All Classes and Interfaces

Class	Description
AbstractAlterer<G extends Gene<?,G>,C extends Comparable<? super C>>	Abstract implementation of the alterer interface.
AbstractChromosome<G extends Gene<?,G>>	The abstract base implementation of the Chromosome interface.
Accumulator<T,A extends Accumulator<T,A,R>,R>	This interface lets you accumulate elements of type T to a result of type R.
Alterer<G extends Gene<?,G>,C extends Comparable<? super C>>	The Alterer is responsible for the changing/recombining the Population.
AltererResult<G extends Gene<?,G>,C extends Comparable<? super C>>	Represents the result pair of a Alterer.alter(Seq, long) call, which consists of the altered population and the number of altered individuals.
AnyChromosome<A>	Chromosome implementation, which allows to create genes without explicit implementing the Chromosome interface.
AnyGene<A>	Gene implementation, which allows to create genes without explicit implementing the Gene interface.
Args	Helper class for parsing command line arguments.
Array<T>	Array implementation class.
Array.Store<T>	Minimal interface for accessing an underlying array structure.
Array.Store.Ref<T>	Mutable reference of an underlying array Store.
ArrayISeq<T>
ArrayMSeq<T>
Arrays	Helper class which contains array helper methods.
ArraySeq<T>
BaseMSeq<T>	General base interface for an ordered, fixed sized, mutable, object sequence.
BaseMSeqIterator<T>
BaseSeq<T>	General base interface for an ordered, fixed sized, object sequence.
BaseSeqIterator<T,S extends BaseSeq<T>>
BaseSeqSpliterator<T>
Basics	This object contains mathematical helper functions.
BitArray	This class represents a fixed sized array of bit or boolean values, backed by a byte[] array.
BitChromosome	Implementation of the classical BitChromosome.
BitGene	Implementation of a BitGene.
Bits	Some bit utils.
BoltzmannSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>	In this Selector, the probability for selection is defined as.
BoundedChromosome<A extends Comparable<? super A>,G extends BoundedGene<A,G>>	Chromosome interface for BoundedGenes.
BoundedGene<A extends Comparable<? super A>,G extends BoundedGene<A,G>>	Base interface for genes where the alleles are bound by a minimum and a maximum value.
CharacterChromosome	Character chromosome which represents character sequences.
CharacterGene	Character gene implementation.
CharSeq	This class is used for holding the valid characters of an CharacterGene.
CharStore
Chromosome<G extends Gene<?,G>>	A chromosome consists of one or more genes.
Codec<T,G extends Gene<?,G>>	A problem Codec contains the information about how to encode a given argument type into a Genotype.
Codecs	This class contains factory methods for creating common problem encodings.
CombineAlterer<G extends Gene<?,G>,C extends Comparable<? super C>>	Alters a chromosome by replacing two genes by the result of a given combiner function.
Concurrency
Constraint<G extends Gene<?,G>,C extends Comparable<? super C>>	This interface allows you to define constraints on single phenotypes.
Copyable<T>	This interface indicates that a class can create a copy of type T.
Crossover<G extends Gene<?,G>,C extends Comparable<? super C>>	Performs a Crossover of two Chromosome.
DoubleAdder	This class implements the the Kahan summation algorithm, which significantly reduces the numerical error when adding double values.
DoubleChromosome	Numeric chromosome implementation which holds 64-bit floating point numbers.
DoubleGene	Implementation of the NumericGene which holds a 64-bit floating point number.
DoubleMoments	Value objects which contains statistical moments.
DoubleMomentStatistics	A state object for collecting statistics such as count, min, max, sum, mean, variance, skewness and kurtosis.
DoubleRange	Double range class.
DoubleSummary	Value objects which contains statistical summary information.
EliteSelector<G extends Gene<?,G>,C extends Comparable<? super C>>	The EliteSelector copies a small proportion of the fittest candidates, without changes, into the next generation.
Empty	Contains static Seq definitions.
Empty.EmptyISeq
Empty.EmptyMSeq
Engine<G extends Gene<?,G>,C extends Comparable<? super C>>	Genetic algorithm engine which is the main class.
Engine.Builder<G extends Gene<?,G>,C extends Comparable<? super C>>	Builder class for building GA Engine instances.
Engine.Setup<G extends Gene<?,G>,C extends Comparable<? super C>>	This interface represents a recipe for configuring (setup) a given Engine.Builder.
EnumGene<A>	Gene which holds enumerable (countable) genes.
Evaluator<G extends Gene<?,G>,C extends Comparable<? super C>>	This interface allows defining different strategies for evaluating the fitness functions of a given population.
Evaluators	This class contains factory methods for creating commonly usable Evaluator implementations.
Evolution<G extends Gene<?,G>,C extends Comparable<? super C>>	This functional interface defines the evolution function, which takes an EvolutionStart object, evolves the population, and returns an EvolutionResult object.
EvolutionDurations	This class contains timing information about one evolution step.
EvolutionInit<G extends Gene<?,G>>	Represents the initialization value of an evolution stream/iterator.
