DocumentCode :
3165290
Title :
A Novel Self-organizing Particle Swarm Optimization based on Gravitation Field Model
Author :
Qi, Kang ; Lei, Wang ; Qidi, Wu
Author_Institution :
Tongji Univ., Shanghai
fYear :
2007
fDate :
9-13 July 2007
Firstpage :
528
Lastpage :
533
Abstract :
This paper presents a novel modified algorithm for particle swarm optimization (PSO). Initially, based on the inspiration of "universal gravitation" in nature, a kind of gravitation field model (GFM) applied to swarm intelligent optimization is designed. From the basis of GFM, a novel gravitational particle swarm optimization (GPSO) method is proposed, in which, a self-organizing field structure and the mass alterable principle are defined. The performance after a predefined number of generations of the proposed approach is validated through empirical simulations with well-known benchmarks by function optimization problem from the standard literature.
Keywords :
gravitation; particle swarm optimisation; self-adjusting systems; function optimization problem; gravitation field model; mass alterable principle; self-organizing particle swarm optimization; swarm intelligent optimization; universal gravitation; Birds; Cities and towns; Design optimization; Educational institutions; Marine animals; Optimization methods; Particle swarm optimization; Space technology; Topology; USA Councils; Gravitation field model; Gravitational particle swarm optimization; Mass alterable principle; Particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2007. ACC '07
Conference_Location :
New York, NY
ISSN :
0743-1619
Print_ISBN :
1-4244-0988-8
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2007.4282541
Filename :
4282541
Link To Document :
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