2978. Appointment Scheduling with Updates: An Exact and Optimal Approach
Invited abstract in session TA-13: Appointment scheduling, stream OR in Healthcare (ORAHS).
Tuesday, 8:30-10:00Room: Clarendon SR 1.01
Authors (first author is the speaker)
| 1. | Alex Kuiper
|
| Business Analytics, University of Amsterdam | |
| 2. | Roshan Mahes
|
| University of Amsterdam |
Abstract
Traditionally, appointment schedules have been determined by minimizing a specific cost function consisting of clients' waiting times and server idling. Under stochastic service times, this intra-day problem is predominantly studied in a static sense, assuming that a schedule---after determined---is fixed. Technological advancements now enable real-time communication with clients during the day. Using such channels allows for updating appointment schedules on the fly, for example, by postponing appointments in case of overcrowding. Yet, while its promise is clear, sending updates at the wrong moments, or too many, may be ineffective or unrealistic, potentially causing client confusion and frustration.
Within optimal appointment scheduling, three rescheduling paradigms are introduced that facilitate updating during the day: via arrivals, the timeline, or the waiting room. Each of these demands its own dynamic programming formulation, but they all yield significant savings over static scheduling. Furthermore, the more updates there are, the better the performance becomes, albeit with diminishing returns. Incorporating additional enrichments extends the applicability of the methodology: the inclusion of no-shows, overtime, and grace periods to account for clients underway.
Sending updates enables the scheduler to exert control during the session, which improves the utilization of the scheduled resource. For the first two paradigms,
Keywords
- Health Care
- Programming, Dynamic
- Stochastic Models
Status: accepted
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