[1]孔 笋,陈增强.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[J].智能系统学报,2010,5(06):498-504.
 KONG Sun,CHEN Zeng-qiang.A new chaotic ant colony optimization algorithm and its application in a QoS multicast routing problem[J].CAAI Transactions on Intelligent Systems,2010,5(06):498-504.
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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(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第5卷
期数:
2010年06期
页码:
498-504
栏目:
出版日期:
2010-12-25

文章信息/Info

Title:
A new chaotic ant colony optimization algorithm and  its application in a QoS multicast routing problem
文章编号:
1673-4785(2010)06-0498-07
作者:
孔 笋陈增强
南开大学 信息技术科学学院,天津 300071
Author(s):
KONG Sun CHEN Zeng-qiang
College of Information Technical Science,Nankai University, Tianjin 300071, China
关键词:
QoS组播路由混沌算法蚁群算法参数优化
Keywords:
QoS multicast routing chaos optimization algorithm ant colony optimization algorithm parameter optimization
分类号:
TP183;TN949.291
文献标志码:
A
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.
Abstract:
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.

参考文献/References:

[1]WANG Z, CROWCROFT J. Quality of service for supporting multimedia applications[J]. IEEE Journal on Selected Areas in Communications, 1996, 14(7): 12281234.
[2]FEI X, LUO J Z, WU J Y, GU Q Q. QoS Routing based on genetic algorithm[J]. Computer Communications, 1999, 22(9): 13941399.
[3]王征应, 石冰心. 基于启发式遗传算法的QoS组播路由问题求解[J]. 计算机学报, 2001, 24(1): 5561.
WANG Zhengying, SHI Bingxin. Solving QoS multicast routing problem based on heuristic genetic algorithm[J]. Chinese Journal of Computers, 2001, 24(1): 5561
[4]孙文生, 刘泽民. 组播路由调度的神经网络方法[J]. 通信学报, 1998, 19(11): 16.
SUN Wensheng, LIU Zemin. Multicast routing based neural networks[J]. Journal on Communications,1998,19(11): 16.
[5]ZHANG Li, CAI Lianbo, LI Meng, WANG Fahui. A method for leastcost QoS multicast routing based on genetic simulated annealing algorithm[J]. Computer Communications, 2009, 32: 105110.
[6]李生红, 潘理, 诸鸿文, 刘泽民. 基于蚂蚁算法的组播路由调度方法[J]. 计算机工程, 2001, 27(4): 6365.
 LI Shenghong, PAN Li, ZHU Hongwen, LIU Zemin. Antalgorithm based multicast routing[J]. Computer Engineering, 2001, 27(4): 6365.
[7]孙力娟, 王汝传. 基于蚁群算法和遗传算法融合的QoS组播路由求解[J]. 电子学报, 2006, 34(8): 13911395.
SUN Lijuan, WANG Ruchuan. Solving QoS multicast routing problem based on the combination of ant colony algorithm and genetic algorithm[J]. Acta Electronica Sinica, 2006, 34(8): 13911395.
[8]WANG Y, XIE J. Ant colony optimization for multicast routing[C]//The 2000 IEEE AsiaPacific Conference on Circuits and Systems. [S.l.], 2000: 5457.
 [9]陈杰, 张洪伟. 基于自适应蚁群算法的QoS 组播路由算法[J].计算机工程, 2008, 34(13): 200203.
CHEN Jie, ZHANG Hongwei. QoS multicast routing algorithm based on adaptive ant colony algorithm[J]. Computer Engineering, 2008, 34(13): 200203.
[10]陈烨. 变尺度混沌蚁群优化算法[J]. 计算机工程与应用, 2007, 43(3): 6870.
CHEN Ye. Scaleable chaotic ant colony optimization[J]. Computer Engineering and Applications, 2007, 43(3):6870.
[11]高尚. 解旅行商问题的混沌蚁群算法[J]. 系统工程理论与实践, 2005, 25( 9): 100104.
 GAO Shang. Solving traveling salesman problem by chaos ant colony optimization algorithm[J]. System EngineeringTheory & Practice, 2005, 25( 9): 100104.
[12]DORIGO M, MANIEZZO V, COLORNI A. Ant system: optimization by a colony of cooperating Agent[J]. IEEE Transactions on Systems, Man and Cybernetics, 1996, 26(1): 2941.
[13]DORIGO M, GAMBARDELLA L M. Ant colony system:a cooperative learning approach to the traveling salesman problem[J].IEEE Transactions on Evolutionary Computation, 1997, 41(1): 5366.
[14]叶志伟, 郑肇葆. 蚁群算法中参数 设置的研究[J].武汉大学学报:信息科学版, 2004, 29(7): 597601.
YE Zhiwei, ZHENG Zhaobao. The research on the parameter in ant colony algorithm[J]. Geomatics and Information Science of Wuhan University, 2004, 29(7): 597601.
[15]吴春明, 陈治, 姜明. 蚁群算法中系统初始化及系统参数的研究[J]. 电子学报, 2006, 34(8): 15301532.
 WU Chunming, CHEN Zhi, JIANG Ming. The research on initialization of ants system and configuration of parameters for different TSP problems in ant algorithm[J]. Acta Electronica Sinica, 2006, 34(8): 15301532.
[16]朱庆保. 蚁群优化算法的收敛性分析[J]. 控制与决策,2006, 21(7): 763770. ZHU Qingbao. Analysis of convergence of ant colony optimization algorithms[J]. Control and Decision, 2006, 21(7): 763770.
[17]李兵, 蒋慰孙. 混沌优化方法及其应用[J]. 控制理论及应用, 1997, 14(4): 613615.
LI Bing, JIANG Weisun. Chaos optimization method and its application[J]. Control Theory & Applications, 1997, 14(4): 613615. [18]WAXMAN B M. Routing of multipoint connections[J]. IEEE Journal on Selected Areas in Communications, 1988, 6(9): 16171622.

相似文献/References:

[1]朱尚明,高大启.AntNet的多路径QoS路由算法研究[J].智能系统学报,2008,3(04):349.
 ZHU Shang-ming,GAO Da-qi.A multipath QoS routing algor ithm based on Ant Net[J].CAAI Transactions on Intelligent Systems,2008,3(06):349.

备注/Memo

备注/Memo:
收稿日期:2009-11-24.
基金项目:国家“863”计划资助项目(2009AA04Z132);国家自然科学基金资助项目(60774088).
通信作者:孔 笋.E-mail:ksuser@mail.nankai.edu.cn.
作者简介:
孔 笋,女,1982年生,博士研究生,主要研究方向为智能优化与鲁棒控制.
 陈增强,男,1964年生,教授,博士生导师,自动化系主任.主要研究方向为智能预测控制、混沌系统与复杂动态网络、多智能体系统控制.发表学术论文100多篇,其中在IEEE刊物上发表5篇(包括长文1篇),被SCI和EI检索100余篇.
更新日期/Last Update: 2011-03-03