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Paper FrBT7.2

Qiu, Zhian (Beijing Jiaotong University), Wang, Hongwei (Beijing Jiaotong University), Yang, Xin (Beijing Jiaotong University), Ning, Pengfei (Beijing Jiaotong University), Li, Yang (Beijing Jiaotong University), Wang, Xi (National Engineering Research Center of Rail Transportation Oper)

Optimization of Car Flow Management within the Collection System of Heavy-Haul Railway System

Scheduled for presentation during the Regular Session "Rail Traffic Management II" (FrBT7), Friday, September 27, 2024, 13:50−14:10, Salon 15

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Keywords Rail Traffic Management

Abstract

Heavy-haul railways play a crucial role in transporting large volumes of bulk cargo, particularly coal. The optimization of car flow management within the collection system is pivotal, given that substantial time is spent by both loaded and empty trains in marshaling stations. This optimization can significantly enhance the transport efficiency of heavy-haul railways. In this paper, we propose a mixed-integer linear programming model to minimize the total time spent by loaded trains at marshaling stations and the time taken by empty trains to load and return to the marshaling station. To enhance the model's computational efficiency, we designed two valid inequalities (VI). To evaluate the effectiveness of our proposed model, we construct test cases using real-world data from the Daqin railway and the Hudong marshaling station and various numerical experiments are constructed. The computational analysis reveals that our model can reduce the objective function value by up to 4.7% of X4a2 test case and an average of 2.7% in all test case compared to traditional empirical methods. Furthermore, the VI results in a maximum reduction of 1400 seconds in computation time, showcasing the practical benefits of our approach. These findings highlight the potential of our methodology to significantly reduce the dwell time of heavy-haul trains at collection system, and than improve the operational efficiency of heavy-haul railways.

 

 

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