Class NSGAIIChildGenerationStrategy

Namespace

OptunaSharp.Samplers.Nsgaii

Assembly

OptunaSharp.dll

The default child-generation strategy of NSGAIISampler. Port of optuna/samplers/nsgaii/_child_generation_strategy.py: NSGAIIChildGenerationStrategy.

With probability crossover_prob a child is produced by crossover of tournament-selected parents; otherwise a single parent is copied. Each parameter is then mutated with probability mutation_prob (defaulting to 1 / len(params)): if a mutation object is set the value is mutated in place, otherwise the parameter is dropped and later resampled independently.

This is a bit-exact Optuna port. The conditional-parameter ("Categorical Parameter Trees") counterpart that evolves branch-defined parameters is NsgaiiiCptChildGenerationStrategy, used by NSGAIIICptSampler.

public class NSGAIIChildGenerationStrategy

Inheritance

object

NSGAIIChildGenerationStrategy

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

NSGAIIChildGenerationStrategy(BaseMutation?, double?, BaseCrossover, double, double, Func<FrozenTrial, IEnumerable<double>>?, LazyRandomState)

Configures the genetic operators and selection randomness used for offspring.

public NSGAIIChildGenerationStrategy(BaseMutation? mutation, double? mutationProb, BaseCrossover crossover, double crossoverProb, double swappingProb, Func<FrozenTrial, IEnumerable<double>>? constraintsFunc, LazyRandomState rng)

Parameters

mutation BaseMutation

Numerical mutation operator used when an offspring coordinate is selected for mutation.

mutationProb double?

Per-parameter mutation probability; null selects the operator default.

crossover BaseCrossover

Operator combining the selected numerical parent vectors.

crossoverProb double

Probability of applying crossover to a mating.

swappingProb double

Probability of taking a coordinate from the alternate parent.

constraintsFunc Func<FrozenTrial, IEnumerable<double>>

Optional legacy callback returning constraint values; positive values violate a constraint.

rng LazyRandomState

Random stream whose draw order is shared with the reference algorithm.

Exceptions

ValueError

A mutation, crossover, or swapping probability is outside its supported interval.

Methods

Generate(Study, OrderedDict<string, BaseDistribution>, List<FrozenTrial>)

Generate a child parameter dict from the given parent population (Python call).

public OrderedDict<string, object?> Generate(Study study, OrderedDict<string, BaseDistribution> searchSpace, List<FrozenTrial> parentPopulation)

Parameters

study Study

Study supplying trial history, objective directions, and storage.

searchSpace OrderedDict<string, BaseDistribution>

Ordered parameter distributions defining the coordinates used by this operation.

parentPopulation List<FrozenTrial>

Eligible parent trials from the current generation.

Returns

OrderedDict<string, object>

External offspring parameter values produced by the configured reproduction strategy.