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NAME

    AI::Genetic::Pro - Efficient genetic algorithms for professional
    purpose with support for multiprocessing.

SYNOPSIS

        use AI::Genetic::Pro;
        
        sub fitness {
            my ($ga, $chromosome) = @_;
            return oct('0b' . $ga->as_string($chromosome)); 
        }
        
        sub terminate {
            my ($ga) = @_;
            my $result = oct('0b' . $ga->as_string($ga->getFittest));
            return $result == 4294967295 ? 1 : 0;
        }
        
        my $ga = AI::Genetic::Pro->new(        
            -fitness         => \&fitness,        # fitness function
            -terminate       => \&terminate,      # terminate function
            -type            => 'bitvector',      # type of chromosomes
            -population      => 1000,             # population
            -crossover       => 0.9,              # probab. of crossover
            -mutation        => 0.01,             # probab. of mutation
            -parents         => 2,                # number  of parents
            -selection       => [ 'Roulette' ],   # selection strategy
            -strategy        => [ 'Points', 2 ],  # crossover strategy
            -cache           => 0,                # cache results
            -history         => 1,                # remember best results
            -preserve        => 3,                # remember the bests
            -variable_length => 1,                # turn variable length ON
            -mce             => 1,                # optional MCE support
            -workers         => 3,                # number of workers (MCE)
        );
            
        # init population of 32-bit vectors
        $ga->init(32);
            
        # evolve 10 generations
        $ga->evolve(10);
        
        # best score
        print "SCORE: ", $ga->as_value($ga->getFittest), ".\n";
        
        # save evolution path as a chart
        $ga->chart(-filename => 'evolution.png');
         
        # save state of GA
        $ga->save('genetic.sga');
        
        # load state of GA
        $ga->load('genetic.sga');

DESCRIPTION

    This module provides efficient implementation of a genetic algorithm
    for professional purpose with support for multiprocessing. It was
    designed to operate as fast as possible even on very large populations
    and big individuals/chromosomes. AI::Genetic::Pro was inspired by
    AI::Genetic, so it is in most cases compatible (there are some
    changes). Additionally AI::Genetic::Pro isn't a pure Perl solution, so
    it doesn't have limitations of its ancestor (such as slow-down in the
    case of big populations ( >10000 ) or vectors with more than 33
    fields).

    If You are looking for a pure Perl solution, consider AI::Genetic.

    Speed

      To increase speed XS code is used, however with portability in mind.
      This distribution was tested on Windows and Linux platforms (and
      should work on any other).

      Multicore support is available through Many-Core Engine (MCE). You
      can gain the most speed up for big populations or time/CPU consuming
      fitness functions, however for small populations and/or simple
      fitness function better choice will be single-process version.

      You can get even more speed up if you turn on use of native arrays
      (parameter: native) instead of packing chromosomes into single
      scalar. However you have to remember about expensive memory use in
      that case.

    Memory