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
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;
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
DOI :
10.1109/BICTA.2010.5645107