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Civil-Comp Conferences
ISSN 2753-3239 CCC: 1
PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo
Paper 23.8
Efficient timetable stability analysis using a graph contraction procedure S. Butikofer, D. Fontana, A. Steiner and R. Wust
Zurich University of Applied Sciences, School of Engineering, Institute of Data Analysis and Process Design, Winterthur, Switzerland S. Butikofer, D. Fontana, A. Steiner, R. Wust, "Efficient timetable stability analysis using a graph
contraction procedure", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance",
Civil-Comp Press, Edinburgh, UK,
Online volume: CCC 1, Paper 23.8, 2022, doi:10.4203/ccc.1.23.8
Keywords: timetable stability, max-plus algebra, event activity network, graph
contraction.
Abstract
Train density on the Swiss rail network has increased significantly in recent years.
This demands much more from the stability of the system, especially in combination
with single-track corridors. For railroad companies, it is therefore becoming
increasingly important to optimize the transport network for stability in order to be
able to offer the demanded service as reliably as possible on the existing infrastructure.
An approach to numerical stability evaluation of timed discrete event systems has
been developed to support planners in testing the timetable for operational stability.
In this approach, the traffic system under consideration is modeled as a network with
all relevant timetable events and links. The system modelled in this way can be
examined for its behavior in the event of a possible disruption using methods from
max-plus algebra. The typical computation time of an evaluation procedure takes
more than 65 minutes for a signifcant partition of the line network. This is far too high
for integration into a practical optimization procedure.
In this paper we present a contraction procedure added to the existing evaluation
framework, and thus reduce the computation time by more than 90% without
compromising the result quality.
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