Module io.jenetics.base
Package io.jenetics
Class ExponentialRankSelector<G extends Gene<?,G>,C extends Comparable<? super C>>
java.lang.Object
io.jenetics.ProbabilitySelector<G,C>
io.jenetics.ExponentialRankSelector<G,C>
- All Implemented Interfaces:
Selector<G,
C>
public final class ExponentialRankSelector<G extends Gene<?,G>,C extends Comparable<? super C>>
extends ProbabilitySelector<G,C>
An alternative to the "weak" LinearRankSelector
is to assign
survival probabilities to the sorted individuals using an exponential
function.
,
where c must within the range[0..1)
.
A small value of c increases the probability of the best phenotypes to be selected. If c is set to zero, the selection probability of the best phenotype is set to one. The selection probability of all other phenotypes is zero. A value near one equalizes the selection probabilities.
This selector sorts the population in descending order while calculating the selection probabilities.
- Since:
- 1.0
- Version:
- 5.0
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Field Summary
Fields inherited from class io.jenetics.ProbabilitySelector
_reverter, _sorted, POPULATION_COMPARATOR
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Constructor Summary
ConstructorDescriptionCreate a new selector with the default value of 0.975.ExponentialRankSelector
(double c) Create a new exponential rank selector. -
Method Summary
Methods inherited from class io.jenetics.ProbabilitySelector
probabilities, select
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Constructor Details
-
ExponentialRankSelector
Create a new exponential rank selector.- Parameters:
c
- the c value- Throws:
IllegalArgumentException
- ifc
is not within the range[0..1)
.
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ExponentialRankSelector
public ExponentialRankSelector()Create a new selector with the default value of 0.975.
-
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Method Details
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probabilities
This method sorts the population in descending order while calculating the selection probabilities.- Specified by:
probabilities
in classProbabilitySelector<G extends Gene<?,
G>, C extends Comparable<? super C>> - Parameters:
population
- The unsorted population.count
- The number of phenotypes to select. This parameter is not needed for most implementations.- Returns:
- Probability array. The returned probability array must have the
length
population.size()
and must sum to one. The returned value is checked withassert(Math.abs(math.sum(probabilities) - 1.0) < 0.0001)
in the base class.
-
toString
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