全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

一种自适应最大最小蚁群算法

, PP. 688-691

Keywords: 蚁群算法,最大最小蚂蚁系统(MMAS),自适应,旅行商问题

Full-Text   Cite this paper   Add to My Lib

Abstract:

介绍蚁群算法结构、原理,分析其优点和不足,回顾它的几个重要的改进模型.为了改进它的不足,在最大最小蚂蚁系统的基础上,提出一种自适应改进模型.对其权重系数、状态转移规则及信息素增量方式等进行改进,实现自适应调整,提高算法性能.为了验证改进算法的性能,进行数值实验,结果显示本文所提改进算法的有效性.

References

[1]  Dorigo M, Maniezzo V, Colorni A. Positive Feedback as aSearch Strategy. Technical Report, 91016, Politecnico di Milano, Italy: University of Padova. Department of Information Engineering,1991
[2]  Dorigo M, Gambardella L M. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Trans on Evolutionary Computation, 1997, 1(1): 5366
[3]  Stutzle T, Hoos H H. MaxMin Ant System. Journal of Future Generation Computer Systems, 2000, 16 (9): 889914
[4]  Zhang Jihui, Xu Xinhe. A New Evolutionary Algorithm-Ant Colony Algorithm. Systems Engineering-Theory & Practice, 1999, 19(3): 8487 (in Chinese) (张纪会,徐心和.一种新的进化算法-蚁群算法.系统工程理论与实践, 1999, 19(3): 8487)
[5]  Wang Ying, Xie Jianying. An Adaptive Ant Colony Optimization Algorithm and Simulation. Journal of System Simulation, 2002, 14(1): 3133 (in Chinese) (王 颖,谢剑英.一种自适应蚁群算法及其仿真研究.系统仿真学报, 2002, 14(1): 3133)
[6]  Watanabe I, Matsui S. Improving the Performance of ACO Algorithms by Adaptive Control of Candidate Set // Proc of the Congress on Evolutionary Computation. Newport Beach, USA, 2003, Ⅱ: 13551362
[7]  Lu Yong, Zhao Guangzhou, Su Fanjun. Adaptive AntBased Dynamic Routing Algorithm // Proc of the 5th World Congress on Intelligent Control and Automation. Hangzhou, China, 2004, Ⅲ: 26942697
[8]  Ngo S H, Jiang Xiaohong, Horiguchi S. Adaptive Routing and Wavelength Assignment Using AntBased Algorithm // Proc of the IEEE International Conference on Networks. Singapore, Singapore, 2004: 482486
[9]  Qin Gangli, Yang Jiaben. An Improved Ant Colony Algorithm Based on Adaptively Adjusting Pheromone. Information and Control, 2002, 31(3): 198201,210 (in Chinese) (覃刚力,杨家本.自适应调整信息素的蚁群算法.信息与控制, 2002, 31(3): 198201,210)
[10]  Li Yong,Duan Zhengcheng.A New Ant System for TSPs. Computer Engineering and Applications, 2003, 39(17): 103106 (in Chinese) (李 勇,段正澄.动态蚁群算法求解TSP问题.计算机工程与应用, 2003, 39(17): 103106)
[11]  Gao Jian. Cluster Analysis Based on Parallel Ant Colony Adaptive Algorithm. Computer Engineering and Applications, 2003, 39(25): 7879,82 (in Chinese) (高 坚.基于并行多种群自适应蚁群算法的聚类分析.计算机工程与应用, 2003, 39(25): 7879,82)

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133