IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v158y2014icp28-36.html
   My bibliography  Save this article

A column-generation-based heuristic algorithm for solving operating theater planning problem under stochastic demand and surgery cancellation risk

Author

Listed:
  • Wang, Yu
  • Tang, Jiafu
  • Fung, Richard Y.K.

Abstract

This paper investigated an operating theater allocation problem with uncertain surgery duration and emergency demand. Under the consideration of surgery cancellation, a stochastic model was developed to minimize the total expected operating cost. A trade-off was sought between the total cost of opening operating rooms and the total overtime due to the overbooking of an operating theater. The sample average approximation method was used to transform the stochastic model into a deterministic one. A column-generation-based heuristic (CGBH) algorithm was developed to solve the integer programming problem. The performance of the CGBH algorithm was tested by solving randomly generated instances with given distributions. Multiple heuristic rules for branching were developed and compared from the perspectives of solution quality and efficiency. Numerical results indicated that high surgery cancellation risk helps to reduce the operating costs of hospitals and improve the OR efficiency but results in patients׳ dissatisfaction, and vice versa. This provides management insights for hospital manager to balance the operating costs and patients׳ satisfaction. The CGBH algorithm performed as well as the CPLEX in the solution quality for small-scale problems. This algorithm can obtain solutions within a 5% gap of the lower bound obtained by the linear problem for large-scale problems that cannot be solved by CPLEX.

