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Online appointment sequencing and scheduling

Author

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  • S. Ayca Erdogan
  • Alexander Gose
  • Brian T. Denton

Abstract

We formulate and solve a new stochastic integer programming model for dynamic sequencing and scheduling of appointments to a single stochastic server. We assume that service durations and the number of customers to be served on a particular day are uncertain. Customers are sequenced and scheduled dynamically (online) one at a time as they request appointments. We present a two-stage stochastic mixed integer program that uses a novel set of non-anticipativity constraints to capture the dynamic multi-stage nature of appointment requests as well as the sequencing of customers. We describe several ways to improve the computational efficiency of decomposition methods to solve our model. We also present some theoretical findings based on small problems to help motivate decision rules for larger problems. Our numerical experiments provide insights into optimal sequencing and scheduling decisions and the performance of the solution methods we propose.

Suggested Citation

  • S. Ayca Erdogan & Alexander Gose & Brian T. Denton, 2015. "Online appointment sequencing and scheduling," IISE Transactions, Taylor & Francis Journals, vol. 47(11), pages 1267-1286, November.
    • Handle: RePEc:taf:uiiexx:v:47:y:2015:i:11:p:1267-1286
    DOI: 10.1080/0740817X.2015.1011355
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    Citations

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    Cited by:

    1. Thierry Garaix & Salim Rostami & Xiaolan Xie, 2020. "Daily outpatient chemotherapy appointment scheduling with random deferrals," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 129-153, March.
    2. Ilke Bakir & Natashia Boland & Brian Dandurand & Alan Erera, 2020. "Sampling Scenario Set Partition Dual Bounds for Multistage Stochastic Programs," INFORMS Journal on Computing, INFORMS, vol. 32(1), pages 145-163, January.
    3. Eduardo Pérez, 2022. "An Appointment Planning Algorithm for Reducing Patient Check-In Waiting Times in Multispecialty Outpatient Clinics," SN Operations Research Forum, Springer, vol. 3(3), pages 1-22, September.
    4. Dongyang Wang & Kumar Muthuraman & Douglas Morrice, 2019. "Coordinated Patient Appointment Scheduling for a Multistation Healthcare Network," Operations Research, INFORMS, vol. 67(3), pages 599-618, May.
    5. Youngbum Hur & Jonathan F. Bard & Douglas J. Morrice, 2021. "Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 134-155, February.
    6. Bowen Pang & Xiaolei Xie & Feng Ju & James Pipe, 2022. "A dynamic sequential decision-making model on MRI real-time scheduling with simulation-based optimization," Health Care Management Science, Springer, vol. 25(3), pages 426-440, September.
    7. Hesaraki, Alireza F. & Dellaert, Nico P. & de Kok, Ton, 2019. "Generating outpatient chemotherapy appointment templates with balanced flowtime and makespan," European Journal of Operational Research, Elsevier, vol. 275(1), pages 304-318.
    8. Alexander H. Gose & Brian T. Denton, 2016. "Sequential Bounding Methods for Two-Stage Stochastic Programs," INFORMS Journal on Computing, INFORMS, vol. 28(2), pages 351-369, May.
    9. Dogru, Ali K. & Melouk, Sharif H., 2019. "Adaptive appointment scheduling for patient-centered medical homes," Omega, Elsevier, vol. 85(C), pages 166-181.
    10. Sharan Srinivas & A. Ravi Ravindran, 2020. "Designing schedule configuration of a hybrid appointment system for a two-stage outpatient clinic with multiple servers," Health Care Management Science, Springer, vol. 23(3), pages 360-386, September.
    11. Tito Homem-de-Mello & Qingxia Kong & Rodrigo Godoy-Barba, 2022. "A Simulation Optimization Approach for the Appointment Scheduling Problem with Decision-Dependent Uncertainties," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2845-2865, September.
    12. Deceuninck, Matthias & Fiems, Dieter & De Vuyst, Stijn, 2018. "Outpatient scheduling with unpunctual patients and no-shows," European Journal of Operational Research, Elsevier, vol. 265(1), pages 195-207.

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