NAME
    AI::Genetic::Pro - Efficient genetic algorithms for professional
    purpose.

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 individuals
            -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
        );
            
    # 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');

DESCRIPTION
    This module provides efficient implementation of a genetic algorithm for
    a professional purpose. It was designed to operate as fast as possible
    even on very large populations and big individuals. "AI::Genetic::Pro"
    was inspired by "AI::Genetic", so it is in most cases compatible (there
    are some changes). Additionaly "AI::Genetic::Pro" doesn't have
    limitations of its ancestor (ie. seriously slow down in case of big
    populations ( >10000 ) or vectors with size > 33 fields).

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

    Memory
        This module was designed to use as little memory as possible.
        Population of size 10000 consist 92-bit vectors uses only ~24MB (in
        "AI::Genetic" something about ~78MB!!!).

    Advanced options
        To provide more flexibility "AI::Genetic::Pro" supports many
        statistic distributions, such as: "uniform", "natural", "chi_square"
        and others. This feature can be used in selection or/and crossover.
        See documentation below.

METHODS
    Simply description of available methods. See below.

  new( %options )
    Constructor. It accepts options in hash-value style. See options and an
    example below.

   -fitness
    This defines a *fitness* function. It expects a reference to a
    subroutine.

   -terminate
    This defines a *terminate* function. It expects a reference to a
    subroutine.

   -type
    This defines the type of chromosomes. Currently, "AI::Genetic::Pro"
    supports four types:

   bitvector
   listvector
   rangevector
   combination
   -population
    This defines the size of the population, i.e. how many individuals to
    simultaneously exist at each generation.

   -crossover
    This defines the crossover rate. Fairest results are achieved with
    crossover rate ~0.95.

   -mutation
   -parents
   -selection
   -strategy
   -cache
   -history
  population($population)
    Set/get population.

  type($type)
    Set/get type of individuals. Currently it can be set to:

    "bitvector",
    "listvector",
    "rangevector",
    "combination".

  parents($parents)
    Set/get number of parents in *Roulette* crossover.

  init()
  evolve()
  history()
  getAvgFitness()
  getFittest()
  getHistory()
  generation()
  chart(%options)
    Generate a chart describing changes of min, mean, max scores in Your
    population. To satisfy Your needs, You can pass following options:

   -filename
    File to save a chart in (obligatory).

   -title
    Title of a chart (default: *Evolution*).

   -x_label
    X label (default: *Generations*).

   -y_label
    Y label (default: *Value*).

   -format
    Format of values, like "sprintf" (default: *'%.2f'*).

   -legend1
    Description of min line (default: *Min value*).

   -legend2
    Description of min line (default: *Mean value*).

   -legend3
    Description of min line (default: *Max value*).

   -width
    Width of a chart (default: *640*).

   -height
    Height of a chart (default: *480*).

   -font
    Path to font in (*.ttf format) to be used (default: none).

   -logo
    Path to logo (png/jpg image) to embed in a chart (default: none).

   In example:
            $ga->chart(-width => 480, height => 320, -filename => 'chart.png');

  save($file)
    Save current state of the genetic algorithm to a specified file.

  load($file)
    Load a state of the genetic algorithm from a specified file.

  as_array($chromosome)
    Return an array representing specified chromosome.

  as_value($chromosome)
    Return score of specified chromosome. Value of *chromosome* is
    calculated by fitness function.

  as_string($chromosome)
    Return string-representation of specified chromosome.

DOCUMENTATION
    At the moment for more information see documentation of AI::Genetic. It
    is compatible in most cases.

SUPPORT
    "AI::Genetic::Pro" is still under development and it has poor
    documentation (for now). However it is used in many production
    environments.

TODO
    More documentation.
    More tests.
    Warnings.

REPORTING BUGS
    When reporting bugs/problems please include as much information as
    possible. It may be difficult for me to reproduce the problem as almost
    every setup is different.

    A small script which yields the problem will probably be of help.

AUTHOR
    Strzelecki Łukasz <strzelec@rswsystems.com>

SEE ALSO
    AI::Genetic

COPYRIGHT
    Copyright (c) Strzelecki Łukasz. All rights reserved. This program is
    free software; you can redistribute it and/or modify it under the same
    terms as Perl itself.