Location Algorithm of Logistics Distribution Facilities Based on BIRCH Clustering
CSTR:
Author:
  • Article
  • | |
  • Metrics
  • |
  • Reference [9]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    The location of logistics distribution facilities has a great impact on logistics costs and deliver time. Its features include:the interaction between the location of delivery facilities and the delivery route planning, the multi-level location, the balance of shipment quantity, etc. Through the analysis of the characteristics of logistics distribution facilities location, a BIRCH-based logistics distribution facility location algorithm, a combination of BIRCH clustering algorithm and Dijkstra-based gravity center method, is designed to provide a better location and save long-term operating costs.

    Reference
    1 关菲, 张强. 模糊多目标物流配送中心选址模型及其求解算法. 中国管理科学, 2013, 21(S1):57-62.
    2 程珩, 牟瑞芳. 物流配送中心选址的重心法探讨. 交通运输工程与信息学报, 2013, 11(1):91-95.[doi:10.3969/j.issn.1672-4747.2013.01.017]
    3 石兆. 物流配送选址-运输路径优化问题研究[博士学位论文]. 长沙:中南大学, 2014.
    4 Zhang T, Ramakrishnan R, Livny M. BIRCH:an efficient data clustering method for very large databases. ACM SIGMOD conference, 1999, 25(2):103-114.[doi:10.1145/233269.233324]
    5 韦相. 基于密度的改进BIRCH聚类算法. 计算机工程与应用, 2013, 49(10):201-205.[doi:10.3778/j.issn.1002-8331.1112-0567]
    6 Karatas M, Yakıcı E. An iterative solution approach to a multi-objective facility location problem. Applied Soft Computing, 2018, 62:272-287.[doi:10.1016/j.asoc.2017.10.035]
    7 武方方. 基于大数据的物流配送中心选址优化研究[硕士学位论文]. 合肥:合肥工业大学, 2015.
    8 Karatas M, Nasuh R, Hakan T. A Comparison of p-median and Maximal Coverage Location Models with Q-coverage Requirement. Procedia Engineering, 2016, 149:169-176.[doi:10.1016/j.proeng.2016.06.652]
    9 王鹏飞. 基于聚类算法的快递服务网点布局研究[硕士学位论文]. 成都:成都理工大学, 2016.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

李捷承,陶耀东,孙咏,高岑.基于BIRCH聚类的物流配送设施选址算法.计算机系统应用,2018,27(9):215-219

Copy
Share
Article Metrics
  • Abstract:1710
  • PDF: 3093
  • HTML: 1516
  • Cited by: 0
History
  • Received:February 12,2018
  • Revised:March 07,2018
  • Online: August 17,2018
Article QR Code
You are the first990809Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063