EvolutionInterceptor<G extends Gene<?,G>,C extends Comparable<? super C>>	The evolution interceptor allows updating the EvolutionStart object, before the evolution start, and update the EvolutionResult object after the evolution.
EvolutionParams<G extends Gene<?,G>,C extends Comparable<? super C>>	This class collects the parameters which control the behavior of the evolution process.
EvolutionParams.Builder<G extends Gene<?,G>,C extends Comparable<? super C>>	Builder class for the evolution parameter.
EvolutionResult<G extends Gene<?,G>,C extends Comparable<? super C>>	Represents a state of the GA after an evolution step.
EvolutionSpliterator<G extends Gene<?,G>,C extends Comparable<? super C>>	The Spliterator implementation of the EvolutionStream.
EvolutionStart<G extends Gene<?,G>,C extends Comparable<? super C>>	Represents a state of the GA at the start of an evolution step.
EvolutionStatistics<C extends Comparable<? super C>,FitnessStatistics>	This class can be used to gather additional statistic information of an evolution process.
EvolutionStream<G extends Gene<?,G>,C extends Comparable<? super C>>	The EvolutionStream class extends the Java Stream and adds a method for limiting the evolution by a given predicate.
EvolutionStreamable<G extends Gene<?,G>,C extends Comparable<? super C>>	This interface defines the capability of creating EvolutionStreams from a given EvolutionStart object.
EvolutionStreamImpl<G extends Gene<?,G>,C extends Comparable<? super C>>
ExponentialRankSelector<G extends Gene<?,G>,C extends Comparable<? super C>>	An alternative to the "weak" LinearRankSelector is to assign survival probabilities to the sorted individuals using an exponential function.
Factory<T>
FitnessNullifier<G extends Gene<?,G>,C extends Comparable<? super C>>	This class allows forcing a reevaluation of the fitness function.
GaussianMutator<G extends NumericGene<?,G>,C extends Comparable<? super C>>	The GaussianMutator class performs the mutation of a NumericGene.
Gene<A,G extends Gene<A,G>>	Genes are the atoms of the Jenetics library.
Genotype<G extends Gene<?,G>>	The central class the GA is working with, is the Genotype.
Hashes	Static methods for simple and efficient hash-code calculation.
IntComparator	Comparator for int values.
IntegerChromosome	Numeric chromosome implementation which holds 32-bit integer numbers.
IntegerGene	NumericGene implementation which holds a 32-bit integer number.
IntermediateCrossover<G extends NumericGene<?,G>,C extends Comparable<? super C>>	This alterer takes two chromosomes (treating it as vectors) and creates a linear combination of these vectors as a result.
IntMoments	Value objects which contains statistical moments.
IntMomentStatistics	A state object for collecting statistics such as count, min, max, sum, mean, variance, skewness and kurtosis.
IntRange	Integer range class.
IntRef	Int reference class, which allows the usage in an lambda expression.
IntSummary	Value objects which contains statistical summary information.
InvertibleCodec<T,G extends Gene<?,G>>	This interface extends the Codec and allows to encode an object from the problem space to a corresponding Genotype, which is the inverse functionality of the codec.
IO	Class for object serialization.
ISeq<T>	Immutable, ordered, fixed sized sequence.
Lazy<T>	Class for lazy value initialization.
Lifecycle	Interfaces and classes for handling resource (AutoCloseable) objects.
Lifecycle.ExtendedCloseable<E extends Exception>	Extends the AutoCloseable with methods for wrapping the thrown exception into unchecked exceptions or ignoring them.
Lifecycle.IOResources	This class allows collecting one or more AutoCloseable objects into one.
Lifecycle.IOValue<T>	This class represents a closeable value.
Lifecycle.Resources<E extends Exception>	This class allows collecting one or more AutoCloseable objects into one.
Lifecycle.ThrowingConsumer<A,E extends Exception>	A method which takes an argument and can throw an exception.
Lifecycle.ThrowingFunction<A,R,E extends Exception>	A function which takes an argument and can throw an exception.
Lifecycle.ThrowingRunnable<E extends Exception>	Runnable task/method, which might throw an exception E.
Lifecycle.Value<T,E extends Exception>	This class represents a closeable value.
Limits	This class contains factory methods for creating predicates, which can be used for limiting the evolution stream.
LimitSpliterator<T>	Extends the Spliterator interface by an additional proceed predicate.
LinearRankSelector<G extends Gene<?,G>,C extends Comparable<? super C>>	In linear-ranking selection the individuals are sorted according to their fitness values.
LineCrossover<G extends NumericGene<?,G>,C extends Comparable<? super C>>	This alterer takes two chromosomes (treating it as vectors) and creates a linear combination of these vectors as a result.
LongChromosome	Numeric chromosome implementation which holds 64-bit integer numbers.
LongGene	NumericGene implementation which holds a 64-bit integer number.
LongMoments	Value objects which contains statistical moments.
LongMomentStatistics	A state object for collecting statistics such as count, min, max, sum, mean, variance, skewness and kurtosis.
LongRange	Long range class.
LongSummary	Value objects which contains statistical summary information.
Mean<T>	A mixin interface for genes which can have a mean value.
