Uses of Class
org.cicirello.search.representations.BitVector

Packages that use BitVector

Package	Description
org.cicirello.search.evo	This package includes classes and interfaces directly related to implementing evolutionary algorithms.
org.cicirello.search.operators.bits	This package includes classes that implement operators that create, mutate, etc, BitVectors.
org.cicirello.search.problems	Package of classes and interfaces related to representing computational problems, as well as classes implementing a variety of specific computational problems.
org.cicirello.search.representations	This package includes classes related to representing solutions to optimization problems.

Uses of BitVector in org.cicirello.search.evo

Constructor parameters in org.cicirello.search.evo with type arguments of type BitVector

Modifier	Constructor	Description
	GeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection)	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)	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, int eliteCount)	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, int eliteCount)	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, int eliteCount, 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.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount, 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.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, int eliteCount, 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.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, 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.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, 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.Double<BitVector> f, double mutationRate, CrossoverOperator<BitVector> crossover, double crossoverRate, SelectionOperator selection, 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)	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)	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, int eliteCount)	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, int eliteCount)	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, int eliteCount, 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, int eliteCount, 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, int eliteCount, 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, 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, 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, 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)	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)	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)	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, int eliteCount)	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, int eliteCount)	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, int eliteCount)	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, int eliteCount, 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, int eliteCount, 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, int eliteCount, 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, int eliteCount, 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, 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, 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, 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, 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)	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)	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)	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, int eliteCount)	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, int eliteCount)	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, int eliteCount)	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, int eliteCount, 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, int eliteCount, 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, int eliteCount, 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, int eliteCount, 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, 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, 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, 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, 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)	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, int eliteCount)	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, int eliteCount, 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.Double<BitVector> f, double mutationRate, SelectionOperator selection, int eliteCount, 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.Double<BitVector> f, double mutationRate, SelectionOperator selection, 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.Double<BitVector> f, double mutationRate, SelectionOperator selection, 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)	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, int eliteCount)	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, int eliteCount, 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, int eliteCount, 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, 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, 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)	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)	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, int eliteCount)	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, int eliteCount)	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, int eliteCount, 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, int eliteCount, 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, int eliteCount, 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, 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, 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, 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)	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)	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, int eliteCount)	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, int eliteCount)	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, int eliteCount, 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, int eliteCount, 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, int eliteCount, 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, 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, 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, ProgressTracker<BitVector> tracker)	Initializes a mutation-only genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation.
	OnePlusOneGeneticAlgorithm(IntegerCostOptimizationProblem<BitVector> problem, double m, int bitLength)	Creates a OnePlusOneGeneticAlgorithm instance for integer-valued optimization problems.
	OnePlusOneGeneticAlgorithm(IntegerCostOptimizationProblem<BitVector> problem, double m, int bitLength, ProgressTracker<BitVector> tracker)	Creates a OnePlusOneGeneticAlgorithm instance for integer-valued optimization problems.
	OnePlusOneGeneticAlgorithm(IntegerCostOptimizationProblem<BitVector> problem, double m, int bitLength, ProgressTracker<BitVector> tracker)	Creates a OnePlusOneGeneticAlgorithm instance for integer-valued optimization problems.
	OnePlusOneGeneticAlgorithm(OptimizationProblem<BitVector> problem, double m, int bitLength)	Creates a OnePlusOneGeneticAlgorithm instance for real-valued optimization problems.
	OnePlusOneGeneticAlgorithm(OptimizationProblem<BitVector> problem, double m, int bitLength, ProgressTracker<BitVector> tracker)	Creates a OnePlusOneGeneticAlgorithm instance for real-valued optimization problems.
	OnePlusOneGeneticAlgorithm(OptimizationProblem<BitVector> problem, double m, int bitLength, ProgressTracker<BitVector> tracker)	Creates a OnePlusOneGeneticAlgorithm instance for real-valued optimization problems.
	SimpleGeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, double crossoverRate)	Initializes a simple genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation, single-point crossover (the SinglePointCrossover class), and fitness-proportional selection (the FitnessProportionalSelection class).
	SimpleGeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, double crossoverRate, ProgressTracker<BitVector> tracker)	Initializes a simple genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation, single-point crossover (the SinglePointCrossover class), and fitness-proportional selection (the FitnessProportionalSelection class).
	SimpleGeneticAlgorithm(int n, int bitLength, FitnessFunction.Double<BitVector> f, double mutationRate, double crossoverRate, ProgressTracker<BitVector> tracker)	Initializes a simple genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation, single-point crossover (the SinglePointCrossover class), and fitness-proportional selection (the FitnessProportionalSelection class).
	SimpleGeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, double crossoverRate)	Initializes a simple genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation, single-point crossover (the SinglePointCrossover class), and fitness-proportional selection (the FitnessProportionalSelection class).
	SimpleGeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, double crossoverRate, ProgressTracker<BitVector> tracker)	Initializes a simple genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation, single-point crossover (the SinglePointCrossover class), and fitness-proportional selection (the FitnessProportionalSelection class).
	SimpleGeneticAlgorithm(int n, int bitLength, FitnessFunction.Integer<BitVector> f, double mutationRate, double crossoverRate, ProgressTracker<BitVector> tracker)	Initializes a simple genetic algorithm with a generational model where children replace the parents, using the standard bit flip mutation, single-point crossover (the SinglePointCrossover class), and fitness-proportional selection (the FitnessProportionalSelection class).

