Experimental analysis of the aging operator for static and dynamic optimisation problems

Authors:
Mario Castrogiovanni;Giuseppe Nicosia;Rosario Rascunà
Affiliations:
Department of Mathematics and Computer Science, University of Catania, Catania, Italy;Department of Mathematics and Computer Science, University of Catania, Catania, Italy;Department of Informatics, University of Sussex, Falmer, Brighton, United Kingdom
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Year:
2007

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Abstract

This work presents an analysis of the static Aging operator for different evolutionary algorithms: two immunological algorithms (OptIA and Clonalg), a standard genetic algorithm SGA, and Differential Evolution (DE) algorithm. The algorithms were tested against standard benchmarks in both unconstrained and dynamic optimisation problems. This work analyses whether the aging operator improves the results when applied to evolutionary algorithms. With the exception of DE, the results report that every algorithm shows an improvement in performance when used in combination with Aging.