T
- The component type of the lists that are mutated.public class ListOrderMutation<T> extends Object implements EvolutionaryOperator<List<T>>
PoissonGenerator
), to determine how
many mutations to apply.Constructor and Description |
---|
ListOrderMutation()
Default is one mutation per candidate.
|
ListOrderMutation(int mutationCount,
int mutationAmount) |
ListOrderMutation(NumberGenerator<Integer> mutationCount,
NumberGenerator<Integer> mutationAmount)
Typically the mutation count will be from a Poisson distribution.
|
Modifier and Type | Method and Description |
---|---|
List<List<T>> |
apply(List<List<T>> selectedCandidates,
Random rng)
Apply the operation to each entry in the list of selected
candidates.
|
public ListOrderMutation()
public ListOrderMutation(int mutationCount, int mutationAmount)
mutationCount
- The constant number of mutations
to apply to each individual in the population.mutationAmount
- The constant number of positions by
which a list element will be displaced as a result of mutation.public ListOrderMutation(NumberGenerator<Integer> mutationCount, NumberGenerator<Integer> mutationAmount)
mutationCount
- A random variable that provides a number
of mutations that will be applied to each individual.mutationAmount
- A random variable that provides a number
of positions by which to displace an element when mutating.public List<List<T>> apply(List<List<T>> selectedCandidates, Random rng)
EvolutionaryOperator
Apply the operation to each entry in the list of selected candidates. It is important to note that this method operates on the list of candidates returned by the selection strategy and not on the current population. Each entry in the list (not each individual - the list may contain the same individual more than once) must be operated on exactly once.
Implementing classes should not assume any particular ordering (or lack of ordering) for the selection. If ordering or shuffling is required, it should be performed by the implementing class. The implementation should not re-order the list provided but instead should make a copy of the list and re-order that. The ordering of the selection should be totally irrelevant for operators that process each candidate in isolation, such as mutation. It should only be an issue for operators, such as cross-over, that deal with multiple candidates in a single operation.
The operator should not modify any of the candidates passed in. Instead it should return a list that contains evolved copies of those candidates (umodified candidates can be included in the results without having to be copied).
apply
in interface EvolutionaryOperator<List<T>>
selectedCandidates
- The individuals to evolve.rng
- A source of randomness for stochastic operators (most
operators will be stochastic).