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Integer programming techniques for the nurse rostering problem

Author

Listed:
  • Haroldo G. Santos

    (Federal University of Ouro Preto)

  • Túlio A. M. Toffolo

    (Federal University of Ouro Preto
    KU Leuven)

  • Rafael A. M. Gomes

    (Federal University of Ouro Preto)

  • Sabir Ribas

    (Federal University of Minas Gerais)

Abstract

This work presents integer programming techniques to tackle the problem of the International Nurse Rostering Competition. Starting from a compact and monolithic formulation in which the current generation of solvers performs poorly, improved cut generation strategies and primal heuristics are proposed and evaluated. A large number of computational experiments with these techniques produced the following results: the optimality of the vast majority of instances was proved, the best known solutions were improved by up to 15 % and strong dual bounds were obtained. In the spirit of reproducible science, all code was implemented using the Computational Infrastructure for Operations Research.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:239:y:2016:i:1:d:10.1007_s10479-014-1594-6
    DOI: 10.1007/s10479-014-1594-6
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    References listed on IDEAS

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    Cited by:

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    2. Florian Mischek & Nysret Musliu, 2019. "Integer programming model extensions for a multi-stage nurse rostering problem," Annals of Operations Research, Springer, vol. 275(1), pages 123-143, April.
    3. Mohammad Reza Hassani & J. Behnamian, 2021. "A scenario-based robust optimization with a pessimistic approach for nurse rostering problem," Journal of Combinatorial Optimization, Springer, vol. 41(1), pages 143-169, January.
    4. 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.
    5. Diego Pecin & Claudio Contardo & Guy Desaulniers & Eduardo Uchoa, 2017. "New Enhancements for the Exact Solution of the Vehicle Routing Problem with Time Windows," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 489-502, August.
    6. Caballini, Claudia & Paolucci, Massimo, 2020. "A rostering approach to minimize health risks for workers: An application to a container terminal in the Italian port of Genoa," Omega, Elsevier, vol. 95(C).
    7. Lai, David S.W. & Leung, Janny M.Y. & Dullaert, Wout & Marques, Inês, 2020. "A graph-based formulation for the shift rostering problem," European Journal of Operational Research, Elsevier, vol. 284(1), pages 285-300.
    8. Sara Ceschia & Nguyen Dang & Patrick Causmaecker & Stefaan Haspeslagh & Andrea Schaerf, 2019. "The Second International Nurse Rostering Competition," Annals of Operations Research, Springer, vol. 274(1), pages 171-186, March.
    9. Toni I. Wickert & Alberto F. Kummer Neto & Márcio M. Boniatti & Luciana S. Buriol, 2021. "An integer programming approach for the physician rostering problem," Annals of Operations Research, Springer, vol. 302(2), pages 363-390, July.
    10. Suk Ho Jin & Ho Yeong Yun & Suk Jae Jeong & Kyung Sup Kim, 2017. "Hybrid and Cooperative Strategies Using Harmony Search and Artificial Immune Systems for Solving the Nurse Rostering Problem," Sustainability, MDPI, vol. 9(7), pages 1-19, June.
    11. George H. G. Fonseca & Túlio A. M. Toffolo, 2022. "A fix-and-optimize heuristic for the ITC2021 sports timetabling problem," Journal of Scheduling, Springer, vol. 25(3), pages 273-286, June.
    12. Sara Ceschia & Rosita Guido & Andrea Schaerf, 2020. "Solving the static INRC-II nurse rostering problem by simulated annealing based on large neighborhoods," Annals of Operations Research, Springer, vol. 288(1), pages 95-113, May.
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    14. Jeffrey H. Kingston, 2021. "Modelling history in nurse rostering," Annals of Operations Research, Springer, vol. 302(2), pages 391-404, July.

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