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国际物流枢纽选址的两阶段方法:以长三角为例

Two-Phase Approach to International Logistics Hub Location: The Case of Yangtze River Delta

IEEE Transactions on Engineering Management · 2024
被引 1
ABS 3

中文导读

提出一个两阶段框架,先用改进的模糊C均值聚类从微观评价中识别候选枢纽,再用自适应重力p-中值模型从宏观规划中确定最优枢纽和货运分配,并以长三角27个城市为例验证,选出上海、苏州、杭州、宁波四个最优枢纽。

Abstract

An international logistics hub (ILH) is an important component of the modern integrated logistics system, and its location selection has always been a hot topic in logistics management. In this article, we aim in developing a two-phase location framework to determine the most preferred ILHs in the logistics network. First, a revised fuzzy C-means clustering algorithm is proposed to identify candidate ILHs from the perspective of microlevel evaluation. The evaluation index system is constructed by the proposed index screening model. Second, an adaptive gravity <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i>-median model is established to determine optimal ILHs and freight flow allocations from a macroplanning perspective. The optimization model takes into account the attractiveness of nodes, the distribution of logistics demand, and the total transportation cost between nodes in the network. Finally, the two-phase approach is applied to the location of ILHs in the Yangtze River Delta (YRD), China. Results show that five alternative locations are identified from 27 cities, and four optimal ILHs (Shanghai, Suzhou, Hangzhou, Ningbo) are determined from five candidate ILHs. The freight flow distribution shows that the share transshipped through them is 33.05%, 26.81%, 22.59%, and 17.55%, respectively. Furthermore, the optimized hub location in the case study is consistent with the practice situation in the YRD. These results illustrate the applicability and feasibility of the proposed two-phase approach for the logistics hub location. We also provide insights for planning logistics hubs and optimizing transportation networks in the YRD from the perspectives of megalopolis and national levels.

物流管理选址决策聚类算法重力p-中值模型长三角