| θ-PSO： a new strategy of particle swarm optimization |
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| 作者姓名： | Wei-min ZHONG ;Shao-jun LI ;Feng QIAN |
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| 作者单位： | Wei-min ZHONG（State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China;Automation Institute, East China University of Science and Technology, Shanghai 200237, China） ;
Shao-jun LI（State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China;Automation Institute, East China University of Science and Technology, Shanghai 200237, China） ;
Feng QIAN（State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China;Automation Institute, East China University of Science and Technology, Shanghai 200237, China） ; |
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| 基金项目： | Project supported by the National Natural Science Foundation of China (Nos. 60625302 and 60704028), the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT0721), the 111 Project (No. B08021), the Major State Basic Research Development Program of Shanghai(No.07JC14016)and Shanghai Leading Academic Discipline Project(No.B504)of China |
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| 摘 要： | Particle swarm optimization （PSO） is an efficient, robust and simple optimization algorithm. Most studies are mainly concentrated on better understanding of the standard PSO control parameters, such as acceleration coefficients, etc. In this paper, a more simple strategy of PSO algorithm called θ-PSO is proposed. In θ-PSO, an increment of phase angle vector replaces the increment of velocity vector and the positions are decided by the mapping of phase angles. Benchmark testing of nonlinear functions is described and the results show that the performance of θ-PSO is much more effective than that of the standard PSO.
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| 关 键 词： | 群微粒最优化分析 相角 计算机技术 基准 |
| 收稿时间： | 6 November 2008 |
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