Species merging and splitting for efficient search in Coevolutionary algorithm

Abstract

Coevolutionary algorithm takes advantage of the reduced search space by evolving species associated with subsets of variables independently but cooperatively. In this paper we propose an efficient Coevolutionary algorithm combining species splitting and merging together. Our algorithm conducts efficient local search in the reduced search space by splitting species for independent variables while it conducts global search by merging species for interdependent variables. We have experimented the proposed algorithm with several benchmarking function optimization problems and the inventory control problem, and have shown that the algorithm outperforms existing coevolutionary algorithms. © Springer-Verlag Berlin Heidelberg 2004.