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Scheduler – A System for Staff Planning

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  • P. Eveborn
  • M. Rönnqvist

Abstract

Scheduling of staff is an important area, both from an academic and industrial point of view. There has been a lot of attention to develop new and efficient methods and models. In this paper, we consider the problem that given a work-force demand, a set of working rules and regulations find schedules for staff members with individual skills and preferences. The planning horizon is typically one week to several months. The problem both constructs tasks and simultaneously allocates them to staff members. The purpose of this paper is not to develop new theoretical results. Instead it deals with novel applications of known approaches to real-world practice. We describe a general scheduling software called SCHEDULER that includes a number of important features. The model is based on a elastic set-partitioning model and as solution method we use a branch-and-price algorithm. As branching strategy we make use of constraint branching and the column generator is a nested constrained shortest path formulation. An important feature is that only legal schedules are generated and used within the model. The system also allows for task changes within shifts, a general description of legal restrictions, preferences and allowable times. The system is in use at a number of companies and we report on the usage at some companies. We also give some numerical results to illustrate the behavior of some important features. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • P. Eveborn & M. Rönnqvist, 2004. "Scheduler – A System for Staff Planning," Annals of Operations Research, Springer, vol. 128(1), pages 21-45, April.
    • Handle: RePEc:spr:annopr:v:128:y:2004:i:1:p:21-45:10.1023/b:anor.0000019097.93634.07
    DOI: 10.1023/B:ANOR.0000019097.93634.07
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    Citations

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    Cited by:

    1. Lusby, Richard Martin & Range, Troels Martin & Larsen, Jesper, 2016. "A Benders decomposition-based matheuristic for the Cardinality Constrained Shift Design Problem," European Journal of Operational Research, Elsevier, vol. 254(2), pages 385-397.
    2. Sanja Petrovic, 2019. "“You have to get wet to learn how to swim” applied to bridging the gap between research into personnel scheduling and its implementation in practice," Annals of Operations Research, Springer, vol. 275(1), pages 161-179, April.
    3. M Lezaun & G Pérez & E Sáinz de la Maza, 2006. "Crew rostering problem in a public transport company," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1173-1179, October.
    4. S. Mirrazavi & Henri Beringer, 2007. "A web-based workforce management system for Sainsburys Supermarkets Ltd," Annals of Operations Research, Springer, vol. 155(1), pages 437-457, November.
    5. Burke, Edmund K. & Curtois, Tim, 2014. "New approaches to nurse rostering benchmark instances," European Journal of Operational Research, Elsevier, vol. 237(1), pages 71-81.
    6. Amir Elalouf, 2014. "Fast approximation algorithms for routing problems with hop-wise constraints," Annals of Operations Research, Springer, vol. 222(1), pages 279-291, November.
    7. Bräysy, Olli & Dullaert, Wout & Nakari, Pentti, 2009. "The potential of optimization in communal routing problems: case studies from Finland," Journal of Transport Geography, Elsevier, vol. 17(6), pages 484-490.
    8. E K Burke & T Curtois & L F van Draat & J-K van Ommeren & G Post, 2011. "Progress control in iterated local search for nurse rostering," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(2), pages 360-367, February.
    9. Escallon-Barrios, Mariana & Noham, Reut & Smilowitz, Karen, 2024. "Dual mode scheduling in volunteer management," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).

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