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Structure-based Decomposition for Pattern-Detection for Railway Timetables

  • We consider the problem of pattern detection in large scale railway timetables. This problem arises in rolling stock optimization planning in order to identify invariant sections of the timetable for which a cyclic rotation plan is adequate. We propose a dual reduction technique which leads to an decomposition and enumeration method. Computational results for real world instances demonstrate that the method is able to produce optimal solutions as fast as standard MIP solvers.

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Metadaten
Author:Stanley Schade, Thomas Schlechte, Jakob WitzigORCiD
Document Type:In Proceedings
Parent Title (English):Operations Research Proceedings 2017
First Page:715
Last Page:721
Publisher:Springer International Publishing
Year of first publication:2018
Preprint:urn:nbn:de:0297-zib-64525
DOI:https://doi.org/10.1007/978-3-319-89920-6_95
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