IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v235y2014i1p252-264.html
   My bibliography  Save this article

A column generation approach for solving the patient admission scheduling problem

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221713008734
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2013.10.050?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. 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.
    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. 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. 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.
    10. 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.
    11. 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.

    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. Range, Troels Martin & Lusby, Richard Martin & Larsen, Jesper, 2013. "A column generation approach for solving the patient admission scheduling problem," Discussion Papers on Economics 1/2013, University of Southern Denmark, Department of Economics.
    2. Ana Batista & Jorge Vera & David Pozo, 2020. "Multi-objective admission planning problem: a two-stage stochastic approach," Health Care Management Science, Springer, vol. 23(1), pages 51-65, March.
    3. 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.
    4. 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.
    5. Omer, Jérémy & Soumis, François, 2015. "A linear programming decomposition focusing on the span of the nondegenerate columns," European Journal of Operational Research, Elsevier, vol. 245(2), pages 371-383.
    6. repec:ipg:wpaper:2013-014 is not listed on IDEAS
    7. de Lima, Vinícius L. & Alves, Cláudio & Clautiaux, François & Iori, Manuel & Valério de Carvalho, José M., 2022. "Arc flow formulations based on dynamic programming: Theoretical foundations and applications," European Journal of Operational Research, Elsevier, vol. 296(1), pages 3-21.
    8. Steffen Heider & Jan Schoenfelder & Thomas Koperna & Jens O. Brunner, 2022. "Balancing control and autonomy in master surgery scheduling: Benefits of ICU quotas for recovery units," Health Care Management Science, Springer, vol. 25(2), pages 311-332, June.
    9. Sebastian Rachuba & Brigitte Werners, 2017. "A fuzzy multi-criteria approach for robust operating room schedules," Annals of Operations Research, Springer, vol. 251(1), pages 325-350, April.
    10. Zhang, Yu & Wang, Yu & Tang, Jiafu & Lim, Andrew, 2020. "Mitigating overtime risk in tactical surgical scheduling," Omega, Elsevier, vol. 93(C).
    11. Şeyda Gür & Mehmet Pınarbaşı & Hacı Mehmet Alakaş & Tamer Eren, 2023. "Operating room scheduling with surgical team: a new approach with constraint programming and goal programming," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1061-1085, December.
    12. F. Davarian & J. Behnamian, 2022. "Robust finite-horizon scheduling/rescheduling of operating rooms with elective and emergency surgeries under resource constraints," Journal of Scheduling, Springer, vol. 25(6), pages 625-641, December.
    13. Weiya Zhong & Yun Shi, 2018. "Two-stage no-wait hybrid flowshop scheduling with inter-stage flexibility," Journal of Combinatorial Optimization, Springer, vol. 35(1), pages 108-125, January.
    14. John Bowers, 2013. "Balancing operating theatre and bed capacity in a cardiothoracic centre," Health Care Management Science, Springer, vol. 16(3), pages 236-244, September.
    15. Gartner, Daniel & Kolisch, Rainer, 2014. "Scheduling the hospital-wide flow of elective patients," European Journal of Operational Research, Elsevier, vol. 233(3), pages 689-699.
    16. Riise, Atle & Mannino, Carlo & Lamorgese, Leonardo, 2016. "Recursive logic-based Benders’ decomposition for multi-mode outpatient scheduling," European Journal of Operational Research, Elsevier, vol. 255(3), pages 719-728.
    17. Michael Samudra & Carla Van Riet & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2016. "Scheduling operating rooms: achievements, challenges and pitfalls," Journal of Scheduling, Springer, vol. 19(5), pages 493-525, October.
    18. Cappanera, Paola & Visintin, Filippo & Banditori, Carlo, 2014. "Comparing resource balancing criteria in master surgical scheduling: A combined optimisation-simulation approach," International Journal of Production Economics, Elsevier, vol. 158(C), pages 179-196.
    19. Duma, Davide & Aringhieri, Roberto, 2019. "The management of non-elective patients: shared vs. dedicated policies," Omega, Elsevier, vol. 83(C), pages 199-212.
    20. Azar, Macarena & Carrasco, Rodrigo A. & Mondschein, Susana, 2022. "Dealing with uncertain surgery times in operating room scheduling," European Journal of Operational Research, Elsevier, vol. 299(1), pages 377-394.
    21. Lizhong Zhao & Chen-Fu Chien & Mitsuo Gen, 2018. "A bi-objective genetic algorithm for intelligent rehabilitation scheduling considering therapy precedence constraints," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 973-988, June.

    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:eee:ejores:v:235:y:2014:i:1:p:252-264. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.