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Structure-Based Decomposition for Pattern-Detection for Railway Timetables

In: Operations Research Proceedings 2017

Author

Listed:
  • Stanley Schade

    (Zuse Institute Berlin, Mathematics of Transportation and Logistics)

  • Thomas Schlechte

    (LBW Optimization GmbH)

  • Jakob Witzig

    (Zuse Institute Berlin, Mathematical Optimization Methods)

Abstract

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.

Suggested Citation

  • Stanley Schade & Thomas Schlechte & Jakob Witzig, 2018. "Structure-Based Decomposition for Pattern-Detection for Railway Timetables," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 715-721, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-89920-6_95
    DOI: 10.1007/978-3-319-89920-6_95
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