计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (3): 28-29.DOI: 10.3778/j.issn.1002-8331.2009.03.007

• 博士论坛 • 上一篇    下一篇

新型多群体协同进化粒子群优化算法

牛 奔,李 丽,楚湘华   

  1. 深圳大学 管理学院,广东 深圳 518060
  • 收稿日期:2008-08-25 修回日期:2008-10-27 出版日期:2009-01-21 发布日期:2009-01-21
  • 通讯作者: 牛 奔

Novel multi-swarm cooperative particle swarm optimization

NIU Ben,LI Li,CHU Xiang-hua   

  1. School of Management,Shenzhen University,Shenzhen,Guangdong 518060,China
  • Received:2008-08-25 Revised:2008-10-27 Online:2009-01-21 Published:2009-01-21
  • Contact: NIU Ben

摘要: 在基本的MCPSO算法中除了主群与从群的信息交流,从群之间没有信息交流。为了解决这一问题,提出了一种具有中心交流机制的改进MCPSO算法,该策略可以实现各个从群之间的信息交流,从而加快算法收敛。仿真实验结果表明改进后的算法具有较好的求解精度和较快的收敛速度。

关键词: 多群体协同进化粒子群算法, 粒子群算法, 中心交流

Abstract: In original MCPSO,there is no information sharing among slave swarms except that the information of the best performing particle is broadcasted to the master swarm.To deal with this issue an improved MCPSO with Center Communication(MCPSO-CC) is proposed,where a center communication strategy is used to transfer the information among all the sub-swarms and accelerate the convergence.Experimental results show that MCPSO-CC achieves not only better solutions but also faster convergence.

Key words: Multi-swarm Cooperative Particle Swarm Optimizer(MCPSO), Particle Swarm Optimization(PSO), center communication