An Improved Particle Swarm Optimization Algorithm

Abstract:

Particle swarm optimization (PSO) algorithm has the ability of global optimization , but it often suffers from premature convergence problem, especially in high-dimensional multimodal functions. In order to overcome the premature property and improve the global optimization performance of PSO algorithm, this paper proposes an improved particle swarm optimization algorithm , called IPSO. The simulation results of eight unimodal/multimodal benchmark functions demonstrate that IPSO is superior in enhancing the global convergence performance and avoiding the premature convergence problem to SPSO no matter on unimodal or multimodal high-dimensional (100 real-valued variables) functions.

• Periodical: Applied Mechanics and Materials (Volumes 401-403)
• Pages: 1328-1335
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.401-403.1328
• Online since: September 2013
• Authors: Yu Feng Yu, Guo Li, Chen Xu
• Keywords: Acceleration Coefficients, Global Optimal Position, Inertia Weight, Particle Swarm, Search Space

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