KSLCore/ksl.simopt.solvers.algorithms.isc/LinearRankingSelection

LinearRankingSelection

class LinearRankingSelection(var eta: Double = DEFAULT_ETA)(source)

Linear-ranking selection-probability assignment for the ISC global phase (§A.5). Members are ranked best-first by shared fitness; rank i (1 = best, N = worst) receives the Baker linear rank probability p_i = (1/N)(η − 2(η−1)(i−1)/(N−1)), where the selection pressure η ∈ [1,2] is the expected number of offspring of the best individual. These probabilities are then made group-average: every member of a noise-aware FitnessGroup receives the average rank probability of that group, so statistically indistinguishable members are selected with equal probability. The probabilities sum to one.

Parameters

eta

the selection pressure η; must be in 1,2

Constructors

LinearRankingSelection

constructor(eta: Double = DEFAULT_ETA)

Types

Companion

object Companion

Properties

eta

var eta: Double

Functions

selectionProbabilities

fun selectionProbabilities(groups: List<FitnessGroup>): List<Pair<Solution, Double>>

Returns each solution paired with its group-averaged linear-rank selection probability, given the noise-aware groups (best group first). The returned probabilities sum to one.