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Article

Investigation of Railway Network Capacity by Means of Dynamic Flows

Institute of Transport Science, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52074 Aachen, Germany
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Appl. Sci. 2024, 14(18), 8233; https://doi.org/10.3390/app14188233
Submission received: 30 July 2024 / Revised: 5 September 2024 / Accepted: 9 September 2024 / Published: 12 September 2024

Abstract

Capacity calculations are essential for the long-term planning of railway infrastructure. Many of the methods currently used in practice calculate characteristic capacity values separately for the single elements (mainly lines and nodes) of a railway network. Approaches that consider the entire network to account for interactions between the elements often rely on many assumptions, which renders a direct practical application difficult. This paper therefore introduces a linear optimization model that comprises railway-specific constraints such as minimum headway times, line capacities, and route conflicts. Under the consideration of these constraints, the developed model permits the calculation of a network-wide capacity. The model is validated on a sample network that is based on a real network of the German railway infrastructure.
Keywords: capacity; railway networks; network effects; optimization; dynamic multicommodity flows; long-term planning capacity; railway networks; network effects; optimization; dynamic multicommodity flows; long-term planning

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MDPI and ACS Style

Nikolayzik, D.; Maus, M.; Nießen, N. Investigation of Railway Network Capacity by Means of Dynamic Flows. Appl. Sci. 2024, 14, 8233. https://doi.org/10.3390/app14188233

AMA Style

Nikolayzik D, Maus M, Nießen N. Investigation of Railway Network Capacity by Means of Dynamic Flows. Applied Sciences. 2024; 14(18):8233. https://doi.org/10.3390/app14188233

Chicago/Turabian Style

Nikolayzik, Dominik, Maren Maus, and Nils Nießen. 2024. "Investigation of Railway Network Capacity by Means of Dynamic Flows" Applied Sciences 14, no. 18: 8233. https://doi.org/10.3390/app14188233

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