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Gewählte Publikation:

Wang, JX; Zhao, YN; Gronalt, M; Lin, BL; Wu, JP.
(2022): Synchronized Optimization for Service Scheduling, Train Parking and Routing at High-Speed Rail Maintenance Depot
IEEE T INTELL TRANSP. 2022; 23(5): 4525-4540. FullText FullText_BOKU

To meet the operational requirements and to ensure safe operations, train units of a passenger railway operator require inspection and/or cleaning at the maintenance depots after running a specified mileage or time period. Accordingly, these inspection and cleaning activities are called depot services. In this paper, we propose an integer linear programming (ILP) model for the integrated optimization problem of depot service scheduling, train parking, and train routing. Both short trains (8 marshaling) and long trains (16 marshaling) are considered in the ILP model which is a combinational optimization problem in the dead-end tracks scenario. Moreover, a real-world case study of the Shanghai South Depot, China is carried out to further examine the effectiveness and efficiency of the proposed methodology. Computational results indicate that our method is able to generate optimized shunting plans for the linearized INLP within reasonable solution time for real-life applications, outperforming the manual method in terms of the solution quality and the computation speed.
Autor*innen der BOKU Wien:
Gronalt Manfred
BOKU Gendermonitor:

Find related publications in this database (Keywords)
Computational modeling
Rail transportation
Maintenance engineering
Maintenance depot
train shunting
service scheduling
integer linear programming

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