IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v41y2021i1d10.1007_s10878-020-00667-0.html
   My bibliography  Save this article

A scenario-based robust optimization with a pessimistic approach for nurse rostering problem

Author

Listed:
  • Mohammad Reza Hassani

    (Bu-Ali Sina University)

  • J. Behnamian

    (Bu-Ali Sina University)

Abstract

Nurse rostering problem (NRP) or nurse scheduling problem is a combinatorial optimization problem that involves the assignment of shifts to nurses while managing coverage constraints, expertise categories, labor legislation, contractual agreements, personal preferences, etc. The focus on this problem serves to improve service quality, nurse health and their satisfaction, and reduction of hospital costs. The existence of uncertainties and inaccurate estimates of the workload leads to a non-optimal or an infeasible solution. In this study, due to the importance of human resource management and crisis management in the health care system, a sustainable approach was developed with a robust scenario-based optimization method. Since NRP is a NP-hard problem, it is impossible to solve it in medium and large sizes in reasonable time. In this paper, a well-known metaheuristic algorithm, namely the differential evolution (DE) algorithm was proposed due to its sound structural features for searching in binary space. Then its performance was compared against the genetic algorithm. The results show that the DE algorithm has good performance.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jcomop:v:41:y:2021:i:1:d:10.1007_s10878-020-00667-0
    DOI: 10.1007/s10878-020-00667-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-020-00667-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10878-020-00667-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Brucker, Peter & Qu, Rong & Burke, Edmund, 2011. "Personnel scheduling: Models and complexity," European Journal of Operational Research, Elsevier, vol. 210(3), pages 467-473, May.
    2. Xidonas, Panos & Mavrotas, George & Hassapis, Christis & Zopounidis, Constantin, 2017. "Robust multiobjective portfolio optimization: A minimax regret approach," European Journal of Operational Research, Elsevier, vol. 262(1), pages 299-305.
    3. Tanzi,Vito & Schuknecht,Ludger, 2000. "Public Spending in the 20th Century," Cambridge Books, Cambridge University Press, number 9780521662918, January.
    4. Deborah L. Kellogg & Steven Walczak, 2007. "Nurse Scheduling: From Academia to Implementation or Not?," Interfaces, INFORMS, vol. 37(4), pages 355-369, August.
    5. Kayse Lee Maass & Boying Liu & Mark S. Daskin & Mary Duck & Zhehui Wang & Rama Mwenesi & Hannah Schapiro, 2017. "Incorporating nurse absenteeism into staffing with demand uncertainty," Health Care Management Science, Springer, vol. 20(1), pages 141-155, March.
    6. 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.
    7. D. Parr & J. Thompson, 2007. "Solving the multi-objective nurse scheduling problem with a weighted cost function," Annals of Operations Research, Springer, vol. 155(1), pages 279-288, November.
    8. Glass, Celia A. & Knight, Roger A., 2010. "The nurse rostering problem: A critical appraisal of the problem structure," European Journal of Operational Research, Elsevier, vol. 202(2), pages 379-389, April.
    9. Onwubolu, Godfrey & Davendra, Donald, 2006. "Scheduling flow shops using differential evolution algorithm," European Journal of Operational Research, Elsevier, vol. 171(2), pages 674-692, June.
    10. 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.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jalel Euchi & Malek Masmoudi & Patrick Siarry, 2022. "Home health care routing and scheduling problems: a literature review," 4OR, Springer, vol. 20(3), pages 351-389, September.
    2. Tan Yu & Yongpei Guan & Xiang Zhong, 2024. "Visiting nurses assignment and routing for decentralized telehealth service networks," Annals of Operations Research, Springer, vol. 341(2), pages 1191-1221, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    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. 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.
    4. 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.
    5. 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).
    6. Young-Chae Hong & Amy Cohn & Stephen Gorga & Edmond O’Brien & William Pozehl & Jennifer Zank, 2019. "Using Optimization Techniques and Multidisciplinary Collaboration to Solve a Challenging Real-World Residency Scheduling Problem," Interfaces, INFORMS, vol. 49(3), pages 201-212, May.
    7. 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.
    8. Smirnov, Dmitry & Huchzermeier, Arnd, 2020. "Analytics for labor planning in systems with load-dependent service times," European Journal of Operational Research, Elsevier, vol. 287(2), pages 668-681.
    9. 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.
    10. Zhang, Zizhen & Qin, Hu & Wang, Kai & He, Huang & Liu, Tian, 2017. "Manpower allocation and vehicle routing problem in non-emergency ambulance transfer service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 45-59.
    11. Tristan Becker & Pia Mareike Steenweg & Brigitte Werners, 2019. "Cyclic shift scheduling with on-call duties for emergency medical services," Health Care Management Science, Springer, vol. 22(4), pages 676-690, December.
    12. Tristan Becker, 2020. "A decomposition heuristic for rotational workforce scheduling," Journal of Scheduling, Springer, vol. 23(5), pages 539-554, October.
    13. 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.
    14. 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.
    15. Fang, Kan & Wang, Shijin & Pinedo, Michael L. & Chen, Lin & Chu, Feng, 2021. "A combinatorial Benders decomposition algorithm for parallel machine scheduling with working-time restrictions," European Journal of Operational Research, Elsevier, vol. 291(1), pages 128-146.
    16. Volland, Jonas & Fügener, Andreas & Brunner, Jens O., 2017. "A column generation approach for the integrated shift and task scheduling problem of logistics assistants in hospitals," European Journal of Operational Research, Elsevier, vol. 260(1), pages 316-334.
    17. Emir Hüseyin Özder & Evrencan Özcan & Tamer Eren, 2019. "Staff Task-Based Shift Scheduling Solution with an ANP and Goal Programming Method in a Natural Gas Combined Cycle Power Plant," Mathematics, MDPI, vol. 7(2), pages 1-26, February.
    18. Lü, Zhipeng & Hao, Jin-Kao, 2012. "Adaptive neighborhood search for nurse rostering," European Journal of Operational Research, Elsevier, vol. 218(3), pages 865-876.
    19. Hans Corsten & Ferdinand Becker & Hagen Salewski, 2020. "Integrating truck and workforce scheduling in a cross-dock: analysis of different workforce coordination policies," Journal of Business Economics, Springer, vol. 90(2), pages 207-237, March.
    20. Andrew Lim & Zhenzhen Zhang & Hu Qin, 2017. "Pickup and Delivery Service with Manpower Planning in Hong Kong Public Hospitals," Transportation Science, INFORMS, vol. 51(2), pages 688-705, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcomop:v:41:y:2021:i:1:d:10.1007_s10878-020-00667-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.