J. J. Merelo-Guervós > Algorithm-Evolutionary-0.78 > Algorithm::Evolutionary::Op::GeneralGeneration

Download:
Algorithm-Evolutionary-0.78.tar.gz

Dependencies

Annotate this POD

CPAN RT

Open  0
View/Report Bugs
Module Version: 3.0   Source   Latest Release: Algorithm-Evolutionary-0.80

NAME ^

Algorithm::Evolutionary::Op::GeneralGeneration - Customizable single generation for an evolutionary algorithm.

SYNOPSIS #Taken from the t/general.t file, verbatim my $m = new Algorithm::Evolutionary::Op::Bitflip; #Changes a single bit my $c = new Algorithm::Evolutionary::Op::Crossover; #Classical 2-point crossover my $replacementRate = 0.3; #Replacement rate use Algorithm::Evolutionary::Op::RouletteWheel; my $popSize = 20; my $selector = new Algorithm::Evolutionary::Op::RouletteWheel $popSize; #One of the possible selectors use Algorithm::Evolutionary::Op::GeneralGeneration; my $onemax = sub { my $indi = shift; my $total = 0; for ( my $i = 0; $i < $indi->length(); $i ++ ) { $total += substr( $indi->{_str}, $i, 1 ); } return $total; }; my @pop; my $numBits = 10; for ( 0..$popSize ) { my $indi = new Algorithm::Evolutionary::Individual::BitString $numBits ; #Creates random individual my $fitness = $onemax->( $indi ); $indi->Fitness( $fitness ); push( @pop, $indi ); } my $generation = new Algorithm::Evolutionary::Op::GeneralGeneration( $onemax, $selector, [$m, $c], $replacementRate ); my @sortPop = sort { $a->Fitness() <=> $b->Fitness() } @pop; my $bestIndi = $sortPop[0]; $generation->apply( \@sortPop ); ^

Base Class ^

Algorithm::Evolutionary::Op::Base

DESCRIPTION ^

Genetic algorithm that uses the other component. Must take as input the operators thar are going to be used, along with its priorities

METHODS ^

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

Creates an algorithm, with the usual operators. Includes a default mutation and crossover, in case they are not passed as parameters

set( $ref_to_params_hash, $ref_to_code_hash, $ref_to_operators_hash )

Sets the instance variables. Takes a ref-to-hash as input

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.

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: 2009/07/24 08:46:59 $ 
  $Header: /cvsroot/opeal/Algorithm-Evolutionary/lib/Algorithm/Evolutionary/Op/GeneralGeneration.pm,v 3.0 2009/07/24 08:46:59 jmerelo Exp $ 
  $Author: jmerelo $ 
  $Revision: 3.0 $
syntax highlighting: