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.

Full text not available from this repository.


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)
Keyword: Computer Science, Artificial Intelligence, Computer Science, Software Engineering, Computer Science, Theory & Methods
Subjects: Q Science > QA Mathematics > QA1-939 Mathematics > QA150-272.5 Algebra
Department: SCHOOL > School of Engineering and Information Technology
Depositing User: ADMIN ADMIN
Date Deposited: 26 Sep 2011 17:36
Last Modified: 20 Mar 2015 09:52

Actions (login required)

View Item View Item