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Rescheduling models for railway traffic management in large-scale networks

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Abstract

In the last decades of railway operations research, microscopic models have been intensively studied to support traffic operators in managing their dispatching areas. However, those models result in long computation times for large and highly utilized networks. The problem of controlling country-wide traffic is still open since the coordination of local areas is hard to tackle in short time and there are multiple interdependencies between trains across the whole network. This work is dedicated to the development of new macroscopic models that are able to incorporate traffic management decisions. Objective of this paper is to investigate how different levels of detail and number of operational constraints may affect the applicability of models for network-wide rescheduling in terms of quality of solutions and computation time. We present four different macroscopic models and test them on the Dutch national timetable. The macroscopic models are compared with a state-of-the-art microscopic model. Trade-off between computation time and solution quality is discussed on various disturbed traffic conditions.

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Acknowledgements

This work is partially funded by the Dutch Technology Foundation STW, research project: Model-Predictive Railway Traffic Management (project no. 11025).

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Correspondence to Pavle Kecman.

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Kecman, P., Corman, F., D’Ariano, A. et al. Rescheduling models for railway traffic management in large-scale networks. Public Transp 5, 95–123 (2013). https://doi.org/10.1007/s12469-013-0063-y

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