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 |
---|
BoltzmannSelector()
Create a new BoltzmannSelector with a default beta of 4.0.
|
BoltzmannSelector(double b)
Create a new BoltzmanSelector with the given b value.
|
Modifier and Type | Method and Description |
---|---|
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 BoltzmanSelectorpublic 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 (p = 1.0 - p
) 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.© 2007-2014 Franz Wilhelmstötter (2014-12-28 10:45)