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On the convergence analysis and parameter selection in particle swarm optimization

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4 Author(s)
Yong-Ling Zheng ; Dept. of Control Sci. & Eng., Zhejiang Univ., Hangzhou, China ; Long-Hua Ma ; Li-Yan Zhang ; Ji-Xin Qian

A PSO with increasing inertia weight, distinct from a widely used PSO with decreasing inertia weight, is proposed in this paper. Far from drawing conclusions from sole empirical study or rule of thumb, this algorithm is derived from particle trajectory study and convergence analysis. Four standard test functions are used to confirm its validity finally. 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.

Published in:

Machine Learning and Cybernetics, 2003 International Conference on  (Volume:3 )

Date of Conference:

2-5 Nov. 2003