Documentation of 'ec.select.TournamentSelection' Java class
TournamentSelection
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ec.select

Class TournamentSelection

  • All Implemented Interfaces:
    Prototype, Setup, SteadyStateBSourceForm, RandomChoiceChooserD, java.io.Serializable, java.lang.Cloneable
    Direct Known Subclasses:
    LexicographicTournamentSelection, ProportionalTournamentSelection, SpatialTournamentSelection, SPEA2TournamentSelection

    public class TournamentSelection
extends SelectionMethod
implements SteadyStateBSourceForm
    Does a simple tournament selection, limited to the subpopulation it's working in at the time.

    Tournament selection works like this: first, size individuals are chosen at random from the population. Then of those individuals, the one with the best fitness is selected.

    size can be any floating point value >= 1.0. If it is a non- integer value x then either a tournament of size ceil(x) is used (with probability x - floor(x)), else a tournament of size floor(x) is used.

    Common sizes for size include: 2, popular in Genetic Algorithms circles, and 7, popularized in Genetic Programming by John Koza. If the size is 1, then individuals are picked entirely at random.

    Tournament selection is so simple that it doesn't need to maintain a cache of any form, so many of the SelectionMethod methods just don't do anything at all.

    Typical Number of Individuals Produced Per produce(...) call
    Always 1.

    Parameters

    base.size
    double >= 1    		 (the tournament size)
    base.pick-worst
    bool = true or false (default)    		 (should we pick the worst individual in the tournament instead of the best?)

    Default Base
    select.tournament

    See Also:
    Serialized Form

    • Field Detail

      • P_TOURNAMENT

        public static final java.lang.String P_TOURNAMENT
        default base
        See Also:
        Constant Field Values

      • probabilityOfPickingSizePlusOne

        public double probabilityOfPickingSizePlusOne
        Probablity of picking the size plus one

      • pickWorst

        public boolean pickWorst
        Do we pick the worst instead of the best?

    • Constructor Detail

      • TournamentSelection

        public TournamentSelection()

    • Method Detail

      • defaultBase

        public Parameter defaultBase()
        Description copied from interface: Prototype
        Returns the default base for this prototype. This should generally be implemented by building off of the static base() method on the DefaultsForm object for the prototype's package. This should be callable during setup(...).
        Specified by:
        defaultBase in interface Prototype

      • setup

        public void setup(EvolutionState state,
                  Parameter base)
        Description copied from class: BreedingSource
        Sets up the BreedingPipeline. You can use state.output.error here because the top-level caller promises to call exitIfErrors() after calling setup. Note that probability might get modified again by an external source if it doesn't normalize right.

        The most common modification is to normalize it with some other set of probabilities, then set all of them up in increasing summation; this allows the use of the fast static BreedingSource-picking utility method, BreedingSource.pickRandom(...). In order to use this method, for example, if four breeding source probabilities are {0.3, 0.2, 0.1, 0.4}, then they should get normalized and summed by the outside owners as: {0.3, 0.5, 0.6, 1.0}.

        Specified by:
        setup in interface Prototype
        Specified by:
        setup in interface Setup
        Overrides:
        setup in class BreedingSource
        See Also:
        Prototype.setup(EvolutionState,Parameter)

      • getTournamentSizeToUse

        public int getTournamentSizeToUse(MersenneTwisterFast random)
        Returns a tournament size to use, at random, based on base size and probability of picking the size plus one.

      • getRandomIndividual

        public int getRandomIndividual(int number,
                               int subpopulation,
                               EvolutionState state,
                               int thread)
        Produces the index of a (typically uniformly distributed) randomly chosen individual to fill the tournament. number is the position of the individual in the tournament.

      • betterThan

        public boolean betterThan(Individual first,
                          Individual second,
                          int subpopulation,
                          EvolutionState state,
                          int thread)
        Returns true if *first* is a better (fitter, whatever) individual than *second*.

      • produce

        public int produce(int subpopulation,
                   EvolutionState state,
                   int thread)
        Description copied from class: SelectionMethod
        An alternative form of "produce" special to Selection Methods; selects an individual from the given subpopulation and returns its position in that subpopulation.
        Specified by:
        produce in class SelectionMethod
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