An improved PSO algorithm for constrained multiobjective optimization problems

Author

Ling, Haifeng ; Xiao, Yihong ; Zhou, Xianzhong ; Jiang, Xunlin

Author_Institution

Sch. of Manage. & Eng., Nanjing Univ., Nanjing, China

fYear

2011

fDate

27-29 June 2011

Firstpage

3859

Lastpage

3863

Abstract

In this paper, we propose an improved PSO algorithm for solving constrained multiobjective optimization problems (CMOP). The new algorithm is based on the ε tolerable constrained Pareto dominance and an effective nondominated solution set maintenance strategy. To improve the convergence and diversity of the Pareto-optimal set, the position and velocity adjustment strategy and the Pareto-optimal solution searching (gbest) method are presented in this paper. The simulation results of the typical mutiobjective optimization problems demonstrate the validity of the algorithm.

Keywords

Pareto optimisation; particle swarm optimisation; search problems; CMOP; PSO algorithm; Pareto dominance; Pareto-optimal set; Pareto-optimal solution searching method; constrained multiobjective optimization problem; nondominated solution set maintenance strategy; particle swarm optimization; position adjustment strategy; velocity adjustment strategy; Algorithm design and analysis; Maintenance engineering; Measurement; Object recognition; Optimization; Particle swarm optimization; Pareto-optimal solution searching; archive maintenance; constrained multiobjective particle swarm optimization(CMOPSO); multi-object problems(MOP);

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Service System (CSSS), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-9762-1

Type

conf

DOI

10.1109/CSSS.2011.5974695

Filename

5974695