Class: MHL::GeneticAlgorithmSolver

Inherits:
Object
  • Object
show all
Defined in:
lib/mhl/genetic_algorithm_solver.rb

Instance Method Summary collapse

Constructor Details

#initialize(opts) ⇒ GeneticAlgorithmSolver

Returns a new instance of GeneticAlgorithmSolver.


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# File 'lib/mhl/genetic_algorithm_solver.rb', line 11

def initialize(opts)
  @population_size = opts[:population_size].to_i
  unless @population_size and @population_size.even?
    raise ArgumentError, 'Even population size required!'
  end

  # perform genotype space-specific configuration
  case opts[:genotype_space_type]
  when :integer
    @genotype_space = IntegerVectorGenotypeSpace.new(opts[:genotype_space_conf])

    begin
      p_m = opts[:mutation_probability].to_f
      @mutation_rv = \
        ERV::RandomVariable.new(:distribution           => :geometric,
                                :probability_of_success => p_m)
    rescue
      raise ArgumentError, 'Mutation probability configuration is wrong.'
    end

    begin
      p_r = opts[:recombination_probability].to_f
      @recombination_rv = \
        ERV::RandomVariable.new(:distribution => :uniform,
                                :min_value    => -p_r,
                                :max_value    => 1.0 + p_r)
    rescue
      raise ArgumentError, 'Recombination probability configuration is wrong.'
    end

  when :bitstring
    @genotype_space   = BitstringGenotypeSpace.new(opts[:genotype_space_conf])
    @recombination_rv = ERV::RandomVariable.new(:distribution => :uniform, :max_value => 1.0)
    @mutation_rv      = ERV::RandomVariable.new(:distribution => :uniform, :max_value => 1.0)

  else
    raise ArgumentError, 'Only integer and bitstring genotype representations are supported!'
  end

  @exit_condition   = opts[:exit_condition]
  @start_population = opts[:genotype_space_conf][:start_population]
end

Instance Method Details

#solve(func) ⇒ Object

This is the method that solves the optimization problem

Parameter func is supposed to be a method (or a Proc, a lambda, or any callable object) that accepts the genotype as argument (that is, the set of parameters) and returns the phenotype (that is, the function result)


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# File 'lib/mhl/genetic_algorithm_solver.rb', line 60

def solve(func)
  # setup population
  if @start_population.nil?
    population = Array.new(@population_size) do
      # generate random genotype according to the chromosome type
      { :genotype => @genotype_space.get_random }
    end
  else
    population = @start_population.map do |x|
      { :genotype => x }
    end
  end

  # initialize variables
  gen = 0
  overall_best = nil

  # default behavior is to loop forever
  begin
    gen += 1
    puts "Starting generation #{gen} at #{Time.now}"

    # assess fitness for every member of the population
    population.each do |s|
      s[:task] = Concurrent::Future.new { func.call(s[:genotype]) }
    end

    # wait for all the evaluations to end
    population.each do |s|
      s[:fitness] = s[:task].value
    end

    # find fittest member
    population_best = population.max_by {|x| x[:fitness] }

    # calculate overall best
    if overall_best.nil?
      overall_best = population_best
    else
      overall_best = [ overall_best, population_best ].max_by {|x| x[:fitness] }
    end

    # print results
    puts "> gen #{gen}, best: #{overall_best[:genotype]}, #{overall_best[:fitness]}"

    # selection by binary tournament
    children = new_generation(population)

    # update population and generation number
    population = children
  end while @exit_condition.nil? or !@exit_condition.call(gen, overall_best)
end