A decision model for high-speed railway express systems. (March 2023)

• Record Type: Journal Article
• Authors: Zhen, Lu; Gao, Jiajing; Zhang, Nianzu; Li, Haolin; Fan, Tianyi
• Is Part Of: Computers & industrial engineering. Volume 177(2023)
• Publication Date: 2023-03
• Subjects: High-speed railway express -- Intermodal transport -- Uncertain scenarios -- Meta-heuristic; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2023.109087
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: This paper studies network planning and freight allocation problems for high-speed railway express systems. This paper considers the uncertain factors of freight demand and capacity of high-speed trains. A metaheuristic algorithm based on simulated annealing is developed for solving the model. Experiments are conducted to assess the efficiency of the methods. Abstract: With the rapid development of high-speed railway (HSR) networks, HSR express systems are becoming one of the most promising logistics systems. Such systems rely on road transportation to connect customers and railway stations in the HSR networks. HSR express systems also provide four main freight services such as arriving today, arriving the next morning, arriving the next day, arriving the day after tomorrow. This paper investigates a network planning and freight allocation problem for HSR express systems that considers decisions on intermodal station selection, vehicle assignment in road transportation, and freight flow organization. We also take into account factors such as the varying demand for different types of freight services and the uncertain capacity of high-speed trains in various scenarios. A two-stage stochastic programming model is proposed to minimize the total operational cost, which consists of fixed costs and variable costs, in random scenarios. To solve the problem, a metaheuristic algorithm is proposed that is validated by numerical experiments. Some sensitivity analysis on numerical experiments and a case study on the high-speed railway express systems of the China Railway Nanchang Group are conducted, the results of which yield useful managerial insights for practitioners.