A PREFERENCE-BASED APPOINTMENT SCHEDULING PROBLEM WITH MULTIPLE PATIENT TYPES

We consider the appointment scheduling process of a physician in a healthcare facility. There are multiple patient types with different priorities in this facility. The facility observes the number of appointment requests from each patient type at the beginning of each day. The facility decides on how to allocate the arriving appointment requests to available slots over the booking horizon. Each type of pa- tient prefers a day in the booking horizon with a specific probability. We model this system with a constrained Markov Decision Process to maximize the infinite-horizon expected discounted revenue subject to the constraint that the infinite-horizon ex- pected discounted rejection cost is below a specific threshold. Patients have only one preference for the appointment day. Each patient is either given an appointment on the day he/she prefers or the appointment request of that patient is denied. We prove that the optimal policy is a randomized booking limit policy. To solve the model, we use Approximate Dynamic Programming (ADP) techniques. We conduct numerical experiments and compare the results obtained with ADP techniques with some benchmark policies.