DocumentCode
3227870
Title
A modified particle swarm optimization algorithm for reliability problems
Author
Zou, Dexuan ; Wu, Jianhua ; Gao, Liqun ; Wang, Xin
Author_Institution
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear
2010
fDate
23-26 Sept. 2010
Firstpage
1098
Lastpage
1105
Abstract
A modified particle swarm optimization (MPSO) algorithm is proposed to solve reliability problems in this paper. The MPSO modifies the velocity updating of particle swarm optimization (PSO) algorithm. For each particle, its personal best particle and the global best particle are separated to update its velocity, in other words, either its personal best particle or the global best particle is considered for velocity updating, and it is determined by a dynamic probability. In addition, a new inertia weight is introduced into the velocity updating, and it is used to balance the global search and local search. Based on a large number of experiments, the proposed algorithm has demonstrated stronger convergence and stability than the other two PSO algorithms on solving reliability problems. The results show that the MPSO can be an efficient alternative for solving reliability problems.
Keywords
particle swarm optimisation; probability; problem solving; reliability; search problems; dynamic probability; global search; inertia weight; particle swarm optimization; personal best particle; reliability problem; velocity updating; Bridges; Redundancy; Turbines; inertia weight; modified particle swarm optimization algorithm; particle swarm optimization algorithm; reliability problems; velocity updating;
fLanguage
English
Publisher
ieee
Conference_Titel
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-6437-1
Type
conf
DOI
10.1109/BICTA.2010.5645107
Filename
5645107
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