Package ec.select

# Class GreedyOverselection

java.lang.Object
ec.BreedingSource
ec.SelectionMethod
ec.select.GreedyOverselection

All Implemented Interfaces:
  `Prototype`, `Setup`, `RandomChoiceChooserD`, `Serializable`, `Cloneable`

public class GreedyOverselection extends SelectionMethod
GreedyOverselection is a SelectionMethod which implements Koza-style fitness-proportionate greedy overselection. Not appropriate for multiobjective fitnesses.

This selection method first divides individuals in a population into two groups: the "good" ("top") group, and the "bad" ("bottom") group. The best top percent of individuals in the population go into the good group. The rest go into the "bad" group. With a certain probability (determined by the gets setting), an individual will be picked out of the "good" group. Once we have determined which group the individual will be selected from, the individual is picked using fitness proportionate selection in that group, that is, the likelihood he is picked is proportionate to his fitness relative to the fitnesses of others in his group.

All this is expensive to set up and bring down, so it's not appropriate for steady-state evolution. If you're not familiar with the relative advantages of selection methods and just want a good one, use TournamentSelection instead.

Note: Fitnesses must be non-negative. 0 is assumed to be the worst fitness.

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

Parameters

base.`top` 0.0 <= double <= 1.0 | (the percentage of the population going into the "good" (top) group)
base.`gets` 0.0 <= double <= 1.0 | (the likelihood that an individual will be picked from the "good" group)

Default Base
select.greedy

See Also:
  - Serialized Form

- ## Field Summary

  Fields
  Modifier and Type
  Field
  Description
  `double`
  `gets_n_percent`
  `static final String`
  `P_GETS`
  `static final String`
  `P_GREEDY`
  `static final String`
  `P_TOP`
  `double[]`
  `sortedFitOver`
  `double[]`
  `sortedFitUnder`
  `int[]`
  `sortedPop`
  Sorted population -- since I *have* to use an int-sized individual (short gives me only 16K), I might as well just have pointers to the population itself.
  `double`
  `top_n_percent`

  ### Fields inherited from class ec.SelectionMethod

  `INDS_PRODUCED, KEY_PARENTS`

  ### Fields inherited from class ec.BreedingSource

  `NO_PROBABILITY, P_PROB, probability`

- ## Constructor Summary

  Constructors
  Constructor
  Description
  `GreedyOverselection()`

- ## Method Summary

  Modifier and Type
  Method
  Description
  `Parameter`
  `defaultBase()`
  Returns the default base for this prototype.
  `void`
  `finishProducing(EvolutionState s, int subpopulation, int thread)`
  A default version of finishProducing, which does nothing.
  `void`
  `prepareToProduce(EvolutionState s, int subpopulation, int thread)`
  A default version of prepareToProduce which does nothing.
  `int`
  `produce(int subpopulation, EvolutionState state, int thread)`
  An alternative form of "produce" special to Selection Methods; selects an individual from the given subpopulation and returns its position in that subpopulation.
  `void`
  `setup(EvolutionState state, Parameter base)`
  Sets up the BreedingPipeline.

  ### Methods inherited from class ec.SelectionMethod

  `produce, produces, produceWithoutCloning, typicalIndsProduced`

  ### Methods inherited from class ec.BreedingSource

  `clone, fillStubs, getProbability, pickRandom, preparePipeline, setProbability, setupProbabilities`

  ### Methods inherited from class java.lang.Object

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

- ## Field Details

  - ### sortedFitOver

    public double[] sortedFitOver

  - ### sortedFitUnder

    public double[] sortedFitUnder

  - ### sortedPop

    public int[] sortedPop
    Sorted population -- since I *have* to use an int-sized individual (short gives me only 16K), I might as well just have pointers to the population itself. :-(

  - ### P_GREEDY

    public static final String P_GREEDY
    See Also:
      - Constant Field Values

  - ### P_TOP

    public static final String P_TOP
    See Also:
      - Constant Field Values

  - ### P_GETS

    public static final String P_GETS
    See Also:
      - Constant Field Values

  - ### top_n_percent

    public double top_n_percent

  - ### gets_n_percent

    public double gets_n_percent

- ## Constructor Details

  - ### GreedyOverselection

    public GreedyOverselection()

- ## Method Details

  - ### 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(...).

  - ### 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)`

  - ### prepareToProduce

    public void prepareToProduce(EvolutionState s, int subpopulation, int thread)
    Description copied from class: `SelectionMethod`
    A default version of prepareToProduce which does nothing.
    Overrides:
      `prepareToProduce` in class `SelectionMethod`

  - ### 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`

  - ### finishProducing

    public void finishProducing(EvolutionState s, int subpopulation, int thread)
    Description copied from class: `SelectionMethod`
    A default version of finishProducing, which does nothing.
    Overrides:
      `finishProducing` in class `SelectionMethod`