Class NSGAIIElitePopulationSelectionStrategy

Namespace

OptunaSharp.Samplers.Nsgaii

Assembly

OptunaSharp.dll

The default elite-population selection strategy of NSGAIISampler. Port of optuna/samplers/nsgaii/_elite_population_selection_strategy.py.

Ranks the combined population by (constrained) non-domination, then fills the elite population rank by rank; the rank that overflows population_size is truncated by crowding distance (descending). The resulting order is load-bearing — it seeds the parent population that later generations index into with rng.choice.

public class NSGAIIElitePopulationSelectionStrategy

Inheritance

object

NSGAIIElitePopulationSelectionStrategy

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

NSGAIIElitePopulationSelectionStrategy(int, Func<FrozenTrial, IEnumerable<double>>?)

Configures nondomination ranking and crowding-distance truncation to a fixed population size.

public NSGAIIElitePopulationSelectionStrategy(int populationSize, Func<FrozenTrial, IEnumerable<double>>? constraintsFunc = null)

Parameters

populationSize int

Number of individuals retained or evaluated per generation.

constraintsFunc Func<FrozenTrial, IEnumerable<double>>

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

Exceptions

ValueError

Population size is below two.

Methods

Select(Study, List<FrozenTrial>)

Select the elite population from the given trials (Python call).

public List<FrozenTrial> Select(Study study, List<FrozenTrial> population)

Parameters

study Study

Study supplying trial history, objective directions, and storage.

population List<FrozenTrial>

Individuals available for survival or reproduction.

Returns

List<FrozenTrial>

The individuals retained by the configured survival rule, in selection order.