A Novel Multiobjective Evolution Strategy: Design for Adaptive Balance Between Proximity and Diversity

Authors:
Yang Shu Min;Ju Xing Xiang
Affiliations:
Wuhan University, China;Huizhou Water conservancy & hydropower Construction. Co. Ltd., China
Venue:
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 6 - Volume 07
Year:
2005

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Abstract

This paper proposes a new multi-objective evolutionary approach to investigate the adaptive balance between proximity and diversity. The proposed algorithm combines several elements such as Gaussian and Cauchy mutations, a nondominance selection, and a dynamic external archive. Numerical experimentations are presented using three benchmark instances, and results are compared with three state-of-the-art algorithms. It is drawn that our algorithm is superior to some extent in term of finding a near-optimal, well-extended and uniformly diversified Pareto optimal front.