A Ε-domination Based Multi-objective Particle Swarm Optimization

Author

Wang, Junnian ; Liu, Lanxia ; Liu, Deshun ; Yan, Yiduo

Author_Institution

Sch. of Inf. & Electr. Eng., Hunan Univ. of Sci. & Technol., Xiangtan, China

Volume

1

fYear

2010

fDate

13-14 March 2010

Firstpage

76

Lastpage

80

Abstract

A multi-objective particle swarm optimization algorithm based on Ε-dominance is proposed. The Ε-dominance is applied to update the external set in order to obtain the Pareto set with better distribution, and the dynamic adjustment strategy, which made the algorithm achieving the search and approximation to the Pareto set, is adopted in the iterative process of the Ε-Pareto solution set. Three benchmark cases were tested and the results show that this algorithm is much more efficient than the DNPSO.

Keywords

Pareto optimisation; iterative methods; particle swarm optimisation; set theory; Ε-Pareto solution set; Ε-domination based multiobjective particle swarm optimization; dynamic adjustment strategy; iterative process; Constraint optimization; Electric variables measurement; Evolutionary computation; Genetic algorithms; Iterative algorithms; Manufacturing automation; Mechatronics; Pareto optimization; Particle measurements; Particle swarm optimization; Ε-dominance; Multi-objective optimization; Pareto set; particle swarm optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on

Conference_Location

Changsha City

Print_ISBN

978-1-4244-5001-5

Electronic_ISBN

978-1-4244-5739-7

Type

conf

DOI

10.1109/ICMTMA.2010.797

Filename

5458827