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Genetic Algorithm Series

[4] Genetic Algorithms: example code

In this post I present an implementation of the Classic Genetic Algorithm version, as an interactive widget, using binary representation of chromosome (we use 0/1 bits as a genes in chromosome, to encode variables). As you may know from previous post, this king of representation make operators easier to implement.

Genetic Algorithm Series

[2] Genetic Algorithms: Operators

Every genetic algorithm is built from 4 basic phases: crossover (expanding the population), mutation, evaluation and selection repeated in loop. There are many other steps that can be added and variations, but the classic genetic algorithm contains only that four. I also explain a basic terms from GA world.