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Indexed by:会议论文
Date of Publication:2007-01-01
Included Journals:CPCI-S、CPCI-SSH
Page Number:8-12
Key Words:particle swarm algorithm; meta-heuristic; global optimization
Abstract:Particle swarm optimization is a relatively new category of meta-heuristic global optimization algorithms. It has been widely concerned by people because of its feasibility and effectiveness. In this paper, an adaptive particle swarm optimization algorithm, which introduces two adaptive acceleration factors in terms of the convergence speed and global search capability of the PSO algorithm, is proposed. A novel weighted function has been introduced and some particles are to be updated in a new way when the proposed algorithm traps in local optimum. The proposed algorithm is shown to enhance the convergence speed and global search capability on different benchmark optimization functions.