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Appointment scheduling in tandem-type service systems

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  • Kuiper, Alex
  • Mandjes, Michel

Abstract

Appointment-based service systems arise in a broad variety of healthcare settings (for example an outpatient clinic or a dentist). Where most existing algorithms specifically consider the situation of the patient undergoing a single service, in many practical situations multiple services have to be sequentially performed. Modeling the service system as a tandem queue, the main objective of this paper is to generate schedules that soundly balance the interests of patients (i.e., low waiting times) and staff (i.e., low idle times). Importantly, following up on prior work for the single-node queue, we advocate a phase-type based technique that can deal with any service-time distribution (which may, in addition, vary across patients). Relying on a novel recursive scheme to evaluate the sojourn-time distribution of clients in such tandem systems, we show how optimal schedules can be computed. Our technique is illustrated by extensive numerical experimentation, also leading to practical guidelines that apply to a broad range of parameter settings.

Suggested Citation

  • Kuiper, Alex & Mandjes, Michel, 2015. "Appointment scheduling in tandem-type service systems," Omega, Elsevier, vol. 57(PB), pages 145-156.
    • Handle: RePEc:eee:jomega:v:57:y:2015:i:pb:p:145-156
    DOI: 10.1016/j.omega.2015.04.009
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Pan, Xingwei & Geng, Na & Xie, Xiaolan & Wen, Jing, 2020. "Managing appointments with waiting time targets and random walk-ins," Omega, Elsevier, vol. 95(C).
    2. Hyun-Jung Alvarez-Oh & Hari Balasubramanian & Ekin Koker & Ana Muriel, 2018. "Stochastic Appointment Scheduling in a Team Primary Care Practice with Two Flexible Nurses and Two Dedicated Providers," Service Science, INFORMS, vol. 10(3), pages 241-260, September.
    3. Andrés Miniguano-Trujillo & Fernanda Salazar & Ramiro Torres & Patricio Arias & Koraima Sotomayor, 2021. "An integer programming model to assign patients based on mental health impact for tele-psychotherapy intervention during the Covid–19 emergency," Health Care Management Science, Springer, vol. 24(2), pages 286-304, June.
    4. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    5. Reihaneh, Mohammad & Ansari, Sina & Farhadi, Farbod, 2023. "Patient appointment scheduling at hemodialysis centers: An exact branch and price approach," European Journal of Operational Research, Elsevier, vol. 309(1), pages 35-52.
    6. Jiang, Bowen & Tang, Jiafu & Yan, Chongjun, 2019. "A stochastic programming model for outpatient appointment scheduling considering unpunctuality," Omega, Elsevier, vol. 82(C), pages 70-82.
    7. Nguyen, Thu Ba T. & Sivakumar, Appa Iyer & Graves, Stephen C., 2018. "Capacity planning with demand uncertainty for outpatient clinics," European Journal of Operational Research, Elsevier, vol. 267(1), pages 338-348.
    8. Kuiper, Alex & de Mast, Jeroen & Mandjes, Michel, 2021. "The problem of appointment scheduling in outpatient clinics: A multiple case study of clinical practice," Omega, Elsevier, vol. 98(C).
    9. Alex Kuiper & Robert H. Lee, 2022. "Appointment Scheduling for Multiple Servers," Management Science, INFORMS, vol. 68(10), pages 7422-7440, October.
    10. Nossack, Jenny, 2022. "Therapy scheduling and therapy planning at hospitals," Omega, Elsevier, vol. 109(C).
    11. Kenneth J. Klassen & Reena Yoogalingam, 2019. "Appointment scheduling in multi-stage outpatient clinics," Health Care Management Science, Springer, vol. 22(2), pages 229-244, June.
    12. Creemers, Stefan & Lambrecht, Marc R. & Beliën, Jeroen & Van den Broeke, Maud, 2021. "Evaluation of appointment scheduling rules: A multi-performance measurement approach," Omega, Elsevier, vol. 100(C).

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