kgal-core/kgal.cellular/CellularGA

CellularGA

interface CellularGA<V, F> : GA<V, F>

CellularGA - cellular genetic algorithm (cGA).

V - value of Chromosome

F - fitness value of Chromosome

A cellular genetic algorithm is a kind of genetic algorithm in which individuals cannot mate arbitrarily, but every one interacts with its closer neighbors on which a basic evolution strategy is applied (selection, crossover, mutation, evaluation).

Creates with Kotlin DSL by cGA.

See also

Cellular Genetic Algorithm by Enrique Alba

CellularPopulation

CellularEvolveScope

CellEvolveScope

Types

object Companion

Properties

activeTimeTotal

val <V, F> GA<V, F>.activeTimeTotal: Duration

Duration between all subsessions of Session.

val GA<*, *>.allSessions: SessionsInfo

Creates SessionsInfo that describes all activity of GA.

val <V, F> GA<V, F>.best: Chromosome<V, F>?

The best Chromosome in Population by fitness.

val <V, F> GA<V, F>.bestFitness: F?

The best fitness of Chromosome in Population.

abstract var cellularType: CellularType

Cellular type for CellularGA.

abstract var elitism: Boolean

Flag for elitism in CellularGA.

val <V, F> GA<V, F>.factory: PopulationFactory<V, F>

Population Factory of GA.

fitnessFunction

abstract var fitnessFunction: (V) -> F

Fitness function - a function that evaluates the quality or "fitness" of each individual (chromosome) in a population. The fitness function determines how well a particular solution matches the target problem. It can be changed.

abstract val isActive: Boolean

Return true if GA is active.

abstract val iteration: Int

Current iteration of genetic algorithm.

@get:JvmName(name = "getMeanDouble")

val GA<*, Double>.mean: Double

@get:JvmName(name = "getMeanInt")

val GA<*, Int>.mean: Double

@get:JvmName(name = "getMeanLong")

val GA<*, Long>.mean: Double

Mean fitness value of chromosomes in Population

@get:JvmName(name = "getMedianDouble")

val GA<*, Double>.median: Double

@get:JvmName(name = "getMedianInt")

val GA<*, Int>.median: Double

@get:JvmName(name = "getMedianLong")

val GA<*, Long>.median: Double

Median fitness value of chromosomes in Population

val GA<*, *>.name: String

Population Name of GA.

abstract var neighborhood: CellularNeighborhood

Neighborhood for CellularGA.

abstract override val population: CellularPopulation<V, F>

Population of homogeneous chromosomes for CellularGA.

abstract val random: Random

Random associated with GA. Defines a pseudorandom number generator for predictive calculations.

val GA<*, *>.size: Int

Population Size of GA.

abstract val state: State

State describes the current state of the genetic algorithm.

statisticsProvider

abstract val statisticsProvider: StatisticsProvider

Statistics configuration associated with GA.

abstract val timeStore: TimeStore

Store for all TimeMarkers of GA.

val <V, F> GA<V, F>.timeTotal: Duration

Duration between the first STARTED and last value of timeStore

val <V, F> GA<V, F>.worst: Chromosome<V, F>?

The worst Chromosome in Population by fitness.

val <V, F> GA<V, F>.worstFitness: F?

The worst fitness of Chromosome in Population.

Functions

clearCollectors

inline suspend fun GA<*, *>.clearCollectors()

Unsubscribe and clear all collectors for StatisticsProvider.

fun <V, F> GA<V, F>.collect(id: String = BASE_COLLECTOR_ID, collector: STAT_COLLECTOR): GA<V, F>

Allows you to collect statistical data using reactive programming by kotlinx.coroutines.flow.

removeCollector

inline suspend fun GA<*, *>.removeCollector(id: String)

Unsubscribe and remove collector by id.

abstract suspend fun restart(forceStop: Boolean = false, resetPopulation: Boolean = true)

Immediately restart genetic algorithm.

abstract suspend fun resume()

Resume stopped genetic algorithm.

abstract suspend fun start()

Start genetic algorithm.

fun GA<*, *>.startBlocking(context: CoroutineContext = EmptyCoroutineContext)

Start GA with runBlocking, non suspend function.

abstract suspend fun stop(stopPolicy: StopPolicy = StopPolicy.Default)

Stop genetic algorithm.