[1]WANG Yan,ZENG Jian-chao.A survey of a multiobjective particle swarm optimization algorithm[J].CAAI Transactions on Intelligent Systems,2010,5(5):377-384.[doi:10.3969/j.issn.1673-4785.2010.05.001]
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A survey of a multiobjective particle swarm optimization algorithm

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 5 Page number: 377-384 Column: 综述 Public date: 2010-10-25
Title:
A survey of a multiobjective particle swarm optimization algorithm
Author(s):
WANG Yan1; 2;  ZENG Jian-chao2
(1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; 2.Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan 030024, China)
Keywords:
multi-objective optimization;  particle swarm optimization;  non-dominated solutions;  archive;  diversity
CLC:
TP18
DOI:
10.3969/j.issn.1673-4785.2010.05.001
Abstract:
Particle swarm optimization (PSO) algorithms have been widely studied and approved as effective multi-objective paper optimizers. In this paper， first of all multi-objective problems were formally described, and the difference between a PSO and genetic algorithm (GA) was introduced. Then the taxonomy of current multi-objective PSO (MOPSO) algorithms, which include aggregate functions, sorting based on objective functions, sub-population methods, Pareto dominated based algorithms, and other algorithms, was presented. Additionally, the main ideas, features, and representative algorithms of each approach were analyzed. Secondly, hot topics in MOPSO algorithms such as selecting non-dominated solutions, pruning archive sets, maintaining the diversity of the solutions set, and selecting both the best personal and global solutions were discussed on the basis of which all typical algorithms were compared. Finally, several viewpoints for the future research of MOPSO were proposed according to the present studies.
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