Class GenerationalEvolutionEngine<T>
- java.lang.Object
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- org.uncommons.watchmaker.framework.AbstractEvolutionEngine<T>
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- org.uncommons.watchmaker.framework.GenerationalEvolutionEngine<T>
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- Type Parameters:
T
- The type of entity that is to be evolved.
- All Implemented Interfaces:
EvolutionEngine<T>
public class GenerationalEvolutionEngine<T> extends AbstractEvolutionEngine<T>
This class implements a general-purpose generational evolutionary algorithm. It supports optional concurrent fitness evaluations to take full advantage of multi-processor, multi-core and hyper-threaded machines.
If multi-threading is enabled, evolution (mutation, cross-over, etc.) occurs on the request thread but fitness evaluations are delegated to a pool of worker threads. All of the host's available processing units are used (i.e. on a quad-core machine there will be four fitness evaluation worker threads).
If multi-threading is disabled, all work is performed synchronously on the request thread. This strategy is suitable for restricted/managed environments where it is not permitted for applications to manage their own threads. If there are no restrictions on concurrency, applications should enable multi-threading for improved performance.
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Constructor Summary
Constructors Constructor Description GenerationalEvolutionEngine(CandidateFactory<T> candidateFactory, EvolutionaryOperator<T> evolutionScheme, FitnessEvaluator<? super T> fitnessEvaluator, SelectionStrategy<? super T> selectionStrategy, Random rng)
Creates a new evolution engine by specifying the various components required by a generational evolutionary algorithm.GenerationalEvolutionEngine(CandidateFactory<T> candidateFactory, EvolutionaryOperator<T> evolutionScheme, InteractiveSelection<T> selectionStrategy, Random rng)
Creates a new evolution engine for an interactive evolutionary algorithm.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description protected List<EvaluatedCandidate<T>>
nextEvolutionStep(List<EvaluatedCandidate<T>> evaluatedPopulation, int eliteCount, Random rng)
This method performs a single step/iteration of the evolutionary process.-
Methods inherited from class org.uncommons.watchmaker.framework.AbstractEvolutionEngine
addEvolutionObserver, evaluatePopulation, evolve, evolve, evolvePopulation, evolvePopulation, getSatisfiedTerminationConditions, removeEvolutionObserver, setSingleThreaded
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Constructor Detail
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GenerationalEvolutionEngine
public GenerationalEvolutionEngine(CandidateFactory<T> candidateFactory, EvolutionaryOperator<T> evolutionScheme, FitnessEvaluator<? super T> fitnessEvaluator, SelectionStrategy<? super T> selectionStrategy, Random rng)
Creates a new evolution engine by specifying the various components required by a generational evolutionary algorithm.- Parameters:
candidateFactory
- Factory used to create the initial population that is iteratively evolved.evolutionScheme
- The combination of evolutionary operators used to evolve the population at each generation.fitnessEvaluator
- A function for assigning fitness scores to candidate solutions.selectionStrategy
- A strategy for selecting which candidates survive to be evolved.rng
- The source of randomness used by all stochastic processes (including evolutionary operators and selection strategies).
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GenerationalEvolutionEngine
public GenerationalEvolutionEngine(CandidateFactory<T> candidateFactory, EvolutionaryOperator<T> evolutionScheme, InteractiveSelection<T> selectionStrategy, Random rng)
Creates a new evolution engine for an interactive evolutionary algorithm. It is not necessary to specify a fitness evaluator for interactive evolution.- Parameters:
candidateFactory
- Factory used to create the initial population that is iteratively evolved.evolutionScheme
- The combination of evolutionary operators used to evolve the population at each generation.selectionStrategy
- Interactive selection strategy configured with appropriate console.rng
- The source of randomness used by all stochastic processes (including evolutionary operators and selection strategies).
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Method Detail
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nextEvolutionStep
protected List<EvaluatedCandidate<T>> nextEvolutionStep(List<EvaluatedCandidate<T>> evaluatedPopulation, int eliteCount, Random rng)
This method performs a single step/iteration of the evolutionary process.- Specified by:
nextEvolutionStep
in classAbstractEvolutionEngine<T>
- Parameters:
evaluatedPopulation
- The population at the beginning of the process.eliteCount
- The number of the fittest individuals that must be preserved.rng
- A source of randomness.- Returns:
- The updated population after the evolutionary process has proceeded by one step/iteration.
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