一种新的混沌蚁群算法及其在QoS组播路由优化问题中的应用  

A new chaotic ant colony optimization algorithm and its application in a QoS multicast routing problem

作　　者：孔笋[1] 陈增强[1] 

机构地区：[1]南开大学信息技术科学学院,天津300071

出　　处：《智能系统学报》2010年第6期498-504,共7页CAAI Transactions on Intelligent Systems

基　　金：国家"863"计划资助项目(2009AA04Z132);国家自然科学基金资助项目(60774088)

摘　　要：基于QoS的组播路由问题是通过发现具有某种相关性能约束的最佳组播树,来更好地利用网络资源以支持应用的QoS需求,作为以QoS为中心的网络体系结构中不可缺少的组成部分,目前已成为网络研究领域的重要内容和热点问题.针对多约束条件下的QoS组播路由问题,提出一种新的混沌蚁群算法.该算法基于传统的蚁群算法所存在的不足,利用混沌优化算法对蚁群算法的运行参数进行动态地优化选择,自适应地改进了全局搜索能力和收敛性.仿真实验结果表明,混沌蚁群算法比该文提到的遗传算法及蚁群算法在解决多约束组播路由问题上具有更好的性能.QoS-based multicast routing can take advantage of network resources to support an application with QoS requirements by searching for the optimal multicast tree with some performance constraints.This problem,which is an indispensable part of QoS-centered network architecture,has become an important issue in network domain research.A new chaotic ant colony optimization algorithm was proposed for a multi-constrained QoS multicast routing problem.To overcome the deficiencies of traditional ant colony algorithms,this algorithm uses a chaotic optimization algorithm to dynamically select parameters of the ant colony algorithm and improves global searching and convergence abilities.Simulation results show that this chaotic ant colony optimization algorithm performs better than the genetic algorithm and ant colony optimization mentioned here for solving a QoS multicast routing problem with multiple constraints.

关 键 词：QOS 组播路由 混沌算法 蚁群算法 参数优化 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TN949.291[自动化与计算机技术—控制科学与工程]