Research on Location Selection of Distribution Center in New Urban Area of Jiuzhou Tong Based on Hierarchical Analysis Method
- DOI
- 10.2991/978-94-6463-570-6_78How to use a DOI?
- Keywords
- distribution center; site selection; hierarchical analysis
- Abstract
With the rapid development of the logistics industry, the site selection of distribution centers is increasingly highlighting its importance. The purpose of this paper is to study the site selection problem of the distribution center in the new urban area of Jiuzhou Tong using the hierarchical analysis method (AHP). By constructing a site selection evaluation model, combined with field research and data analysis, the key factors affecting site selection are identified, and the optimal site selection scheme is given. The results of the study show that the AHP-based site selection method can effectively improve the scientificity and rationality of site selection, and provides strong support for the planning and development of the distribution center in the new urban area of Jiuzhou Tong.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiaobing Shao AU - Shengyuan Wang PY - 2024 DA - 2024/11/22 TI - Research on Location Selection of Distribution Center in New Urban Area of Jiuzhou Tong Based on Hierarchical Analysis Method BT - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024) PB - Atlantis Press SP - 788 EP - 794 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-570-6_78 DO - 10.2991/978-94-6463-570-6_78 ID - Shao2024 ER -