hgalib-0.2: Haskell Genetic Algorithm Library Source code Contents Index

GA

Description

Genetic Algorithms

Synopsis

data Config c p = Config { cConfig :: ChromosomeConfig c p pConfig :: PopulationConfig c p newPopulation :: p -> GAState c p p maxFitness :: Maybe Double maxGeneration :: Maybe Int currentGeneration :: Int gen :: StdGen } data PopulationConfig c p = PopulationConfig { bestChromosomePop :: p -> GAState c p c roulettePop :: p -> GAState c p p tournamentPop :: p -> GAState c p p applyCrossoverPop :: p -> GAState c p p applyMutationPop :: p -> GAState c p p } data ChromosomeConfig c p = ChromosomeConfig { fitness :: c -> Double mutate :: c -> GAState c p c cross :: c -> c -> GAState c p (c, c) } defaultConfig :: Config c p type GAState c p = State (Config c p) bestChromosome :: p -> GAState c p c gaRand :: Random a => (a, a) -> GAState c p a run :: p -> GAState c p p rouletteM :: p -> GAState c p p mutateM :: p -> GAState c p p crossM :: p -> GAState c p p tournamentM :: p -> GAState c p p isDone :: p -> GAState c p Bool

Documentation

data Config c p Source

Constructors Config cConfig :: ChromosomeConfig c p The config for the chromosome model pConfig :: PopulationConfig c p The config for the population model newPopulation :: p -> GAState c p p The function that transforms a population into the next generation maxFitness :: Maybe Double The fitness at which to stop the GA maxGeneration :: Maybe Int The generation at which to stop the GA currentGeneration :: Int The number of generations elapsed. defaultConfig sets this to 0 gen :: StdGen The random number generator

data PopulationConfig c p Source

Constructors PopulationConfig bestChromosomePop :: p -> GAState c p c roulettePop :: p -> GAState c p p tournamentPop :: p -> GAState c p p applyCrossoverPop :: p -> GAState c p p applyMutationPop :: p -> GAState c p p

data ChromosomeConfig c p Source

Constructors ChromosomeConfig fitness :: c -> Double The fitness function for the chromosome model mutate :: c -> GAState c p c The mutation operator for the chromosome model cross :: c -> c -> GAState c p (c, c) The crossover operator for the chromosome model

defaultConfig :: Config c p Source

defaultConfig acts as a blank slate for genetic algorithms. cConfig, pConfig, gen, and maxFitness or maxGeneration must be defined

type GAState c p = State (Config c p) Source

bestChromosome :: p -> GAState c p c Source

Wrapper function which returns the best chromosome of a population

gaRand :: Random a => (a, a) -> GAState c p a Source

Generates a random number which updating the random number generator for the config

run :: p -> GAState c p p Source

Runs the specified GA config until the termination condition is reached

rouletteM :: p -> GAState c p p Source

A wrapper function for use in newPopulation for roulette selection

mutateM :: p -> GAState c p p Source

A wrapper function for use in newPopulation for mutating the population

crossM :: p -> GAState c p p Source

A wrapper function for use in newPopulation for applying crossover to the population

tournamentM :: p -> GAState c p p Source

A wrapper function for use in newPopulation for tournament selection

isDone :: p -> GAState c p Bool Source

Returns true if the given population satisfies the termination condition for the GA config

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