Research on Logistics Transport Network Optimization of the China-Europe Railway Express

Na Chen and Yani Sun

Chapter 72 in Economic Management and Big Data Application:Proceedings of the 3rd International Conference, 2024, pp 820-831 from World Scientific Publishing Co. Pte. Ltd.

Abstract: We construct a hybrid hub-and-spoke logistics transportation network model that allows for direct transportation. In order to minimize the network running cost, the model is solved by a hybrid two-stage random search and genetic algorithm, and the program is written in Python. After collecting relevant data from CR Express for empirical study, the results showed that the system cost is the best. The five cities of Tianjin, Zhengzhou, Chongqing, Xi’an, and Suzhou were selected as hub nodes. The total cost of the hybrid hub-and-spoke logistics transportation network model with direct access is about 20.19 percent lower than the model without direct access, indicating that establishing direct access in the network can reduce transportation costs and improve logistics efficiency. Finally, we study the factorial experiment of the number p of central hubs and the discount coefficient of trunk transportation α. Results show that when the discount coefficient is low, the total network cost can be reduced by increasing the number of hubs. When the coefficient of scale effect is fixed, with the increase in the number of hubs in the network, the total cost shows a U-shaped trend of decreasing first and then increasing.

Keywords: Big Data; Information Management; Economic; Data Applications; Blockchain; E-commerce (search for similar items in EconPapers)
JEL-codes: C63 C8 O14 (search for similar items in EconPapers)
Date: 2024
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