Simple framework of Genetic Algorithm
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README.md

GA

Simple Framework for Genetic Algorithm

Installation

Add this line to your application's Gemfile:

gem 'ga'

And then execute:

$ bundle

Or install it yourself as:

$ gem install ga

Usage

Define your unit

require methods:

  • Unit.random_new
  • Unit#initialize(genome) need copy genome
  • Unit#fitness return fitness
  • Unit#fitness= #set fitness
  • Unit#cross!(target_unit)
  • Unit#mutate!
class Unit
  include GA

  attr_accessor :genome, :fitness

  def self.random_new
    self.new(3.times.map { rand(3) })
  end

  def initialize(genome)
    @genome = genome.dup
  end

  def fitness
    @fitness ||= genome.reduce(&:+)
  end

  def cross!(target)
    (rand(3) + 1).times do |i|
      genome[i], target.genome[i] = target.genome[i], genome[i]
    end
  end

  def mutate!
    (rand(3) + 1).times do
      i = rand(3)
      genome[i] = (genome[i] + rand(3)) % 3
    end
  end
end

Evolve

Unit#evolve(total_units, generations, crossover_rate, muration_rate) return latest units

units = Unit.evolve(32, 100, 0.8, 0.15) 
best = units.max

Print evolve info

gz = Unit.new_ga_zoo
ga.debug!
units = ga.evolve(32, 100, 0.8, 0.15)

Use before_init_fitness callback

gz = Unit.new_ga_zoo
gz.before_init_fitness do |units, generation|
  # parallel calculate fitness
  data = Parallel.map(units, in_processes: 8) {|unit| unit.fitness }
  units.each_with_index {|unit, index| unit.fitness = data[index] }
end

More

see examples/ folder

Contributing

Bug reports and pull requests are welcome on GitHub at https://github.com/xjz19901211/ga.

License

The gem is available as open source under the terms of the MIT License.