Modal mutations in evolutionary algorithms

Modal mutation schemes for evolutionary algorithms as a generalization of the breeder genetic algorithm mutation scheme are introduced and analyzed for multimodal continuous parameter optimization problems.

Abstract

With this paper modal mutation schemes for evolutionary algorithms as a generalization of the breeder genetic algorithm mutation scheme are introduced and analyzed for multimodal continuous parameter optimization problems. A new scaling rule for multiple mutations is formalized and compared with a new step-size scaling for evolution strategies. A performance comparison of the multivalued evolutionary algorithm with modal mutations with recently published results concerning the performance of Bayesian/sampling and very fast simulated reannealing techniques for global optimization is given.>