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

Methods in org.cicirello.search.operators.bits that return BitVector

Modifier and Type	Method	Description
BitVector	BitVectorInitializer.createCandidateSolution()

Methods in org.cicirello.search.operators.bits with parameters of type BitVector

Modifier and Type	Method	Description
void	KPointCrossover.cross(BitVector c1, BitVector c2)	Performs a crossover for an evolutionary algorithm, such that crossover forms two children from two parents.
void	SinglePointCrossover.cross(BitVector c1, BitVector c2)	Performs a crossover for an evolutionary algorithm, such that crossover forms two children from two parents.
void	TwoPointCrossover.cross(BitVector c1, BitVector c2)	Performs a crossover for an evolutionary algorithm, such that crossover forms two children from two parents.
void	UniformCrossover.cross(BitVector c1, BitVector c2)	Performs a crossover for an evolutionary algorithm, such that crossover forms two children from two parents.
MutationIterator	DefiniteBitFlipMutation.iterator(BitVector c)
void	BitFlipMutation.mutate(BitVector c)
void	DefiniteBitFlipMutation.mutate(BitVector c)
void	BitFlipMutation.undo(BitVector c)
void	DefiniteBitFlipMutation.undo(BitVector c)

Uses of BitVector in org.cicirello.search.problems

Methods in org.cicirello.search.problems that return BitVector

Modifier and Type	Method	Description
final BitVector	PermutationToBitVectorProblem.createCandidateSolution()

Methods in org.cicirello.search.problems with parameters of type BitVector

Modifier and Type	Method	Description
double	HollandRoyalRoad.cost(BitVector candidate)	Computes the cost of a candidate solution to the problem instance.
double	Mix.cost(BitVector candidate)
int	OneMax.cost(BitVector candidate)
int	OneMaxAckley.cost(BitVector candidate)
double	PermutationToBitVectorProblem.DoubleCost.cost(BitVector candidate)
int	PermutationToBitVectorProblem.IntegerCost.cost(BitVector candidate)
double	Plateaus.cost(BitVector candidate)
int	Porcupine.cost(BitVector candidate)
int	RoyalRoad.cost(BitVector candidate)
double	Trap.cost(BitVector candidate)
int	TwoMax.cost(BitVector candidate)
int	TwoMaxEqualPeaks.cost(BitVector candidate)
double	PermutationToBitVectorProblem.DoubleCost.costAsDouble(BitVector candidate)
double	PermutationToBitVectorProblem.IntegerCost.costAsDouble(BitVector candidate)
final Permutation	PermutationToBitVectorProblem.toPermutation(BitVector bits)	Converts a BitVector to a Permutation.
double	HollandRoyalRoad.value(BitVector candidate)	Computes the value of the candidate solution within the usual constraints and interpretation of the problem.
double	Mix.value(BitVector candidate)
int	OneMax.value(BitVector candidate)
int	OneMaxAckley.value(BitVector candidate)
double	PermutationToBitVectorProblem.DoubleCost.value(BitVector candidate)
int	PermutationToBitVectorProblem.IntegerCost.value(BitVector candidate)
double	Plateaus.value(BitVector candidate)
int	Porcupine.value(BitVector candidate)
int	RoyalRoad.value(BitVector candidate)
double	Trap.value(BitVector candidate)
int	TwoMax.value(BitVector candidate)
int	TwoMaxEqualPeaks.value(BitVector candidate)

Uses of BitVector in org.cicirello.search.representations

Methods in org.cicirello.search.representations that return BitVector

Modifier and Type	Method	Description
BitVector	BitVector.copy()	Creates an identical copy of this object.

Methods in org.cicirello.search.representations with parameters of type BitVector

Modifier and Type	Method	Description
void	BitVector.and(BitVector other)	Computes the bitwise AND of this BitVector and another BitVector.
static void	BitVector.exchangeBits(BitVector b1, BitVector b2, int firstIndex, int lastIndex)	Exchanges a sequence of bits between two BitVector objects.
static void	BitVector.exchangeBits(BitVector b1, BitVector b2, BitVector mask)	Exchanges a selection of bits between two BitVectors, where the bits to exchange are indicated by a bit mask, also represented by a BitVector.
void	BitVector.or(BitVector other)	Computes the bitwise OR of this BitVector and another BitVector.
void	BitVector.xor(BitVector other)	Computes the bitwise XOR of this BitVector and another BitVector.