Improving PSO-based multiobjective optimization using competition and immunity clonal

Authors:
Xiaohua Zhang;Hongyun Meng;Licheng Jiao
Affiliations:
Institute of Intelligent Information Processing, Xidian University, Xian, China;Dept.of Applied Math, Xidian University, Xian, China;Institute of Intelligent Information Processing, Xidian University, Xian, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

An Intelligent Particle Swarm Optimization (IPSO) for MO problems is proposed based on AER (Agent-Environment-Rules) model, in which Competition and Clonal Selection operator are designed to provide an appropriate selection pressure to propel the swarm population towards the Pareto-optimal front. Simulations and comparison with NSGA-II and MOPSO indicate that IPSO is highly competitive.