Tracking Changing Extrema with Modified Adaptive Particle Swarm Optimizer

Author

Shan, Shimin ; Deng, Guishi

Author_Institution

Inst. of Syst. Eng., Dalian Univ. of Technol.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3305

Lastpage

3309

Abstract

The purpose of this paper is to present a modified PSO (particle swarm optimization) algorithm applied to the complex dynamic environment. The algorithm presented is referred as improved adaptive particle swarm optimizer (IAPSO). A new variable-"activity factor" and distributed responding method are introduced by IAPSO. Several experiments based on complex dynamic environment were performed to test the performance of the algorithm. The dynamic environment used is generated by the dynamic function #1 (DF1). Furthermore, additional feature of setting reinitializing threshold randomly is put to the basic IAPSO to improve its performance. The experimental results indicate that IAPSO is more adaptive in complex dynamic environment than adaptive particle swarm optimizer (APSO) and other PSO-based algorithms

Keywords

particle swarm optimisation; activity factor; changing extrema; distributed responding method; dynamic function; improved adaptive particle swarm optimizer; particle swarm optimization; Casting; Heuristic algorithms; Modeling; Monitoring; Optimization methods; Particle swarm optimization; Particle tracking; Performance evaluation; Systems engineering and theory; Testing; APSO; DF1; Dynamic Environment; PSO;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712979

Filename

1712979