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计算机工程 ›› 2008, Vol. 34 ›› Issue (2): 193-195. doi: 10.3969/j.issn.1000-3428.2008.02.064

• 人工智能及识别技术 • 上一篇    下一篇

基于文化进化的并行粒子群算法

马慧民1.2,叶春明2   

  1. (1. 上海电机学院经济管理学院,上海 200245;2. 上海理工大学管理学院,上海 200093)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-01-20 发布日期:2008-01-20

Parallel Particle Swarm Optimization Algorithm Based on Cultural Evolution

MA Hui-min1.2, YE Chun-ming2   

  1. (1. Business School, Shanghai Dianji University, Shanghai 200245;2 Business School, University of Shanghai for Science and Technology, Shanghai 200093)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-01-20 Published:2008-01-20

摘要: 为了改善粒子群算法对大规模问题求解的性能,提出一种基于文化进化的并行粒子群算法,阐述了该算法的原理和具体实施方案。选取背包问题作为算法的应用对象,通过对仿真实例进行计算和结果比较,表明该算法在最优值、求解速度、稳定性等方面具有较好的 效果。

关键词: 文化进化, 并行, 粒子群算法, 背包问题

Abstract: A Parallel Particle Swarm Optimization algorithm based on Cultural Evolution (PPSOCE) is proposed to improve the performance of particle swarm optimization for application to large-scale problem. The detailed realization of the method is illustrated. The example of other literatures is computed. By comparison result, it can be found that this proposed algorithm illustrates its higher searching efficiency and better stability.

Key words: cultural evolution, parallel, particle swarm optimization, knapsack problems

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