A Scheduling Approach for the Combination Scheme and Train Timetable of a Heavy-Haul Railway

Hanxiao Zhou, Leishan Zhou, Bin Guo, Zixi Bai, Zeyu Wang and Lu Yang
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Hanxiao Zhou: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Leishan Zhou: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Bin Guo: State Research Center of Rail Transit Technology Education and Service, Beijing Jiaotong University, Beijing 100044, China
Zixi Bai: Beijing Key Laboratory of Traffic Engineering, Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Zeyu Wang: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Lu Yang: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

Mathematics, 2021, vol. 9, issue 23, 1-29

Abstract: Heavy-haul railway transport is a critical mode of regional bulk cargo transport. It dramatically improves the freight transport capacity of railway lines by combining several unit trains into one combined train. In order to improve the efficiency of the heavy-haul transport system and reduce the transportation cost, a critical problem involves arranging the combination scheme in the combination station (CBS) and scheduling the train timetable along the trains’ journey. With this consideration, this paper establishes two integer programming models in stages involving the train service plan problem (TSPP) model and train timetabling problem (TTP) model. The TSPP model aims to obtain a train service plan according to the freight demands by minimizing the operation cost. Based on the train service plan, the TTP model is to simultaneously schedule the combination scheme and train timetable, considering the utilization optimal for the CBS. Then, an effective hybrid genetic algorithm (HGA) is designed to solve the model and obtain the combination scheme and train timetable. Finally, some experiments are implemented to illustrate the feasibility of the proposed approaches and demonstrate the effectiveness of the HGA.

Keywords: freight transportation; heavy-haul railway; combination scheme; train timetable; genetic algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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