计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (31): 53-55.DOI: 10.3778/j.issn.1002-8331.2009.31.017

• 研究、探讨 • 上一篇    下一篇

基于boltzmann选择策略的人工蜂群算法

丁海军,冯庆娴   

  1. 河海大学(常州) 计算机及信息工程学院,江苏 常州 213022
  • 收稿日期:2008-06-25 修回日期:2008-10-16 出版日期:2009-11-01 发布日期:2009-11-01
  • 通讯作者: 丁海军

Artificial bee colony algorithm based on Boltzmann selection policy

DING Hai-jun,FENG Qing-xian   

  1. College of Computer & Information Engineering,Hohai University,Changzhou,Jiangsu 213022,China
  • Received:2008-06-25 Revised:2008-10-16 Online:2009-11-01 Published:2009-11-01
  • Contact: DING Hai-jun

摘要: 人工蜂群算法(ABC)是一种基于蜜蜂行为的优化算法。基于Boltzmann选择机制提出了一种改进的人工蜂群算法(BABC)用来优化多变量函数。BABC算法使初始群体均匀化;采用Boltzmann选择机制来代替轮盘赌以防止算法过早收敛。经过实验证明,该算法具有全局搜索能力好,收敛速度快,参数设置少等优点。

关键词: 人工蜂群算法(ABC), 群集智能, 进化计算, 函数优化

Abstract: Artificial Bee Colony(ABC) algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm.In this work,an improved ABC algorithm(BABC) is proposed based on the Boltzmann selection mechanism and used for optimizing multivariable functions.BABC algorithm makes the initial group symmetrical.To avoid premature,this method applies Boltzmann selection mechanism instead of roulette.The experimental results have shown that,the good performance of the algorithm such as avoiding local optima,quick convergence and fewer parameters.

Key words: Artificial Bee Colony(ABC), swarm intelligence, evolutionary, function optimization

中图分类号: