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Branch-and-price for staff rostering: An efficient implementation using generic programming and nested column generation

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  • Dohn, Anders
  • Mason, Andrew

Abstract

We present a novel generic programming implementation of a column-generation algorithm for the generalized staff rostering problem. The problem is represented as a generalized set partitioning model, which is able to capture commonly occurring problem characteristics given in the literature. Columns of the set partitioning problem are generated dynamically by solving a pricing subproblem, and constraint branching in a branch-and-bound framework is used to enforce integrality. The pricing problem is formulated as a novel three-stage nested shortest path problem with resource constraints that exploits the inherent problem structure. A very efficient implementation of this pricing problem is achieved by using generic programming principles in which careful use of the C++ pre-processor allows the generator to be customized for the target problem at compile-time. As well as decreasing run times, this new approach creates a more flexible modeling framework that is well suited to handling the variety of problems found in staff rostering. Comparison with a more-standard run-time customization approach shows that speedups of around a factor of 20 are achieved using our new approach. The adaption to a new problem is simple and the implementation is automatically adjusted internally according to the new definition. We present results for three practical rostering problems. The approach captures all features of each problem and is able to provide high-quality solutions in less than 15minutes. In two of the three instances, the optimal solution is found within this time frame.

Suggested Citation

  • Dohn, Anders & Mason, Andrew, 2013. "Branch-and-price for staff rostering: An efficient implementation using generic programming and nested column generation," European Journal of Operational Research, Elsevier, vol. 230(1), pages 157-169.
  • Handle: RePEc:eee:ejores:v:230:y:2013:i:1:p:157-169
    DOI: 10.1016/j.ejor.2013.03.018
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    2. Gérard, Matthieu & Clautiaux, François & Sadykov, Ruslan, 2016. "Column generation based approaches for a tour scheduling problem with a multi-skill heterogeneous workforce," European Journal of Operational Research, Elsevier, vol. 252(3), pages 1019-1030.
    3. Elín Björk Böðvarsdóttir & Niels-Christian Fink Bagger & Laura Elise Høffner & Thomas J. R. Stidsen, 2022. "A flexible mixed integer programming-based system for real-world nurse rostering," Journal of Scheduling, Springer, vol. 25(1), pages 59-88, February.
    4. Kjartan Kastet Klyve & Ilankaikone Senthooran & Mark Wallace, 2023. "Nurse rostering with fatigue modelling," Health Care Management Science, Springer, vol. 26(1), pages 21-45, March.
    5. Václavík, Roman & Novák, Antonín & Šůcha, Přemysl & Hanzálek, Zdeněk, 2018. "Accelerating the Branch-and-Price Algorithm Using Machine Learning," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1055-1069.
    6. Christian Tilk & Michael Drexl & Stefan Irnich, 2018. "Nested Branch-and-Price-and-Cut for Vehicle Routing Problems with Multiple Resource Interdependencies," Working Papers 1801, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    7. Tilk, Christian & Drexl, Michael & Irnich, Stefan, 2019. "Nested branch-and-price-and-cut for vehicle routing problems with multiple resource interdependencies," European Journal of Operational Research, Elsevier, vol. 276(2), pages 549-565.
    8. Wang, Wenshu & Xie, Kexin & Guo, Siqi & Li, Weixing & Xiao, Fan & Liang, Zhe, 2023. "A shift-based model to solve the integrated staff rostering and task assignment problem with real-world requirements," European Journal of Operational Research, Elsevier, vol. 310(1), pages 360-378.

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