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Local search neighbourhoods for dealing with a novel nurse rostering model

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  • Burak Bilgin
  • Patrick Causmaecker
  • Benoît Rossie
  • Greet Vanden Berghe

Abstract

A novel nurse rostering model is developed to represent real world problem instances more accurately. The proposed model is generic in the sense that it allows modelling of essentially different problem instances. Novel local search neighbourhoods are implemented to take advantage of the problem properties represented by the model. These neighbourhoods are used in a variable neighbourhood search and in an adaptive large neighbourhood search algorithm. The performance of the solution method is evaluated empirically on real world data. The proposed model is open to further extensions for covering personnel planning problems in different sectors and countries. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:194:y:2012:i:1:p:33-57:10.1007/s10479-010-0804-0
    DOI: 10.1007/s10479-010-0804-0
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    References listed on IDEAS

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    Cited by:

    1. Komarudin & Tim De Feyter & Marie-Anne Guerry & Greet Vanden Berghe, 2020. "The extended roster quality staffing problem: addressing roster quality variation within a staffing planning period," Journal of Scheduling, Springer, vol. 23(2), pages 253-264, April.
    2. 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.
    3. Turhan, Aykut Melih & Bilgen, Bilge, 2022. "A mat-heuristic based solution approach for an extended nurse rostering problem with skills and units," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    4. Akoluk, Damla & Karsu, Özlem, 2022. "Ensuring multidimensional equality in public service," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    5. Tim De Feyter & Marie-Anne Guerry & Komarudin, 2017. "Optimizing cost-effectiveness in a stochastic Markov manpower planning system under control by recruitment," Annals of Operations Research, Springer, vol. 253(1), pages 117-131, June.
    6. 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.
    7. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    8. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.
    9. Komarudin, & Guerry, Marie-Anne & De Feyter, Tim & Vanden Berghe, Greet, 2013. "The roster quality staffing problem – A methodology for improving the roster quality by modifying the personnel structure," European Journal of Operational Research, Elsevier, vol. 230(3), pages 551-562.
    10. Lena Hörsting & Catherine Cleophas, 2023. "Integrating Micro-Depot Freight Transport in Existing Public Transport Services," SN Operations Research Forum, Springer, vol. 4(3), pages 1-35, September.
    11. Chiaramonte Michael & Cochran Jeffery & Caswell David, 2015. "Nurse preference rostering using agents and iterated local search," Annals of Operations Research, Springer, vol. 226(1), pages 443-461, March.
    12. Xiang Li & Haoyue Fan & Jiaming Liu & Qifeng Xun, 2022. "Staff scheduling in blood collection problems," Annals of Operations Research, Springer, vol. 316(1), pages 365-400, September.

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