How can I make a Genetic Algorithm with BioJava?
With the introduction of the org.biojavax.ga package it is now possible to generate Genetic Algorithms using BioJava. Genetic Algorithms are a class of simulation, optimization or problem solving algorithms that attempt to evolve a solution to a problem. The solution being evolved is encoded as a ‘chromosome’ which is typically a binary string although other encodings are possible. At each generation (iteration) a population of chromosomes is available. Like real chromsomes they mutate and recombine with some frequency at each generation. Critically, after each round of potential mutation and recombination the chromosomes that encode the best solution are favoured for replication. Thus, there is a trend towards increasingly good solutions in the population. The example below demonstrates a very simple genetic algorithm constructed using the GA framework. The framework is designed to be very flexible and uses an interchangeable parts philosophy. The core interface is the GeneticAlgorith