MeanAlterer<G extends Gene<?,G> & Mean<G>,C extends Comparable<? super C>>	Alters a chromosome by replacing two genes by its mean value.
MinMax<C>	This consumer class is used for calculating the min and max value according to the given Comparator.
MonteCarloSelector<G extends Gene<?,G>,C extends Comparable<? super C>>	The Monte Carlo selector selects the individuals from a given population randomly.
MSeq<T>	Mutable, ordered, fixed sized sequence.
MultiPointCrossover<G extends Gene<?,G>,C extends Comparable<? super C>>	Multiple point crossover
Mutator<G extends Gene<?,G>,C extends Comparable<? super C>>	This class is for mutating the chromosomes of a given population.
MutatorResult<T>	Represents the result pair of one of the four Mutator.mutate calls.
NanoClock	Clock implementation with nano second precision.
NumericChromosome<N extends Number & Comparable<? super N>,G extends NumericGene<N,G>>	Numeric chromosome interface.
NumericGene<N extends Number & Comparable<? super N>,G extends NumericGene<N,G>>	Base interface for numeric genes.
ObjectStore<T>
Optimize	This enum determines whether the GA should maximize or minimize the fitness function.
Ordered<T>	Object wrapper, which makes the wrapped value Comparable, by defining a separate Comparator.
PartialAlterer<G extends Gene<?,G>,C extends Comparable<? super C>>	This alterer wraps a given alterer which works on a given section of the genotype's chromosomes.
PartiallyMatchedCrossover<T,C extends Comparable<? super C>>	The PartiallyMatchedCrossover (PMX) guarantees that all Genes are found exactly once in each chromosome.
PermutationChromosome<T>	This chromosome can be used to model permutations of a given (sub) set of alleles.
Phenotype<G extends Gene<?,G>,C extends Comparable<? super C>>	The Phenotype consists of a Genotype, the current generation and an optional fitness value.
Predicates	This class contains some common predicates
Probabilities	Mathematical functions regarding probabilities.
ProbabilitySelector<G extends Gene<?,G>,C extends Comparable<? super C>>	Probability selectors are a variation of fitness proportional selectors and selects individuals from a given population based on its selection probability P(i).
Problem<T,G extends Gene<?,G>,C extends Comparable<? super C>>	This interface describes a problem which can be solved by the GA evolution Engine.
ProxySorter	This sorting methods doesn't sort a given array directly, instead an index lookup array is returned which allows to access the array in a sorted order.
ProxySorter.Comparator<T>	The comparator used for comparing two array elements at the specified indexes.
Quantile	Implementation of the quantile estimation algorithm published by
RandomAdapter	Some places in the Java API still require a Random object instead of the new RandomGenerator.
RandomRegistry	This class holds the RandomGenerator engine used for the GA.
Randoms	Some random helper functions.
Recombinator<G extends Gene<?,G>,C extends Comparable<? super C>>	An enhanced genetic algorithm (EGA) combine elements of existing solutions in order to create a new solution, with some of the properties of each parent.
Requires	Some helper methods for creating hash codes and comparing values.
RetryConstraint<G extends Gene<?,G>,C extends Comparable<? super C>>	This simple Constraint implementation repairs an invalid phenotype by creating new individuals until a valid one has been created.
RouletteWheelSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>	The roulette-wheel selector is also known as fitness proportional selector, but in the Jenetics library it is implemented as probability selector.
Selector<G extends Gene<?,G>,C extends Comparable<? super C>>	Selectors are responsible for selecting a given number of individuals from the population.
Self<S extends Self<S>>	This interface defines a recursive generic type S, which represents the type of the implementing class.
Seq<T>	General interface for a ordered, fixed sized, object sequence.
SerialIO	Helper methods needed for implementing the Java serializations.
SerialIO.Reader<T>	Object reader interface
SerialIO.Writer<T>	Object writer interface.
SinglePointCrossover<G extends Gene<?,G>,C extends Comparable<? super C>>	Single point crossover
StochasticUniversalSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>	StochasticUniversalSelector is a method for selecting a population according to some given probability in a way that minimizes chance fluctuations.
StreamProxy<T>
StreamPublisher<T>	This class allows creating a reactive Flow.Publisher from a given Java Stream.
Streams	This class contains factory methods for (flat) mapping stream elements.
Subset	This class creates random subsets of size k from a set of n elements.
SwapMutator<G extends Gene<?,G>,C extends Comparable<? super C>>	The SwapMutation changes the order of genes in a chromosome, with the hope of bringing related genes closer together, thereby facilitating the production of building blocks.
TournamentSelector<G extends Gene<?,G>,C extends Comparable<? super C>>	In tournament selection the best individual from a random sample of s individuals is chosen from the population Pg.
TruncationSelector<G extends Gene<?,G>,C extends Comparable<? super C>>	In truncation selection, individuals are sorted according to their fitness.
UniformCrossover<G extends Gene<?,G>,C extends Comparable<? super C>>	The uniform crossover uses swaps single genes between two chromosomes, instead of whole ranges as in single- and multipoint crossover.
Verifiable	This interface lets you check an object for validity.