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
Algorithm::Evolutionary::Op::Generation_Skeleton does have a incompatible interface
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