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A column-generation-based approach for an integrated service planning and physician scheduling problem considering re-consultation

Author

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  • Shaowen Lan

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Wenjuan Fan

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Kaining Shao

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Shanlin Yang

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Panos M. Pardalos

    (University of Florida)

Abstract

In this paper, an integrated service planning and physician scheduling problem in the outpatient department is investigated, considering the re-consultation of patients as well as multiple types of physicians and consultation services. The problem is to determine 1) the number of patients to be served for each type of consultation service in each shift of a planning horizon and, 2) the working schedule for all planned physicians during the horizon, to maximize the total net benefit of the department. An integer programming model is presented as the original model, which is further decomposed into a Master Problem (MP) and several Pricing Problems (PPs). An approach that incorporates the Column Generation (CG) heuristic and the Variable Neighborhood Search algorithm (VNS), i.e., CG-VNS, is developed to solve the problem. In the computational experiments, the proposed CG-VNS is compared with the original model in the small-scale instances. In the large-scale instances, the proposed CG-VNS is compared with CG-Gurobi, which applies the hybrid CG and the solver Gurobi to calculate the restricted MP and the PPs. The performances of the proposed CG-VNS and the CG-Gurobi approach are further tested in the experiments.

Suggested Citation

  • Shaowen Lan & Wenjuan Fan & Kaining Shao & Shanlin Yang & Panos M. Pardalos, 2022. "A column-generation-based approach for an integrated service planning and physician scheduling problem considering re-consultation," Journal of Combinatorial Optimization, Springer, vol. 44(5), pages 3446-3476, December.
  • Handle: RePEc:spr:jcomop:v:44:y:2022:i:5:d:10.1007_s10878-022-00896-5
    DOI: 10.1007/s10878-022-00896-5
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    References listed on IDEAS

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    1. Jens Brunner & Günther Edenharter, 2011. "Long term staff scheduling of physicians with different experience levels in hospitals using column generation," Health Care Management Science, Springer, vol. 14(2), pages 189-202, June.
    2. Jonathan Patrick & Amine Montazeri & Wojtek Michalowski & Diponkar Banerjee, 2019. "Automated Pathologist Scheduling at The Ottawa Hospital," Interfaces, INFORMS, vol. 49(2), pages 93-103, March.
    3. Yann Ferrand & Michael Magazine & Uday S. Rao & Todd F. Glass, 2011. "Building Cyclic Schedules for Emergency Department Physicians," Interfaces, INFORMS, vol. 41(6), pages 521-533, December.
    4. Damcı-Kurt, Pelin & Zhang, Minjiao & Marentay, Brian & Govind, Nirmal, 2019. "Improving physician schedules by leveraging equalization: Cases from hospitals in U.S," Omega, Elsevier, vol. 85(C), pages 182-193.
    5. Huguette Beaulieu & Jacques Ferland & Bernard Gendron & Philippe Michelon, 2000. "A mathematical programming approach for scheduling physicians in the emergency room," Health Care Management Science, Springer, vol. 3(3), pages 193-200, June.
    6. Arvind Venkat & Sunder Kekre & Gajanan G. Hegde & Jennifer Shang & Thomas P. Campbell, 2015. "Strategic Management of Operations in the Emergency Department," Production and Operations Management, Production and Operations Management Society, vol. 24(11), pages 1706-1723, November.
    7. Shnits, Boris & Bendavid, Illana & Marmor, Yariv N., 2020. "An appointment scheduling policy for healthcare systems with parallel servers and pre-determined quality of service," Omega, Elsevier, vol. 97(C).
    8. Kraul, Sebastian & Fügener, Andreas & Brunner, Jens O. & Blobner, Manfred, 2019. "A robust framework for task-related resident scheduling," European Journal of Operational Research, Elsevier, vol. 276(2), pages 656-675.
    9. Pierre Hansen & Nenad Mladenović & José Moreno Pérez, 2010. "Variable neighbourhood search: methods and applications," Annals of Operations Research, Springer, vol. 175(1), pages 367-407, March.
    10. Andreas Fügener & Jens O. Brunner, 2019. "Planning for Overtime: The Value of Shift Extensions in Physician Scheduling," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 732-744, October.
    11. Erhard, Melanie & Schoenfelder, Jan & Fügener, Andreas & Brunner, Jens O., 2018. "State of the art in physician scheduling," European Journal of Operational Research, Elsevier, vol. 265(1), pages 1-18.
    12. Jonathan Patrick & Martin L. Puterman & Maurice Queyranne, 2008. "Dynamic Multipriority Patient Scheduling for a Diagnostic Resource," Operations Research, INFORMS, vol. 56(6), pages 1507-1525, December.
    13. Jan Schoenfelder & Christian Pfefferlen, 2018. "Decision Support for the Physician Scheduling Process at a German Hospital," Service Science, INFORMS, vol. 10(3), pages 215-229, September.
    14. Nazgol Niroumandrad & Nadia Lahrichi, 2018. "A stochastic tabu search algorithm to align physician schedule with patient flow," Health Care Management Science, Springer, vol. 21(2), pages 244-258, June.
    15. Topaloglu, Seyda, 2009. "A shift scheduling model for employees with different seniority levels and an application in healthcare," European Journal of Operational Research, Elsevier, vol. 198(3), pages 943-957, November.
    16. Melissa R. Bowers & Charles E. Noon & Wei Wu & J. Kirk Bass, 2016. "Neonatal Physician Scheduling at the University of Tennessee Medical Center," Interfaces, INFORMS, vol. 46(2), pages 168-182, April.
    17. Jun Pei & Zorica Dražić & Milan Dražić & Nenad Mladenović & Panos M. Pardalos, 2019. "Continuous Variable Neighborhood Search (C-VNS) for Solving Systems of Nonlinear Equations," INFORMS Journal on Computing, INFORMS, vol. 31(2), pages 235-250, April.
    18. Christopher N. Gross & Andreas Fügener & Jens O. Brunner, 2018. "Online rescheduling of physicians in hospitals," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 296-328, June.
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