A co-evolutionary particle swarm optimization-based method for multiobjective optimization

Authors:
Hong-yun Meng;Xiao-hua Zhang;San-yang Liu
Affiliations:
Dept.of Applied Math., XiDian University, Xian, China;Institute of Intelligent Information Processing, XiDian University, Xian, China;Dept.of Applied Math., XiDian University, Xian, China
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

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Abstract

A co-evolutionary particle swarm optimization is proposed for multiobjective optimization (MO), in which co-evolutionary operator, competition mutation operator and new selection mechanism are designed for MO problem to guide the whole evolutionary process. By the sharing and exchange of information among particles, it can not only shrink the searching region but maintain the diversity of the population, avoid getting trapped in local optima which is proved to be effective in providing an appropriate selection pressure to propel the population towards the Pareto-optimal Front. Finally, the proposed algorithm is evaluated by the proposed quality measures and metrics in literatures.