PHP Classes

PHP Genetic Algorithm Methods: Implements crossover, mutation and inversion

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genetic_algorithm 1.0.0Freeware5Algorithms, PHP 5, Biology, Artificia...
Description 

Author

Sasan Nobakht

This class implements crossover, mutation and inversion genetic algorithm methods.

It takes several parameters to configure values that define how the execution of the genetic algorithm methods are implemented to optimize the order of a set of entities known as population.

Each method uses several techniques in order to produce their offsprings. Theses techniques are:

1. Crossover

1.1 Single Point Crossover
1.2 Two Points Crossover
1.3 Uniform Crossover
1.4 Ring Crossover

2. Mutation

2.1 Bit Flip Mutation
2.2 Random Resetting
2.3 Swap Mutation
2.4 Scramble Mutation
2.5 Inversion Mutation
2.6 Insertion Mutation

3. Inversion

3.1 Inversion all chromosome

The class produces new population generations and returns the results as a binary encoded string.

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Name: Sasan Nobakht <contact>
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Example

<?php
set_time_limit (0);
ini_set('memory_limit', '1024M'); // or you could use 1G

require_once 'Genetic.class.php';
$Genetic = new GeneticAlgorithm (
    array(
        'Goal' => 'AI',

        'PopulationSize' => 200, // Size of Population In Each Generation
        'MaxIteration' => 400,
        'GenerationGap' => 100, // Percent of Checking Fitness Function on Population
        'Age' => 6,
        'Strategy' => 'M,L',
        'Elitism' => true,

        'MinAcceptableFitness' => 0,
        'CodingType' => 'Binary',

        'CrossOverRate' => 100, // Percent
        'MutationRate' => 100, // Percent
        'InversionRate' => 100, // Percent

        'CrossOverTechnique' => 1,
        'MutationTechnique' => 1,

        'SingleCrossOverPoint' => 3,
        'TwoCrossOverPoint1' => 2,
        'TwoCrossOverPoint2' => 4,
        'UniformCrossOverRatio' => 50, // Percent
        'RingCrossOverCuttingPoint' => 3,
        'RingCrossOverCuttingByRandom' => false
    )
);

$Genetic->Run();

echo "<pre>";
print_r(array_reverse($Genetic->Generations));
echo "</pre>";

Screenshots (6)  
  • Standalone
  • Chromosome.png
  • GenerationTable.png
  • Result
  • Form.png
  • Intro.png
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Accessible without login Plain text file Ajax.php Example Load Ajax Result
Accessible without login Plain text file Genetic.class.php Class Main Genetic Algorithm Class
Accessible without login Plain text file index.php Aux. Demo Mainpage
Accessible without login Plain text file StandaloneExample.php Example Standalone Example

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  Related pages  
Front-rear crossover: A new crossover technique for solving a trap problem
A Novel Crossover Operator for Genetic Algorithms: Ring Crossover