Real coded clonal selection algorithm for unconstrained global optimization using a hybrid inversely proportional hypermutation operator

Authors:
Vincenzo Cutello;Giuseppe Nicosia;Mario Pavone
Affiliations:
University of Catania, Catania, Italy;University of Catania, Catania, Italy;University of Catania, Catania, Italy
Venue:
Proceedings of the 2006 ACM symposium on Applied computing
Year:
2006

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Abstract

Numerical optimization of given objective functions is a crucial task in many real-life problems. This paper introduces a new immunological algorithm for continuous global optimization problems, called opt-IMMALG; it is an improved version of a previously proposed clonal selection algorithm, using a real-code representation and a new Inversely Proportional Hypermutation operator.We evaluate and assess the performance of opt-IMMALG and several others algorithms, namely opt-IA, PSO, arPSO, DE, and SEA with respect to their general applicability as numerical optimization algorithms. The experiments have been performed on 23 widely used benchmark problems.The experimental results show that opt-IMMALG is a suitable numerical optimization technique that, in terms of accuracy, outperforms the analyzed algorithms in this comparative study. In addition it is shown that opt-IMMALG is also suitable for solving large-scale problems.