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.

iteration

abstract val iteration: Int

Current iteration of genetic algorithm.

mean

@get:JvmName(name = "getMeanDouble")

val EvolveScope<*, Double>.mean: Double

@get:JvmName(name = "getMeanInt")

val EvolveScope<*, Int>.mean: Double

@get:JvmName(name = "getMeanLong")

val EvolveScope<*, Long>.mean: Double

Mean fitness value of chromosomes in Population

median

@get:JvmName(name = "getMedianDouble")

val EvolveScope<*, Double>.median: Double

@get:JvmName(name = "getMedianInt")

val EvolveScope<*, Int>.median: Double

@get:JvmName(name = "getMedianLong")

val EvolveScope<*, Long>.median: Double

Median fitness value of chromosomes in Population

name

val EvolveScope<*, *>.name: String

Population Name of GA.

parallelismConfig

abstract val parallelismConfig: ParallelismConfig

Store parallelism configuration for GA. Determines genetic operators process.

population

abstract override val population: DistributedPopulation<V, F>

Override base population as DistributedPopulation for DistributedGA.

random

abstract val random: Random

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

size

val EvolveScope<*, *>.size: Int

Population Size of GA.

startOption

abstract var startOption: EvolveScopeStartOption

Option for starting children.

statisticsConfig

abstract val statisticsConfig: StatisticsConfig

Statistics configuration associated with GA.

store

abstract val store: MutableMap<String, Any?>

Store serves to synchronize between iterations of GA.

timeIteration

val <V, F> EvolveScope<V, F>.timeIteration: Duration?

Duration between current and previous iteration.

timeStore

abstract val timeStore: TimeStore

Store for all TimeMarkers of GA.

worst

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

The worst Chromosome in Population by fitness. Uses a StatisticsConfig.guaranteedSorted for optimization, except in the case of a call from DistributedEvolveScope.

worstFitness

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

The worst fitness of Chromosome in Population. Uses a StatisticsConfig.guaranteedSorted for optimization, except in the case of a call from DistributedEvolveScope.

Functions

bestFitness

fun <F> EvolveScope<*, F>.bestFitness(): Statistic<F?>

Creates Statistic for best fitness of Chromosome in Population.

emitStat

abstract suspend fun emitStat(value: StatisticNote<Any?>)

Emit StatisticNote to StatisticsProvider.

evaluateAll

inline suspend fun <V, F> EvolveScope<V, F>.evaluateAll(start: Int, end: Int, parallelismLimit: Int, crossinline fitnessFunction: (V) -> F)

Base evaluates function for all chromosomes in Population by fitnessFunction

launchChildren

suspend fun <V, F> DistributedEvolveScope<V, F>.launchChildren(parallelismLimit: Int)

Executes synchronized launch of DistributedEvolveScope.children with DistributedEvolveScope.startOption.

migration

fun <V, F> DistributedEvolveScope<V, F>.migration(percent: Double)

Executes random migration stage. Migration in DistributedGA is a process of chromosomes exchange between subpopulations.

parallelProcess

inline suspend fun EvolveScope<*, *>.parallelProcess(parallelismLimit: Int, startIteration: Int, endIteration: Int, crossinline action: suspend (iteration: Int, random: Random) -> Unit)

Iterative parallel process action from startIteration to endIteration.

inline suspend fun EvolveScope<*, *>.parallelProcess(parallelismLimit: Int, startIteration: Int, endIteration: Int, step: Int, crossinline action: suspend (iteration: Int, random: Random) -> Unit)

Iterative parallel process action from startIteration to endIteration with step.

process

inline fun EvolveScope<*, *>.process(parallelismLimit: Int, sequential: () -> Unit, parallel: () -> Unit)

Process action with sequential or parallel mode.

inline suspend fun EvolveScope<*, *>.process(parallelismLimit: Int, startIteration: Int, endIteration: Int, crossinline action: suspend (iteration: Int, random: Random) -> Unit)

Iterative process action from startIteration to endIteration.

inline suspend fun EvolveScope<*, *>.process(parallelismLimit: Int, startIteration: Int, endIteration: Int, step: Int, crossinline action: suspend (iteration: Int, random: Random) -> Unit)

Iterative process action from startIteration to endIteration with step.

randomByChance