Research on the Location-Routing Optimization of International Freight Trains Considering the Implementation of Blockchain

Zhichao Hong, Hao Shen, Wenjie Sun, Jin Zhang (), Hongbin Liang and Gang Zhao
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Zhichao Hong: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Hao Shen: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Wenjie Sun: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Jin Zhang: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Hongbin Liang: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Gang Zhao: China Railway Union International Container Smart Logistics Chengdu Co., Ltd., Chengdu 610084, China

Mathematics, 2024, vol. 12, issue 23, 1-23

Abstract: The purpose of this study is to solve the problem of low load factor and profit margin in the point-to-point transportation of international freight trains through the assembly transportation organization mode. A bi-objective location-routing optimization model is constructed to optimize problems, such as the location of the assembly center, route of freight assembly, frequency of international freight trains, and number of formations. The objectives are to minimize the total comprehensive cost and maximize the average satisfaction of the shippers. Considering the impact of blockchain technology, the proportion of customs clearance time reduction after blockchain implementation, the proportion of customs clearance fee reduction after blockchain implementation, and the cost of blockchain technology are introduced into the model. The case study is based on railroad transportation data for 2022. In this case, 43 stations in the Indo-China Peninsula are selected as origin stations, and two Chinese stations are designated terminal stations. An improved NSGA-II algorithm (ANSGAII-OD) is proposed to resolve the location-routing optimization model. This algorithm is based on opposition-based learning and its dominant strength. The case study indicates that assembly transportation is advantageous compared with direct transportation. Moreover, the comprehensive cost is reduced by 19.77%. Furthermore, blockchain technology can effectively reduce costs and improve transportation efficiency. After the implementation of blockchain technology, the comprehensive cost is reduced by 8.10%, whereas the average satisfaction of shippers is increased by 10.35%.

Keywords: international freight trains; assembly center; location-routing optimization model; blockchain technology; ANSGAII-OD (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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