Intelligent particle swarm optimization in multiobjective optimization

Author

Xiao-Hua, Zhang ; Hong-Yun, Meng ; Li-cheng, Jiao

Author_Institution

Inst. of Intelligent Inf. Process., Xidian Univ., Xi´´an

Volume

1

fYear

2005

fDate

5-5 Sept. 2005

Firstpage

714

Abstract

How to find a sufficient number of uniformly distributed and representative Pareto optimal solutions is very important for multiobjective optimization (MO) problems. A new model for particle swarm optimization is constructed firstly, and then an intelligent particle swarm optimization (IPSO) for MO problems is proposed based on AER (agent-environment-rules) model, in which competition operator and clonal selection operator are designed to provide an appropriate selection pressure to propel the swarm population towards the Pareto-optimal front. The quantitative and qualitative comparisons indicate that the proposed approach is highly competitive and that can be considered as a viable alternative to solve MO problems

Keywords

Pareto optimisation; multi-agent systems; particle swarm optimisation; Pareto optimal solution; agent-environment-rules model; clonal selection operator; competition operator; intelligent particle swarm optimization; multiobjective optimization; Birds; Filters; Heuristic algorithms; Intelligent agent; Pareto optimization; Particle swarm optimization; Proposals; Propulsion;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2005. The 2005 IEEE Congress on

Conference_Location

Edinburgh, Scotland

Print_ISBN

0-7803-9363-5

Type

conf

DOI

10.1109/CEC.2005.1554753

Filename

1554753