A PREFERENCE-BASED APPOINTMENT SCHEDULING PROBLEM WITH MULTIPLE PATIENT TYPES
Journal Title: Endüstri Mühendisliği - Year 2019, Vol 30, Issue 2
Abstract
This paper focuses on the appointment scheduling mechanism of a physician or a diagnostic resource in a healthcare facility. Multiple patient types with different revenues use the facility. The facility observes the number of appointment requests arriving from each patient type at the beginning of each day. It decides on how to allocate available appointment slots to these appointment requests. Patients prefer a day in the booking horizon with a specific probability and they have only one preference. Patients are either given an appointment for their preferred days or their appointment requests are rejected. The facility wants to keep the rejection costs at a certain level, while maximizing its revenues. This process is modeled with a discrete time and constrained Markov Decision Process to maximize the infinite-horizon expected discounted revenue. The constraint guarantees that the infinite-horizon expected discounted rejection cost is below a specific threshold. We have proved that the optimal policy is a randomized booking limit policy. To solve the model, we have implemented Temporal Difference (TD) Learning Algorithm, which is a well-known Approximate Dynamic Programming (ADP) method. We have compared the ADP results with other heuristics numerically.
Authors and Affiliations
Feray TUNÇALP, Lerzan ÖRMECİ
Keywords
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