Optimal Rescheduling in Classification Yards with Train Processing Alternatives

Henning Preis (), Daniel Haalboom and Nikola Bešinović
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Henning Preis: Chair of Railway Operations, “Friedrich List” Faculty of Transport and Traffic Sciences, Technische Universität Dresden
Daniel Haalboom: Chair of Railway Operations, “Friedrich List” Faculty of Transport and Traffic Sciences, Technische Universität Dresden
Nikola Bešinović: Chair of Railway Operations, “Friedrich List” Faculty of Transport and Traffic Sciences, Technische Universität Dresden

Chapter Chapter 65 in Operations Research Proceedings 2023, 2025, pp 511-518 from Springer

Abstract: Abstract Classification yards are important nodes in railroad networks, especially in the single wagonload transport system. The yard operations are complex due to a high number of involved resources and restrictive dependencies. Inbound train delays can cause railcar transitions to occur later than originally envisaged. Decisions on job sequencing and resource allocation have a major impact on reactionary outbound delays and thus on the quality of service in the network. Due to permanent updates of arrival times and resource availabilities, a constant rescheduling of operations is necessary. In some cases, it is useful to deviate from the standard treatment by replacing certain processes, parallelize activities or assigning additional personnel to reduce resulting delays of outbound trains. The paper addresses these options and their integration into a comprehensive scheduling approach. Therefore, a mixed integer program (MIP) considering train processing alternatives is presented together. It includes all necessary types of resources, i.e. personnel and locomotives together with their interdependencies and time constraints. The objective function minimizes the overall outbound delay. Afterwards, some practical scenarios adapted from the classification yard in Munich operated by DB Cargo AG are calculated with CPLEX. The results of the optimization approach are presented and evaluated regarding to the effects of the alternative train treatments. Finally, conclusions are derived for operating the model in real-time-environments of classification yards.

Keywords: Rail freight transportation; Resource scheduling; Optimization (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-58405-3_65

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