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

Authors:
Mario Giacobini;Mike Preuss;Marco Tomassini
Affiliations:
Information Systems Department, University of Lausanne, Switzerland;Systems Analysis Group, Computer Science Department, University of Dortmund, Germany;Information Systems Department, University of Lausanne, Switzerland
Venue:
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Year:
2006

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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.