GA - PHP Classes

Name:	GA Support forum
Base name:	`ga`
Description:	Generic genetic algorithms base implementation
Version:	`-`
Required PHP version:	`-`
License:	GNU General Public License (GPL)
All time users:	2057 users
All time rank:	1294
Week users:	9 users
Week rank:	801

	Author		Groups		Detailed description

	User ratings		Applications		Related links		Files

Author

Name:	Rafael Pinto `<e-mail contact>`
Published packages:	4 Browse this author's classes
Country:	Brazil - PHP jobs in Brazil
Home page:	`http://www.inf.ufrgs.br/~rcpinto`
Age:	27
All time rank:	265
Week rank:	452

Innovation Award

September 2005
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Genetic Algorithms are computing algorithms used to find approximate solutions to optimization problems. These problems consist in determining sequences of data that may provide better results depending on the order of the data elements.

The genetic algorithms are inspired in the evolutionary biology theories that determine that on each generation the individuals tend to evolve and address better the problems that challenge their survival.

Evolution happens after performing slight mutations to the chromosome sequence of the individuals of the current generation. The best fit individuals will survive and become the origin of the next generation.

In computing genetic algorithms can be used to optimize solutions for problems like job scheduling, artificial intelligence for computer operated game characters, compact file storage, etc..

This class can be used as a framework to implement PHP applications that can benefit of the use of genetic algorithms.

Manuel Lemos

Groups

	Algorithms	Numerical and statistical algorithms	View top rated classes
	Artificial intelligence	Automation of tasks using human-like intelligence	View top rated classes

Detailed description

This class implements base methods to apply genetic algorithms to arbitrary subjects.

Its functions can be call instantiating a class object or called static methods.

The class can perform several types of generic algorithm operations like crossover, mutation, selection and death over populations of any objects of the same class.

It can be used as a base implementation of genetic algorithms to solve many types of problems on which the best solution may be found through natural selection.

User ratings

Ratings	Utility	Consistency	Documentation	Examples	Tests	Videos	Overall	Rank
All time:	`Sufficient (75.0%)`	`Good (91.7%)`	`-`	`Good (83.3%)`	`-`	`-`	`Not sure (55.0%)`	1023
Month:	Not yet rated by the users

Applications that use this class

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Files

File	Role	Description
`ga.php`	Class	GA Class
`gaExample1.php`	Example	GA Example 1
`gaExample2.php`	Example	GA Example 2

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Class: GA