Suggested Citation

  • Wang, Yu & Tang, Jiafu & Fung, Richard Y.K., 2014. "A column-generation-based heuristic algorithm for solving operating theater planning problem under stochastic demand and surgery cancellation risk," International Journal of Production Economics, Elsevier, vol. 158(C), pages 28-36.
    • Handle: RePEc:eee:proeco:v:158:y:2014:i:c:p:28-36
    DOI: 10.1016/j.ijpe.2014.07.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527314002321
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2014.07.015?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. Oleg V. Shylo & Oleg A. Prokopyev & Andrew J. Schaefer, 2013. "Stochastic Operating Room Scheduling for High-Volume Specialties Under Block Booking," INFORMS Journal on Computing, INFORMS, vol. 25(4), pages 682-692, November.
    2. Hifi, M. & Zissimopoulos, V., 1996. "A recursive exact algorithm for weighted two-dimensional cutting," European Journal of Operational Research, Elsevier, vol. 91(3), pages 553-564, June.
    3. Brian T. Denton & Andrew J. Miller & Hari J. Balasubramanian & Todd R. Huschka, 2010. "Optimal Allocation of Surgery Blocks to Operating Rooms Under Uncertainty," Operations Research, INFORMS, vol. 58(4-part-1), pages 802-816, August.
    4. H. Fei & C. Chu & N. Meskens, 2009. "Solving a tactical operating room planning problem by a column-generation-based heuristic procedure with four criteria," Annals of Operations Research, Springer, vol. 166(1), pages 91-108, February.
    5. Adan, Ivo & Bekkers, Jos & Dellaert, Nico & Jeunet, Jully & Vissers, Jan, 2011. "Improving operational effectiveness of tactical master plans for emergency and elective patients under stochastic demand and capacitated resources," European Journal of Operational Research, Elsevier, vol. 213(1), pages 290-308, August.
    6. Catherine Combes & Nadine Meskens & Celine Rivat, 2008. "Using KDD process to forecast a duration of surgery," Post-Print halshs-00519264, HAL.
    7. Marco E. Lübbecke & Jacques Desrosiers, 2005. "Selected Topics in Column Generation," Operations Research, INFORMS, vol. 53(6), pages 1007-1023, December.
    8. Combes, C. & Meskens, N. & Rivat, C. & Vandamme, J.-P., 2008. "Using a KDD process to forecast the duration of surgery," International Journal of Production Economics, Elsevier, vol. 112(1), pages 279-293, March.
    9. Lamiri, Mehdi & Xie, Xiaolan & Dolgui, Alexandre & Grimaud, Frederic, 2008. "A stochastic model for operating room planning with elective and emergency demand for surgery," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1026-1037, March.
    10. Cardoen, Brecht & Demeulemeester, Erik & Beliën, Jeroen, 2010. "Operating room planning and scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 201(3), pages 921-932, March.
    11. Saremi, Alireza & Jula, Payman & ElMekkawy, Tarek & Wang, G. Gary, 2013. "Appointment scheduling of outpatient surgical services in a multistage operating room department," International Journal of Production Economics, Elsevier, vol. 141(2), pages 646-658.
    12. Ben Bachouch, Rym & Guinet, Alain & Hajri-Gabouj, Sonia, 2012. "An integer linear model for hospital bed planning," International Journal of Production Economics, Elsevier, vol. 140(2), pages 833-843.
    13. Jebali, AIda & Hadj Alouane, Atidel B. & Ladet, Pierre, 2006. "Operating rooms scheduling," International Journal of Production Economics, Elsevier, vol. 99(1-2), pages 52-62, February.
    14. Fei, H. & Chu, C. & Meskens, N. & Artiba, A., 2008. "Solving surgical cases assignment problem by a branch-and-price approach," International Journal of Production Economics, Elsevier, vol. 112(1), pages 96-108, March.
    15. Kim, Seung-Chul & Horowitz, Ira, 2002. "Scheduling hospital services: the efficacy of elective-surgery quotas," Omega, Elsevier, vol. 30(5), pages 335-346, October.
    16. Cynthia Barnhart & Ellis L. Johnson & George L. Nemhauser & Martin W. P. Savelsbergh & Pamela H. Vance, 1998. "Branch-and-Price: Column Generation for Solving Huge Integer Programs," Operations Research, INFORMS, vol. 46(3), pages 316-329, June.
    17. Geon Cho & Dong X. Shaw, 1997. "A Depth-First Dynamic Programming Algorithm for the Tree Knapsack Problem," INFORMS Journal on Computing, INFORMS, vol. 9(4), pages 431-438, November.
    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. Aida Jebali & Ali Diabat, 2015. "A stochastic model for operating room planning under capacity constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7252-7270, December.
    2. Mahdi Noorizadegan & Abbas Seifi, 2018. "An efficient computational method for large scale surgery scheduling problems with chance constraints," Computational Optimization and Applications, Springer, vol. 69(2), pages 535-561, March.
    3. Freeman, Nickolas & Zhao, Ming & Melouk, Sharif, 2018. "An iterative approach for case mix planning under uncertainty," Omega, Elsevier, vol. 76(C), pages 160-173.
    4. Yanbo Ma & Kaiyue Liu & Zheng Li & Xiang Chen, 2022. "Robust Operating Room Scheduling Model with Violation Probability Consideration under Uncertain Surgery Duration," IJERPH, MDPI, vol. 19(20), pages 1-20, October.
    5. Nickolas K. Freeman & Sharif H. Melouk & John Mittenthal, 2016. "A Scenario-Based Approach for Operating Theater Scheduling Under Uncertainty," Manufacturing & Service Operations Management, INFORMS, vol. 18(2), pages 245-261, May.
    6. Marques, Inês & Captivo, M. Eugénia, 2017. "Different stakeholders’ perspectives for a surgical case assignment problem: Deterministic and robust approaches," European Journal of Operational Research, Elsevier, vol. 261(1), pages 260-278.
    7. Aisha Tayyab & Saif Ullah & Mohammed Fazle Baki, 2023. "An Outer Approximation Method for Scheduling Elective Surgeries with Sequence Dependent Setup Times to Multiple Operating Rooms," Mathematics, MDPI, vol. 11(11), pages 1-15, May.
    8. Zhang, Yu & Wang, Yu & Tang, Jiafu & Lim, Andrew, 2020. "Mitigating overtime risk in tactical surgical scheduling," Omega, Elsevier, vol. 93(C).
    9. Shao, Kaining & Fan, Wenjuan & Lan, Shaowen & Kong, Min & Yang, Shanlin, 2023. "A column generation-based heuristic for brachytherapy patient scheduling with multiple treatment sessions considering radioactive source decay and time constraints," Omega, Elsevier, vol. 118(C).
    10. Hossein Hashemi Doulabi & Soheyl Khalilpourazari, 2023. "Stochastic weekly operating room planning with an exponential number of scenarios," Annals of Operations Research, Springer, vol. 328(1), pages 643-664, September.
    11. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    12. 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.
    13. Zhang, Jian & Dridi, Mahjoub & El Moudni, Abdellah, 2020. "Column-generation-based heuristic approaches to stochastic surgery scheduling with downstream capacity constraints," International Journal of Production Economics, Elsevier, vol. 229(C).
    14. Arezoo Atighehchian & Mohammad Mehdi Sepehri & Pejman Shadpour & Kamran Kianfar, 2020. "A two-step stochastic approach for operating rooms scheduling in multi-resource environment," Annals of Operations Research, Springer, vol. 292(1), pages 191-214, September.
    15. Jose M. Molina-Pariente & Erwin W. Hans & Jose M. Framinan, 2018. "A stochastic approach for solving the operating room scheduling problem," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 224-251, June.
    16. Wang, Yu & Zhang, Yu & Tang, Jiafu, 2019. "A distributionally robust optimization approach for surgery block allocation," European Journal of Operational Research, Elsevier, vol. 273(2), pages 740-753.
    17. Hejer Khlif Hachicha & Farah Zeghal Mansour, 2018. "Two-MILP models for scheduling elective surgeries within a private healthcare facility," Health Care Management Science, Springer, vol. 21(3), pages 376-392, September.
    18. Ruiwei Jiang & Siqian Shen & Yiling Zhang, 2017. "Integer Programming Approaches for Appointment Scheduling with Random No-Shows and Service Durations," Operations Research, INFORMS, vol. 65(6), pages 1638-1656, December.
    19. Zheng Zhang & Brian T. Denton & Xiaolan Xie, 2020. "Branch and Price for Chance-Constrained Bin Packing," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 547-564, July.
    20. Stock, Gregory N. & McDermott, Christopher & Anand, Gopesh, 2016. "Average surgeon-level volume and hospital performance," International Journal of Production Economics, Elsevier, vol. 182(C), pages 253-262.
    21. Babak Akbarzadeh & Ghasem Moslehi & Mohammad Reisi-Nafchi & Broos Maenhout, 2020. "A diving heuristic for planning and scheduling surgical cases in the operating room department with nurse re-rostering," Journal of Scheduling, Springer, vol. 23(2), pages 265-288, April.
    22. 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.

