RealValued>	This class implements Gaussian mutation.
class	UndoableCauchyMutation<T extends RealValued>	This class implements Cauchy mutation with support for the UndoableMutationOperator.undo(T) method.
final class	UndoableGaussianMutation<T extends RealValued>	This class implements Gaussian mutation with support for the UndoableMutationOperator.undo(T) method.
class	UndoableUniformMutation<T extends RealValued>	This class implements a uniform mutation with support for the UndoableMutationOperator.undo(T) method.
class	UniformMutation<T extends RealValued>	This class implements a uniform mutation.