License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.ATMOS.2020.12
URN: urn:nbn:de:0030-drops-131487
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/13148/
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van den Broek, Roel ; Hoogeveen, Han ; van den Akker, Marjan

Personnel Scheduling on Railway Yards

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OASIcs-ATMOS-2020-12.pdf (1 MB)

Abstract

In this paper we consider the integration of the personnel scheduling into planning railway yards. This involves an extension of the Train Unit Shunting Problem, in which a conflict-free schedule of all activities at the yard has to be constructed. As the yards often consist of several kilometers of railway track, the main challenge in finding efficient staff schedules arises from the potentially large walking distances between activities.
We present two efficient heuristics for staff assignment. These methods are integrated into a local search framework to find feasible solutions to the Train Unit Shunting Problem with staff requirements. To the best of our knowledge, this is the first algorithm to solve the complete version of this problem. Additionally, we propose a dynamic programming method to assign staff members as passengers to train movements to reduce their walking time. Furthermore, we describe several ILP-based approaches to find a feasible solution of the staff assignment problem with maximum robustness, which solution we use to evaluate the quality of the solutions produced by the heuristics.
On a set of 300 instances of the train unit shunting problem with staff scheduling on a real-world railway yard, the best-performing heuristic integrated into the local search approach solves 97% of the instances within three minutes on average.

BibTeX - Entry

@InProceedings{vandenbroek_et_al:OASIcs:2020:13148,
  author =	{Roel van den Broek and Han Hoogeveen and Marjan van den Akker},
  title =	{{Personnel Scheduling on Railway Yards}},
  booktitle =	{20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020)},
  pages =	{12:1--12:15},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-170-2},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{85},
  editor =	{Dennis Huisman and Christos D. Zaroliagis},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/13148},
  URN =		{urn:nbn:de:0030-drops-131487},
  doi =		{10.4230/OASIcs.ATMOS.2020.12},
  annote =	{Keywords: Staff Scheduling, Train Shunting, Partial Order Schedule}
}

Keywords: Staff Scheduling, Train Shunting, Partial Order Schedule
Collection: 20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020)
Issue Date: 2020
Date of publication: 10.11.2020

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