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Multi-Objective Particle Swarm Optimization Algorithm Based on Enhanced ε-Dominance

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3 Author(s)
Jiang Hao ; Inst. of Inf. Eng., Xiangtan Univ. ; Zheng Jin-hua ; Chen liang-jun

In this paper, we describe a multi-objective particle swarm optimization algorithm (MOPSO) that incorporates the concept of the enhanced epsiv-dominance. We present this new concept to update the archive. The archiving technique can help us to maintain a sequence of well-spread solutions. A new particle update strategy and the mutation operator are shown to speed up convergence. To compare with the state-of-art MOEAs on a well-established suite of test problems, our new approach is simple constructed, and results indicate that it works effectively and has steady-state performance. It is confirmed from the results that the proposed method outperforms other methods

Published in:

Engineering of Intelligent Systems, 2006 IEEE International Conference on

Date of Conference:

22-23 April 2006