On the Choice of the Mutation Probability for the (1+1) EA

Abstract

When evolutionary algorithms are used for function optimization, they perform a heuristic search that is in fluenced by many parameters. Here,the choice of the mutation probability is investigated. It is shown for a non-trivial example function that the most recommended choice for the mutation probability 1 / n is by far not optimal,i.e., it leads to a superpolynomial running time while another choice of the mutation probability leads to a search algorithm with expected polynomial running time. Furthermore, a simple evolutionary algorithm with an extremely simple dynamic mutation probability scheme is suggested to overcome the difficulty of finding a proper setting for the mutation probability.