Performance scalability of a cooperative coevolution multiobjective evolutionary algorithm

Tse , Guan Tan and Teo, Jason Tze Wi and Hui, Keng Lau (2007) Performance scalability of a cooperative coevolution multiobjective evolutionary algorithm. In: International Conference on Computational Intelligence and Security, 15-19 December 2007 , Harbin, China.

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Abstract

Recently, numerous Multiobjective Evolutionary Algorithms (MOEAs) have been presented to solve real life problems. However, a number of issues still remain with regards to MOEAs such as convergence to the true Pareto front as well as scalability to many objective problems rather than just bi-objective problems. The performance of these algorithms maybe augmented by incorporating the coevolutionary concept. Hence, in this paper, a new algorithm for multiobjective optimization called SPEA2-CC is illustrated. SPEA2-CC combines an MOEA, Strength Pareto Evolutionary Algorithm 2 (SPEA2) with Cooperative Coevolution (CC). Scalability tests have been conducted to evaluate and compare the SPEA2-CC against the original SPEA2 for seven DTLZ test problems with a set of objectives (3 to 5 objectives). The results show clearly that the performance scalability of SPEA2-CC was significantly better compared to the original SPEA2 as the number of objectives becomes higher.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Computer Science, Artificial Intelligence, Computer Science, Software Engineering, Computer Science, Theory & Methods
Subjects: ?? QA150-272.5 ??
Divisions: SCHOOL > School of Engineering and Information Technology
Depositing User: Unnamed user with email storage.bpmlib@ums.edu.my
Date Deposited: 26 Sep 2011 09:36
Last Modified: 20 Mar 2015 01:52
URI: http://eprints.ums.edu.my/id/eprint/1161

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