Train platforming and rescheduling with flexible interlocking mechanisms: An aggregate approach

Gongyuan Lu, Jia Ning, Xiaobo Liu and Nie, Yu (Marco)

Transportation Research Part E: Logistics and Transportation Review, 2022, vol. 159, issue C

Abstract: This paper proposes a route-based model for the Train Platforming and Rescheduling Problem (TPRP). Built on the concept of Degree of Conflict (DOC), the proposed model can accommodate various interlocking mechanisms with an aggregate railway yard representation. Thanks to the topology of a typical yard, such an aggregate representation promises to reduce the size of the optimization problems concerning yard operations. The TPRP model is formulated as a mixed integer linear program, and solved using both a commercial solver and two heuristic algorithms developed based on the idea of rolling horizon. The proposed model and algorithms are validated using several case studies constructed using data collected at a large high-speed railway station in China. We find the proposed TPRP model can produce, with reasonable computation resources, high quality platform/schedule decisions for real-world applications. In addition, the heuristic algorithms consistently offer high quality approximate solutions at a computational cost considerably lower than what is demanded by a benchmark commercial solver. The results from a simulation model show the differences between various interlocking mechanisms are well captured using a unified aggregate yard representation based on DOC. As expected, more flexible interlocking mechanisms can achieve greater operational efficiency at the expense of looser safety standards.

Keywords: Train platforming and rescheduling; Degree of conflict; Interlocking mechanism; Mixed integer linear program; Rolling horizon (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.tre.2022.102622

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