Personnel Scheduling on Railway Yards

Authors Roel van den Broek, Han Hoogeveen, Marjan van den Akker

Thumbnail PDF


  • Filesize: 1.37 MB
  • 15 pages

Document Identifiers

Author Details

Roel van den Broek
  • Department of Computer Science, Utrecht University, The Netherlands
Han Hoogeveen
  • Department of Computer Science, Utrecht University, The Netherlands
Marjan van den Akker
  • Department of Computer Science, Utrecht University, The Netherlands

Cite AsGet BibTex

Roel van den Broek, Han Hoogeveen, and Marjan van den Akker. Personnel Scheduling on Railway Yards. In 20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020). Open Access Series in Informatics (OASIcs), Volume 85, pp. 12:1-12:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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.

Subject Classification

ACM Subject Classification
  • Applied computing → Transportation
  • Computing methodologies → Planning for deterministic actions
  • Staff Scheduling
  • Train Shunting
  • Partial Order Schedule


  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    PDF Downloads


  1. J Arturo Castillo-Salazar, Dario Landa-Silva, and Rong Qu. Workforce scheduling and routing problems: literature survey and computational study. Annals of Operations Research, 239(1):39-67, 2016. Google Scholar
  2. Richard Freling, Dennis Huisman, and Albert PM Wagelmans. Models and algorithms for integration of vehicle and crew scheduling. Journal of Scheduling, 6(1):63-85, 2003. Google Scholar
  3. Richard Freling, Ramon M Lentink, Leo G Kroon, and Dennis Huisman. Shunting of passenger train units in a railway station. Transportation Science, 39(2):261-272, 2005. Google Scholar
  4. Attila A Kovacs, Sophie N Parragh, Karl F Doerner, and Richard F Hartl. Adaptive large neighborhood search for service technician routing and scheduling problems. Journal of scheduling, 15(5):579-600, 2012. Google Scholar
  5. Leo G Kroon, Ramon M Lentink, and Alexander Schrijver. Shunting of passenger train units: an integrated approach. Transportation Science, 42(4):436-449, 2008. Google Scholar
  6. Ramon M Lentink, Pieter-Jan Fioole, Leo G Kroon, and Cor Van’t Woudt. Applying operations research techniques to planning of train shunting. Planning in Intelligent Systems: Aspects, Motivations, and Methods, pages 415-436, 2006. Google Scholar
  7. Jorne Van den Bergh, Jeroen Beliën, Philippe De Bruecker, Erik Demeulemeester, and Liesje De Boeck. Personnel scheduling: A literature review. European journal of operational research, 226(3):367-385, 2013. Google Scholar
  8. Roel van den Broek, Han Hoogeveen, Marjan van den Akker, and Bob Huisman. Train shunting and service scheduling: an integrated local search approach. Master’s thesis, Utrecht University, 2016. URL:
  9. Roel van den Broek, Han Hoogeveen, Marjan van den Akker, and Bob Huisman. A local search algorithm for train unit shunting with service scheduling. Transportation Science, 2020. Manuscript submitted for publication. Google Scholar