Abstract
The propagation of delays between trains has a considerable impact on railway operations. Ideally, planners would like to create timetables that avoid such propagation as much as possible. To improve existing timetables, tools for automatic detection of systematic dependencies of delays among trains would be of great aid. We present efficient algorithms to detect two of the most important types of dependencies, namely dependencies due to resource conflicts and due to maintained connections. We give experimental results on real-world data that demonstrate the practical applicability of our algorithms.
This work was partially supported by the Future and Emerging Technologies Unit of EC (IST priority - 6th FP), under contract no. FP6-021235-2 (project ARRIVAL).
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References
Conte, C.: Identifying Dependencies Among Delays. PhD thesis, Georg-August-Universität zu Göttingen (2007), http://webdoc.sub.gwdg.de/diss/2008/conte/
Conte, C., Schöbel, A.: Identifying dependencies among delays. In: Proceedings of IAROR 2007 (2007)
Daamen, W., Goverde, R.M.P., Hansen, I.A.: Non-discriminatory automatic registration of knock-on train delays. Networks and Spatial Economics 9(1), 47–69 (2009)
D’Ariano, A.: Improving Real-Time Train Dispatching: Models, Algorithms and Applications. PhD thesis, TU Delft (2008), http://repository.tudelft.nl/
Gatto, M.: On the Impact of Uncertainty on some Optimization Problems: Combinatorial Aspects of Delay Management and Robust Online Scheduling. PhD thesis, ETH Zürich, No. 17452 (2007)
Goverde, R.M.P.: Optimal scheduling of connections in railway systems. Technical report, TRAIL, Delft, The Netherlands (1998)
Hubert, M., Rousseeuw, P.J., Aelst, S.V.: High-breakdown robust multivariate methods. Statistical Science 23(1), 92–119 (2008)
R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2008), http://www.R-project.org
Schöbel, A.: Optimization in Public Transportation. Optimization and Its Applications, vol. 3. Springer, Heidelberg (2006)
Wille, A., Bühlmann, P.: Tri-graph: a novel graphical model with application to genetic regulatory networks. Technical report, ETH Zürich (2004), ftp://ftp.stat.math.ethz.ch/Research-Reports/Other-Manuscripts/buhlmann/trigraph.pdf
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Flier, H., Gelashvili, R., Graffagnino, T., Nunkesser, M. (2009). Mining Railway Delay Dependencies in Large-Scale Real-World Delay Data. In: Ahuja, R.K., Möhring, R.H., Zaroliagis, C.D. (eds) Robust and Online Large-Scale Optimization. Lecture Notes in Computer Science, vol 5868. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05465-5_15
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DOI: https://doi.org/10.1007/978-3-642-05465-5_15
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