org.uncommons.watchmaker.framework
Class GenerationalEvolutionEngine<T>

java.lang.Object
  org.uncommons.watchmaker.framework.AbstractEvolutionEngine<T>
      org.uncommons.watchmaker.framework.GenerationalEvolutionEngine<T>

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.

Author:

Daniel Dyer

See Also:

SteadyStateEvolutionEngine, EvolutionStrategyEngine

Constructor Summary

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.

Method Summary

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

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

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).

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).

Method Detail

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 class AbstractEvolutionEngine<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.