78 lines
2.1 KiB
Elixir
78 lines
2.1 KiB
Elixir
defmodule Genetic do
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alias Types.Chromosome
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def initialize(genotype, opts \\ []) do
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population_size = Keyword.get(opts, :population_size, 100)
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for _ <- 1..population_size, do: genotype.()
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end
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def evaluate(population, fitness_function, opts \\ []) do
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population
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|> Enum.map(
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fn chromosome ->
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fitness = fitness_function.(chromosome)
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age = chromosome.age + 1
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%Chromosome{chromosome | fitness: fitness, age: age}
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end
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)
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|> Enum.sort_by(& &1.fitness, &>=/2)
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end
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def select(population, opts \\ []) do
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population
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|> Enum.chunk_every(2)
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|> Enum.map(&List.to_tuple(&1))
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end
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def crossover(population, opts \\ []) do
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population
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|> Enum.reduce([],
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fn {p1, p2}, acc ->
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cx_point = :rand.uniform(length(p1.genes))
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{{h1,t1},{h2,t2}} =
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{Enum.split(p1.genes, cx_point),
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Enum.split(p2.genes, cx_point)}
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{c1,c2} = {%Chromosome{p1 | genes: h1 ++ t2}, %Chromosome{p2 | genes: h2 ++ t1} }
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[c1,c2 | acc]
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end
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)
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end
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def mutation(population, opts \\ []) do
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population
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|> Enum.map(
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fn chromosome ->
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if :rand.uniform() < 0.05 do
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%Chromosome{chromosome | genes: Enum.shuffle(chromosome)}
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else
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chromosome
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end
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end
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)
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end
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def run(problem, opts \\ []) do
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population = initialize(&problem.genotype/0)
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population
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|> evolve(problem, opts)
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end
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def evolve(population, problem, opts \\ []) do
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population = evaluate(population, &problem.fitness_function/1, opts)
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best = hd(population)
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IO.write("\rCurrent Best: #{best.fitness}")
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if problem.terminate?(population) do
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best
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else
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population
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|> select(opts)
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|> crossover(opts)
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|> mutation(opts)
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|> evolve(problem, opts)
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end
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end
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end
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