NAME

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

SYNOPSIS

use Algorithm::Evolutionary qw( Individual::BitString 
Op::Mutation Op::Crossover
Op::RouletteWheel
Op::Breeder);

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

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::Breeder( $selector, [$m, $c] );

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

Breeder part of the evolutionary algorithm; takes a population and returns another created from the first

METHODS

new( $ref_to_operator_array[, $selector = new Algorithm::Evolutionary::Op::Tournament_Selection 2 ] )

Creates a breeder, with a selector and array of operators

apply( $population[, $how_many || $population_size] )

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