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Capacity Assessment in Railway Networks

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Handbook of Optimization in the Railway Industry

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 268))

Abstract

Capacity assessment is essential for densely utilized railway networks. To guarantee stable operations, it is necessary to evaluate the capacity occupation and determine possible infrastructure bottlenecks. This requires accurate microscopic models that incorporate detailed infrastructure characteristics, signalling and interlocking logic, train characteristics, and driver behaviour. This chapter presents capacity assessment models based on a novel algebraic approach that builds on accurate running and blocking time computations. The capacity assessment should be undertaken on corridors, station areas, and networks, and as such, support a better understanding of the existing timetable constraints and possible infrastructure investments.

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Author information

Authors and Affiliations

  1. Delft University of Technology, Stevinweg 1, 2628 CN, Delft, The Netherlands

    Nikola Bešinović & Rob M. P. Goverde

Authors
  1. Nikola Bešinović
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  2. Rob M. P. Goverde
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Corresponding author

Correspondence to Nikola Bešinović .

Editor information

Editors and Affiliations

  1. Zuse Institute Berlin & Freie Universität Berlin, Berlin, Germany

    Ralf Borndörfer

  2. Department of Optimization, Zuse Institute Berlin, Berlin, Germany

    Torsten Klug

  3. Optrail, Rome, Italy

    Leonardo Lamorgese

  4. SINTEF DIGITAL & University of Oslo, Oslo, Norway

    Carlo Mannino

  5. LBW Optimization GmbH & Zuse Institute Berlin, Berlin, Germany

    Markus Reuther

  6. LBW Optimization GmbH & Zuse Institute Berlin, Berlin, Germany

    Thomas Schlechte

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Bešinović, N., Goverde, R.M.P. (2018). Capacity Assessment in Railway Networks. In: Borndörfer, R., Klug, T., Lamorgese, L., Mannino, C., Reuther, M., Schlechte, T. (eds) Handbook of Optimization in the Railway Industry. International Series in Operations Research & Management Science, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-319-72153-8_2

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