3. Algorithms

The algorithms module is intended to contain some specific algorithms in order to execute very common evolutionary algorithms. The method used here are more for convenience than reference as the implementation of every evolutionary algorithm may vary infinitly. Most of the algorithms in this module use operators registered in the toolbox with the same keywords, mate() for crossover, mutate() for mutation, select() for selection and evaluate() for evaluation.

You are encouraged to write your own algorithms in order to make them do what you realy them to do.

eap.algorithms.eaSimple(toolbox, population, cxpb, mutpb, ngen[, halloffame])

This algorithm reproduce the simplest evolutionary algorithm.

eap.algorithms.eaMuPlusLambda(toolbox, population, mu, lambda_, cxpb, mutpb, ngen[, halloffame])

This is the evolutionary algorithm, ...

eap.algorithms.eaMuCommaLambda(toolbox, population, mu, lambda_, cxpb, mutpb, ngen[, halloffame])

This is the evolutionary algorithm

eap.algorithms.eaSteadyState(toolbox, population, ngen[, halloffame])

The is the steady-state evolutionary algorithm