G
- the gene type.N
- the BoltzmannSelector requires a number type.public final class BoltzmannSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>> extends ProbabilitySelector<G,N>
In this Selector
, the probability for selection is defined as.
.
Constructor and Description |
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BoltzmannSelector()
Create a new BoltzmannSelector with a default beta of 4.0.
|
BoltzmannSelector(double b)
Create a new BoltzmannSelector with the given b value.
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Modifier and Type | Method and Description |
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boolean |
equals(Object obj) |
int |
hashCode() |
protected double[] |
probabilities(Population<G,N> population,
int count)
Return an Probability array, which corresponds to the given Population.
|
String |
toString() |
probabilities, select
public BoltzmannSelector(double b)
b
- the b value of this BoltzmannSelectorpublic BoltzmannSelector()
protected double[] probabilities(Population<G,N> population, int count)
ProbabilitySelector
Return an Probability array, which corresponds to the given Population. The probability array and the population must have the same size. The population is not sorted. If a subclass needs a sorted population, the subclass is responsible to sort the population.
The implementer always assumes that higher fitness values are better. The base class inverts the probabilities, by reverting the returned probability array, if the GA is supposed to minimize the fitness function.probabilities
in class ProbabilitySelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>
population
- The unsorted population.count
- The number of phenotypes to select. This parameter is not
needed for most implementations.population.size()
and must sum to
one. The returned value is checked with
assert(Math.abs(math.sum(probabilities) - 1.0) < 0.0001)
in the base class.© 2007-2017 Franz Wilhelmstötter (2017-04-28 16:50)