Improved multi-objective diversity control oriented genetic algorithm

Authors:
Theera Piroonratana;Nachol Chaiyaratana
Affiliations:
Department of Production Engineering, King Mongkut's Institute of Technology North Bangkok, Bangsue, Bangkok, Thailand;Research and Development Center for Intelligent Systems, King Mongkut's Institute of Technology North Bangkok, Bangsue, Bangkok, Thailand
Venue:
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Year:
2006

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Abstract

This paper presents an improved multi-objective diversity control oriented genetic algorithm (MODCGA-II). The improvement includes the introduction of an objective-domain diversity control operator, which is chromosome representation independent, and a solution archive. The performance comparison between the MODCGA-II, a non-dominated sorting genetic algorithm II (NSGA-II) and an improved strength Pareto evolutionary algorithm (SPEA-II) is carried out where different two-objective benchmark problems with specific multi-objective characteristics are utilised. The results indicate that the MODCGA-II solutions are better than the solutions generated by the NSGA-II and SPEA-II in terms of the closeness to the true Pareto optimal solutions and the uniformity of solution distribution along the Pareto front.