DocumentCode
2998315
Title
Empirical study of particle swarm optimizer with an increasing inertia weight
Author
Zheng, Yong-ling ; Ma, Long-hua ; Zhang, Li-yan ; Qian, Ji-Xin
Author_Institution
Dept. of Control Sci. & Eng., Zheijiang Univ., Hangzhou, China
Volume
1
fYear
2003
fDate
8-12 Dec. 2003
Firstpage
221
Abstract
A PSO with increasing inertia weight, distinct from a widely used PSO with decreasing inertia weight, is proposed in this paper. Four standard test functions with asymmetric initial range settings are used to confirm its validity. From the experiments, it is clear that a PSO with increasing inertia weight outperforms the one with decreasing inertia weight, both in convergent speed and solution precision, with no additional computing load compared with the PSO with a decreasing inertia weight.
Keywords
artificial life; convergence; evolutionary computation; optimisation; search problems; asymmetric initial range settings; computing load; convergent speed; inertia weight; particle swarm optimizer; standard test functions; Benchmark testing; Birds; Control systems; Equations; Insects; Integrated circuit modeling; Particle swarm optimization; Performance analysis; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN
0-7803-7804-0
Type
conf
DOI
10.1109/CEC.2003.1299578
Filename
1299578
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