Genetic Algorithms with Java (JGAP)

http://jcraane.blogspot.com/2009/02/introduction-to-genetic-algorithms-with.html

http://code.google.com/p/jc-examples/

Out of interest I am familiarizing myself in genetic algorithms, in short GA. My interest in GA came when I first heard about the JGAP project. As mentioned on the project's site "JGAP (pronounced "jay-gap") is a Genetic Algorithms and Genetic Programming component provided as a Java framework.". For a newcomer I found it difficult to get a good overview about all the concepts introduced in genetic algorithms. Before diving into JGAP, I think it is essential that these concepts are well understood. This post is an introduction to genetic algorithms (GA) with JGAP and is explained with a concrete example. In one of my next posts I will demonstrate solving a problem with genetic programming (GP).

So what is a genetic algorithm? Given is the following definition from John R. Koza:

The genetic algorithm is a probabilistic search algorithm that iteratively transforms a set (called a population) of mathematical objects (typically fixed-length binary character strings), each with an associated fitness value, into a new population of offspring objects using the Darwinian principle of natural selection and using operations that are patterned after naturally occurring genetic operations, such as crossover (sexual recombination) and mutation.