++ed by:
EGOR

1 PAUSE user
1 non-PAUSE user.

J. J. Merelo-Guervós
and 1 contributors

NAME

Algorithm::Evolutionary::Op::Generation_Skeleton - Even more customizable single generation for an evolutionary algorithm.

SYNOPSIS

    use Algorithm::Evolutionary qw( Individual::BitString 
                                Op::Mutation Op::Crossover
                                Op::RouletteWheel
                                Fitness::ONEMAX Op::Generation_Skeleton
                                Op::Replace_Worst);

    use Algorithm::Evolutionary::Utils qw(average);

    my $onemax = new Algorithm::Evolutionary::Fitness::ONEMAX;

    my @pop;
    my $number_of_bits = 20;
    my $population_size = 20;
    my $replacement_rate = 0.5;
    for ( 1..$population_size ) {
      my $indi = new Algorithm::Evolutionary::Individual::BitString $number_of_bits ; #Creates random individual
      $indi->evaluate( $onemax );
      push( @pop, $indi );
    }

    my $m =  new Algorithm::Evolutionary::Op::Mutation 0.5;
    my $c = new Algorithm::Evolutionary::Op::Crossover; #Classical 2-point crossover

    my $selector = new Algorithm::Evolutionary::Op::RouletteWheel $population_size; #One of the possible selectors

    my $generation = 
      new Algorithm::Evolutionary::Op::Generation_Skeleton( $onemax, $selector, [$m, $c], $replacement_rate );

    my @sortPop = sort { $b->Fitness() <=> $a->Fitness() } @pop;
    my $bestIndi = $sortPop[0];
    my $previous_average = average( \@sortPop );
    $generation->apply( \@sortPop );

Base Class

Algorithm::Evolutionary::Op::Base

DESCRIPTION

Skeleton class for a general single-generation (or single step) in an evolutionary algorithm; its instantiation requires a fitness function, a Selector, a reference to an array of operators and a replacement operator

METHODS

new( $evaluation_function, $selector, $ref_to_operator_array, $replacement_operator )

Creates an algorithm, with no defaults except for the default replacement operator (defaults to Algorithm::Evolutionary::Op::ReplaceWorst)

set( $ref_to_params_hash, $ref_to_code_hash, $ref_to_operators_hash )

Sets the instance variables. Takes a ref-to-hash as input. Not intended to be used from outside the class

apply( $population )

Applies the algorithm to the population, which should have been evaluated first; checks that it receives a ref-to-array as input, croaks if it does not. Returns a sorted, culled, evaluated population for next generation.

SEE ALSO

More or less in the same ballpark, alternatives to this one

Copyright

This file is released under the GPL. See the LICENSE file included in this distribution, or go to http://www.fsf.org/licenses/gpl.txt

  CVS Info: $Date: 2013/01/05 12:43:32 $ 
  $Header: /media/Backup/Repos/opeal/opeal/Algorithm-Evolutionary/lib/Algorithm/Evolutionary/Op/Generation_Skeleton.pm,v 3.3 2013/01/05 12:43:32 jmerelo Exp $ 
  $Author: jmerelo $ 
  $Revision: 3.3 $