An Improved Particle Swarm Optimization Algorithm Based on Centroid and Exponential Inertia Weight

Shouwen Chen, Zhuoming Xu, Yan Tang and Shun Liu

Mathematical Problems in Engineering, 2014, vol. 2014, 1-14

Abstract:

Particle swarm optimization algorithm (PSO) is a global stochastic tool, which has ability to search the global optima. However, PSO algorithm is easily trapped into local optima with low accuracy in convergence. In this paper, in order to overcome the shortcoming of PSO algorithm, an improved particle swarm optimization algorithm (IPSO), based on two forms of exponential inertia weight and two types of centroids, is proposed. By means of comparing the optimization ability of IPSO algorithm with BPSO, EPSO, CPSO, and ACL-PSO algorithms, experimental results show that the proposed IPSO algorithm is more efficient; it also outperforms other four baseline PSO algorithms in accuracy.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:976486

DOI: 10.1155/2014/976486

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