NAME

Algorithm::Evolutionary::Run - Class for setting up an experiment with algorithms and population

SYNOPSIS

  use Algorithm::Evolutionary::Run;

  my $algorithm = new Algorithm::Evolutionary::Run 'conf.yaml';
  #or
  my $conf = {
    'fitness' => {
      'class' => 'MMDP'
    },
    'crossover' => {
      'priority' => '3',
      'points' => '2'
     },
    'max_generations' => '1000',
    'mutation' => {
      'priority' => '2',
      'rate' => '0.1'
    },
    'length' => '120',
    'max_fitness' => '20',
    'pop_size' => '1024',
    'selection_rate' => '0.1'
  };

  my $algorithm = new Algorithm::Evolutionary::Run $conf;

  #Run it to the end
  $algorithm->run();
  
  #Print results
  $algorithm->results();
  
  #A single step
  $algorithm->step();

DESCRIPTION

This is a no-fuss class to have everything needed to run an algorithm in a single place, although for the time being it's reduced to fitness functions in the A::E::F namespace, and binary strings. Mostly for demo purposes, but can be an example of class for other stuff.

METHODS

new( $algorithm_description )

Creates the whole stuff needed to run an algorithm. Can be called from a hash with t options, as per the example. All of them are compulsory. See also the examples subdir for examples of the YAML conf file.

population_size( $new_size )

Resets the population size to the $new_size. It does not do anything to the actual population, just resests the number. You should do a reset_population afterwards.

reset_population()

Resets population, creating a new one; resets fitness counter to 0

step()

Runs a single step of the algorithm, that is, a single generation

run()

Applies the different operators in the order that they appear; returns the population as a ref-to-array.

random_member()

Returns a random guy from the population

results()

Returns results in a hash that contains the best, total time so far and the number of evaluations.

evaluated_population()

Returns the portion of population that has been evaluated (all but the new ones)

compute_average_distance( $individual )

Computes the average hamming distance to the population

compute_min_distance( $individual )