Evolutionary Computation

A Genetic Algorithm is a problem solving technique based on the reproduction of living beings.

In a Genetic Algorithm there is a data structure which admits every possible solution to a problem.

Every possible set of data admitted by this structure is a solution to the problem. Some solutions will be better than others.

Finding the optimized solution means having solved the problem, therefore, Genetic Algorithms are really a searching method.

But it is a very special searching method in which the solutions to the problem are able to interproduce combining their characteristics and generating new solutions.

In every cycle the closest solutions to the objetive are chosen, and the others are eliminated. The chosen solutions will interproduce, allowing from time to time mutations or random modifications during reproduction.

Ejemplos de Vida is a program written in Visual Basic that allow us to study some artificial worlds. It includes a Genetic Algorithm (spanish) able to find one sentence written by the user. The program is free and the source code is avalable.

[ Introduction by Manu Herrán ]
[ http://www.redcientifica.com/gaia/ce/ce_i.htm ]

In this document it describes the bases, the operation, the programming and some options of the Evolutionary Algorithms.

But sometimes is not easy to aply Genetic Algorithms to solve one problem. This document explains some Variations on Genetic Algorithms.

Applictions of the Evolutionary Computation