    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. 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.
    2. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    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. 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.
    5. 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.
    6. 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.
    7. Jose M. Molina-Pariente & Erwin W. Hans & Jose M. Framinan, 2018. "A stochastic approach for solving the operating room scheduling problem," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 224-251, June.
    8. Lamiri, Mehdi & Grimaud, Frédéric & Xie, Xiaolan, 2009. "Optimization methods for a stochastic surgery planning problem," International Journal of Production Economics, Elsevier, vol. 120(2), pages 400-410, August.
    9. Aisha Tayyab & Saif Ullah & Mohammed Fazle Baki, 2023. "An Outer Approximation Method for Scheduling Elective Surgeries with Sequence Dependent Setup Times to Multiple Operating Rooms," Mathematics, MDPI, vol. 11(11), pages 1-15, May.
    10. Roshanaei, Vahid & Booth, Kyle E.C. & Aleman, Dionne M. & Urbach, David R. & Beck, J. Christopher, 2020. "Branch-and-check methods for multi-level operating room planning and scheduling," International Journal of Production Economics, Elsevier, vol. 220(C).
    11. Akbarzadeh, Babak & Moslehi, Ghasem & Reisi-Nafchi, Mohammad & Maenhout, Broos, 2019. "The re-planning and scheduling of surgical cases in the operating room department after block release time with resource rescheduling," European Journal of Operational Research, Elsevier, vol. 278(2), pages 596-614.
    12. Eun, Joonyup & Kim, Sang-Phil & Yih, Yuehwern & Tiwari, Vikram, 2019. "Scheduling elective surgery patients considering time-dependent health urgency: Modeling and solution approaches," Omega, Elsevier, vol. 86(C), pages 137-153.
    13. Morteza Lalmazloumian & M. Fazle Baki & Majid Ahmadi, 2023. "A two-stage stochastic optimization framework to allocate operating room capacity in publicly-funded hospitals under uncertainty," Health Care Management Science, Springer, vol. 26(2), pages 238-260, June.
    14. repec:ipg:wpaper:2013-014 is not listed on IDEAS
    15. Fei, Hongying & Meskens, Nadine & Combes, Catherine & Chu, Chengbin, 2009. "The endoscopy scheduling problem: A case study with two specialised operating rooms," International Journal of Production Economics, Elsevier, vol. 120(2), pages 452-462, August.
    16. Duma, Davide & Aringhieri, Roberto, 2019. "The management of non-elective patients: shared vs. dedicated policies," Omega, Elsevier, vol. 83(C), pages 199-212.
    17. 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.
    18. Cardoen, Brecht & Demeulemeester, Erik & Beliën, Jeroen, 2010. "Operating room planning and scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 201(3), pages 921-932, March.
    19. Vahid Roshanaei & Curtiss Luong & Dionne M. Aleman & David R. Urbach, 2017. "Collaborative Operating Room Planning and Scheduling," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 558-580, August.
    20. Silva, Thiago A.O. & de Souza, Mauricio C., 2020. "Surgical scheduling under uncertainty by approximate dynamic programming," Omega, Elsevier, vol. 95(C).
    21. Mahdi Noorizadegan & Abbas Seifi, 2018. "An efficient computational method for large scale surgery scheduling problems with chance constraints," Computational Optimization and Applications, Springer, vol. 69(2), pages 535-561, March.

    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:proeco:v:158:y:2014:i:c:p:28-36. 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/ijpe .

    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.