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
Link To Document :
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