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Simulated annealing approach to nurse rostering benchmark and real-world instances

Author

Listed:
  • Frederik Knust

    (Connext Communication GmbH)

  • Lin Xie

    (Leuphana University of Lüneburg)

Abstract

The nurse rostering problem, which addresses the task of assigning a given set of activities to nurses without violating any complex rules, has been studied extensively in the last 40 years. However, in a lot of hospitals the schedules are still created manually, as most of the research has not produced methods and software suitable for a practical application. This paper introduces a novel, flexible problem model, which can be categorized as ASBN|RVNTO|PLG. Two solution methods are implemented, including a MIP model to compute good bounds for the test instances and a heuristic method using the simulated annealing algorithm for practical use. Both methods are tested on the available benchmark instances and on the real-world data. The mathematical model and solution methods are integrated into a state-of-the-art duty rostering software, which is primarily used in Germany and Austria.

Suggested Citation

  • Frederik Knust & Lin Xie, 2019. "Simulated annealing approach to nurse rostering benchmark and real-world instances," Annals of Operations Research, Springer, vol. 272(1), pages 187-216, January.
    • Handle: RePEc:spr:annopr:v:272:y:2019:i:1:d:10.1007_s10479-017-2546-8
    DOI: 10.1007/s10479-017-2546-8
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    References listed on IDEAS

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    1. 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.
    2. Cheang, B. & Li, H. & Lim, A. & Rodrigues, B., 2003. "Nurse rostering problems--a bibliographic survey," European Journal of Operational Research, Elsevier, vol. 151(3), pages 447-460, December.
    3. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    4. Dowsland, Kathryn A., 1998. "Nurse scheduling with tabu search and strategic oscillation," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 393-407, April.
    5. Burke, Edmund K. & Li, Jingpeng & Qu, Rong, 2010. "A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems," European Journal of Operational Research, Elsevier, vol. 203(2), pages 484-493, June.
    6. Haroldo G. Santos & Túlio A. M. Toffolo & Rafael A. M. Gomes & Sabir Ribas, 2016. "Integer programming techniques for the nurse rostering problem," Annals of Operations Research, Springer, vol. 239(1), pages 225-251, April.
    7. Paola Cappanera & Giorgio Gallo, 2004. "A Multicommodity Flow Approach to the Crew Rostering Problem," Operations Research, INFORMS, vol. 52(4), pages 583-596, August.
    8. Deborah L. Kellogg & Steven Walczak, 2007. "Nurse Scheduling: From Academia to Implementation or Not?," Interfaces, INFORMS, vol. 37(4), pages 355-369, August.
    9. B. Maenhout & M. Vanhoucke, 2008. "Branching Strategies in a Branch-and-Price Approach for a Multiple Objective Nurse Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 08/495, Ghent University, Faculty of Economics and Business Administration.
    10. Burke, Edmund K. & Curtois, Timothy & Post, Gerhard & Qu, Rong & Veltman, Bart, 2008. "A hybrid heuristic ordering and variable neighbourhood search for the nurse rostering problem," European Journal of Operational Research, Elsevier, vol. 188(2), pages 330-341, July.
    11. Edmund K. Burke & Timothy Curtois & Rong Qu & Greet Vanden Berghe, 2013. "A Time Predefined Variable Depth Search for Nurse Rostering," INFORMS Journal on Computing, INFORMS, vol. 25(3), pages 411-419, August.
    12. Valouxis, Christos & Gogos, Christos & Goulas, George & Alefragis, Panayiotis & Housos, Efthymios, 2012. "A systematic two phase approach for the nurse rostering problem," European Journal of Operational Research, Elsevier, vol. 219(2), pages 425-433.
    13. Lü, Zhipeng & Hao, Jin-Kao, 2012. "Adaptive neighborhood search for nurse rostering," European Journal of Operational Research, Elsevier, vol. 218(3), pages 865-876.
    14. Burak Bilgin & Patrick Causmaecker & Benoît Rossie & Greet Vanden Berghe, 2012. "Local search neighbourhoods for dealing with a novel nurse rostering model," Annals of Operations Research, Springer, vol. 194(1), pages 33-57, April.
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    Cited by:

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    2. Safae Er-Rbib & Guy Desaulniers & Issmail Elhallaoui & Patrick Munroe, 2021. "Preference-based and cyclic bus driver rostering problem with fixed days off," Public Transport, Springer, vol. 13(2), pages 251-286, June.
    3. 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.

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