Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (25): 1-4.DOI: 10.3778/j.issn.1002-8331.2010.25.001

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Research on representative algorithms of swarm intelligence

YU Jian-ping1,ZHOU Xin-min2,CHEN Ming1   

  1. 1.College of Mathematics and Computer Science,Hunan Normal University,Changsha 410081,China
    2.Information School,Hunan University of Commerce,Changsha 410205,China
  • Received:2010-06-13 Revised:2010-07-28 Online:2010-09-01 Published:2010-09-01
  • Contact: YU Jian-ping


余建平1,周新民2,陈 明1   

  1. 1.湖南师范大学 数学与计算机科学学院,长沙 410081
    2.湖南商学院 信息学院,长沙 410205
  • 通讯作者: 余建平

Abstract: Swarm intelligence has the characteristics of the collective intelligence emerging from the cooperation of individuals with little intelligence,which provides basic solutions for the complicated distributed problems under the conditions without central control and global model.The potential features of the parallel and distribution make the swarm intelligence an important direction in computer domain.After introducing the basic swarm intelligence model,two kinds of the swarm intelligence-based representative algorithms——The particle swarm optimization and the ant colony optimization are detailed and the characteristics of them are compared.Finally,the future research aspects of the swarm intelligence are emphatically suggested,especially the broad-applied ant algorithms.

摘要: 群体智能是指无智能的或具有简单智能的个体通过协作表现出群体智能行为的特性,它在没有集中控制且不提供全局模型的前提下,为寻找复杂的分布式问题求解方案提供了基础。群体智能潜在的并行性和分布式特征使之成为计算机领域一个重要的研究方向。在介绍群体智能模型的基础上,分别对基于该模型的蚁群优化算法和粒子群优化算法这两类代表性算法进行较为详尽的归纳阐述并进行比较,最后就目前应用最为广泛的蚁群算法对群体智能的发展趋势进行展望。

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