jcgp.backend.modules.es

Class TournamentSelection

java.lang.Object

jcgp.backend.modules.Module

jcgp.backend.modules.es.EvolutionaryStrategy

jcgp.backend.modules.es.TournamentSelection

public class TournamentSelection
extends EvolutionaryStrategy

Tournament selection

This strategy generates a new population by selecting a specified number of chromosomes from the original population and selecting the fittest out of the isolated subset (the tournament). The selected individual is mutated using the specified mutator. This process is repeated until the new population is complete.

One integer parameter is used to control this strategy: tournament size. This must always be greater than 0 and smaller than or equal to the population size. Setting it to equal population size results in the same chromosome being selected for every tournament, and setting it to 1 leads to an effectively random search.
One additional parameter, report, controls whether a detailed log of the algorithm's operation is to be printed or not. Reports respect the report interval base parameter.

Author:

Eduardo Pedroni

See Also:

EvolutionaryStrategy

Constructor Summary

Constructors

Constructor and Description
TournamentSelection(Resources resources) Creates a new instance of TournamentSelection.

Method Summary

Modifier and Type	Method and Description
void	evolve(Population population, Mutator mutator) Performs the selection algorithm and uses the mutator to create the next generation of solutions.

Methods inherited from class jcgp.backend.modules.Module

getLocalParameters, toString

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

TournamentSelection

public TournamentSelection(Resources resources)

Creates a new instance of TournamentSelection.

Parameters:

resources - a reference to the experiment's resources.

Method Detail

evolve

public void evolve(Population population,
                   Mutator mutator)

Description copied from class: EvolutionaryStrategy

Performs the selection algorithm and uses the mutator to create the next generation of solutions.

Specified by:

evolve in class EvolutionaryStrategy

Parameters:

population - the population to evolve.

mutator - the mutator with which to mutate the promoted individuals.