计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (18): 116-118.DOI: 10.3778/j.issn.1002-8331.2010.18.036

• 网络、通信、安全 • 上一篇    下一篇

改进型量子蚁群算法求解QoS单播路由

曹建国1,陶 亮2   

  1. 1.安徽工贸职业技术学院,安徽 淮南 232007
    2.安徽大学 计算智能与信号处理教育部重点实验室,合肥 230039
  • 收稿日期:2009-11-04 修回日期:2010-04-29 出版日期:2010-06-21 发布日期:2010-06-21
  • 通讯作者: 曹建国

Improved quantum ant colony algorithm for QoS unicast routing algorithm

CAO Jian-guo1,TAO Liang2   

  1. 1.Anhui Industry & Trade Vocational and Technical College,Huainan,Anhui 232007,China
    2.Key Lab of Intelligent Computing & Signal Processing,Ministry of Education,Anhui University,Hefei 230039,China
  • Received:2009-11-04 Revised:2010-04-29 Online:2010-06-21 Published:2010-06-21
  • Contact: CAO Jian-guo

摘要: 针对遗传以及蚁群算法在求解QoS单播路由问题时收敛速度慢和易于陷入局部最优的问题。采用量子蚁群算法求解QoS单播路由,采用量子旋转门实现蚂蚁的移动,用量子非门来实现蚂蚁位置的变异,同时为了确保算法不陷于局部最优,对量子蚁群算法做了改进,并进行了对比实验。实验表明该算法不但克服了遗传以及蚁群算法的易限于局部最优解的缺陷,在收敛速度上也优于相关算法,能较好地解决QoS单播路由问题。

关键词: QoS单播路由, 量子蚁群, 蚁群算法, 路由

Abstract: For the genetic algorithm and ant colony algorithm solving QoS unicast routing problem is easily trapped into local optimization and has slow convergence.Ant colony algorithm is used to solve the quantum QoS unicast routing,quantum revolving doors are used to complete the ant movement,quantum non-gates are used to realize ant location variation,and in order to ensure the algorithm is not trapped in local optimum,quantum ant colony algorithm is improved,and conductes comparative experiments related to the simulation.Experiments show that this algorithm not only overcomes the defects that the genetic algorithm and ant colony algorithm is easily trapped into local optimization and the convergence speed is also better than the ant colony algorithm.The QoS unicast routing problem can be better solved.

Key words: QoS unicast routing, quantum ant colony, ant colony algorithm, routing

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