Structure-based Decomposition for Pattern-Detection for Railway Timetables

Please always quote using this URN: urn:nbn:de:0297-zib-64525
  • 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 Witzig
Document Type:ZIB-Report
Date of first Publication:2017/07/14
Series (Serial Number):ZIB-Report (17-40)
ISSN:1438-0064

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