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Manual Reference Pages  -  ALGORITHM::EVOLUTIONARY::OP::GENERALGENERATION (3)

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NAME

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

CONTENTS

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

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

set( CW$ref_to_params_hash, CW$ref_to_code_hash, CW$ref_to_operators_hash )

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

apply( CW$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

o A more modern and flexible version: Algorithm::Evolutionary::Op::Generation_Skeleton.
o Algorithm::Evolutionary::Op::CanonicalGA.
o Algorithm::Evolutionary::Op::FullAlgorithm.

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
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perl v5.20.3 ALGORITHM::EVOLUTIONARY::OP::GENERALGENERATION (3) 2014-10-25

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