Effects of scale-free and small-world topologies on binary coded self-adaptive CEA

Abstract

In this paper we investigate the properties of CEAs with populations structured as Watts-Strogatz small-world graphs and Albert-Barabási scale-free graphs as problem solvers, using several standard discrete optimization problems as a benchmark. The EA variants employed include self-adaptation of mutation rates. Results are compared with the corresponding classical panmictic EA showing that topology together with self-adaptation drastically influences the search. © Springer-Verlag Berlin Heidelberg 2006.