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A column generation approach for solving the patient admission scheduling problem

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  • Range, Troels Martin
  • Lusby, Richard Martin
  • Larsen, Jesper

Abstract

This paper addresses the Patient Admission Scheduling (PAS) problem. The PAS problem entails assigning elective patients to beds, while satisfying a number of hard constraints and as many soft constraints as is possible, and arises at all planning levels for hospital management. There exist a few, different variants of this problem. In this paper we consider one such variant and propose an optimization-based heuristic building on branch-and-bound, column generation, and dynamic constraint aggregation to solve it. We achieve tighter lower bounds than previously reported in the literature and, in addition, we are able to produce new best known solutions for five out of twelve instances from a publicly available repository.

Suggested Citation

  • Range, Troels Martin & Lusby, Richard Martin & Larsen, Jesper, 2014. "A column generation approach for solving the patient admission scheduling problem," European Journal of Operational Research, Elsevier, vol. 235(1), pages 252-264.
    • Handle: RePEc:eee:ejores:v:235:y:2014:i:1:p:252-264
    DOI: 10.1016/j.ejor.2013.10.050
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    1. Issmail Elhallaoui & Abdelmoutalib Metrane & Guy Desaulniers & François Soumis, 2011. "An Improved Primal Simplex Algorithm for Degenerate Linear Programs," INFORMS Journal on Computing, INFORMS, vol. 23(4), pages 569-577, November.
    2. R Lusby & A Dohn & T M Range & J Larsen, 2012. "A column generation-based heuristic for rostering with work patterns," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(2), pages 261-277, February.
    3. Kusters, Rob J. & Groot, Petra M. A., 1996. "Modelling resource availability in general hospitals design and implementation of a decision support model," European Journal of Operational Research, Elsevier, vol. 88(3), pages 428-445, February.
    4. Francesca Guerriero & Rosita Guido, 2011. "Operational research in the management of the operating theatre: a survey," Health Care Management Science, Springer, vol. 14(1), pages 89-114, March.
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    Cited by:

    1. Bouarab, Hocine & El Hallaoui, Issmail & Metrane, Abdelmoutalib & Soumis, François, 2017. "Dynamic constraint and variable aggregation in column generation," European Journal of Operational Research, Elsevier, vol. 262(3), pages 835-850.
    2. Range, Troels Martin & Kozlowski, Dawid & Petersen, Niels Chr., 2016. "Dynamic job assignment: A column generation approach with an application to surgery allocation," Discussion Papers on Economics 4/2016, University of Southern Denmark, Department of Economics.
    3. Lusby, Richard Martin & Schwierz, Martin & Range, Troels Martin & Larsen, Jesper, 2016. "An Adaptive Large Neighbourhood Search Procedure Applied to the Dynamic Patient Admission Scheduling Problem," Discussion Papers on Economics 1/2016, University of Southern Denmark, Department of Economics.
    4. Kaining Shao & Wenjuan Fan & Zishu Yang & Shanlin Yang & Panos M. Pardalos, 2022. "A column generation approach for patient scheduling with setup time and deteriorating treatment duration," Operational Research, Springer, vol. 22(3), pages 2555-2586, July.
    5. Chengliang Wang & Feifei Yang & Quan-Lin Li, 2023. "Optimal Decision of Dynamic Bed Allocation and Patient Admission with Buffer Wards during an Epidemic," Mathematics, MDPI, vol. 11(3), pages 1-23, January.
    6. Guido, Rosita & Groccia, Maria Carmela & Conforti, Domenico, 2018. "An efficient matheuristic for offline patient-to-bed assignment problems," European Journal of Operational Research, Elsevier, vol. 268(2), pages 486-503.
    7. Bastos, Leonardo S.L. & Marchesi, Janaina F. & Hamacher, Silvio & Fleck, Julia L., 2019. "A mixed integer programming approach to the patient admission scheduling problem," European Journal of Operational Research, Elsevier, vol. 273(3), pages 831-840.
    8. Range, Troels Martin & Kozlowski, Dawid & Petersen, Niels Chr., 2019. "Dynamic job assignment: A column generation approach with an application to surgery allocation," European Journal of Operational Research, Elsevier, vol. 272(1), pages 78-93.
    9. Liu, Haichao & Wang, Yang & Hao, Jin-Kao, 2024. "Solving the patient admission scheduling problem using constraint aggregation," European Journal of Operational Research, Elsevier, vol. 316(1), pages 85-99.
    10. Roshanaei, Vahid & Luong, Curtiss & Aleman, Dionne M. & Urbach, David, 2017. "Propagating logic-based Benders’ decomposition approaches for distributed operating room scheduling," European Journal of Operational Research, Elsevier, vol. 257(2), pages 439-455.
    11. Fabian Schäfer & Manuel Walther & Alexander Hübner & Heinrich Kuhn, 2019. "Operational patient-bed assignment problem in large hospital settings including overflow and uncertainty management," Flexible Services and Manufacturing Journal, Springer, vol. 31(4), pages 1012-1041, December.
    12. Aleida Braaksma & Martin S. Copenhaver & Ana C. Zenteno & Elizabeth Ugarph & Retsef Levi & Bethany J. Daily & Benjamin Orcutt & Kathryn M. Turcotte & Peter F. Dunn, 2023. "Evaluation and implementation of a Just-In-Time bed-assignment strategy to reduce wait times for surgical inpatients," Health Care Management Science, Springer, vol. 26(3), pages 501-515, September.

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