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1754. Appointment Scheduling with Updates: An Exact and Optimal Approach

Invited abstract in session WA-39: Stochastic Models in Service Operations II, stream Stochastic Modelling.

Wednesday, 8:30-10:00
Room: 35 (building: 306)

Authors (first author is the speaker)

1. Roshan Mahes
2. Alex Kuiper
Business Analytics, 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 a fixed schedule. However, technological advancements have opened up the possibility of communicating 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. Therefore, the static appointment scheduling problem is extended to a dynamic setting that allows the rescheduling of future clients.

Three rescheduling paradigms - via arrivals, the timeline, or the waiting room - are introduced that can be solved to optimality via dynamic programming. By rescheduling, the scheduler takes control over the running session, and the experiments indicate that total costs are significantly decreasing, even with relatively few updates. The benefits concentrate on increasing utilization (less idling). The magnitude of the decrease is moderated by the length of the grace period, which accounts for not sending updates to clients possibly underway. Also, we argue that the third paradigm is most effective for rescheduling.

Keywords

Status: accepted

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