Health Care Management Science, vol.17, no.1, pp.60-76, 2014 (SSCI)
We study a scheduling problem in which arriving patients require appointments at specific future days within a treatment specific time window. This research is motivated by a study of chemotherapy scheduling practices at the British Columbia Cancer Agency (Canada). We formulate this problem as a Markov Decision Process (MDP). Since the resulting MDPs are intractable to exact methods, we employ linear-programming-based Approximate Dynamic Programming (ADP) to obtain approximate solutions. Using simulation, we compare the performance of the resulting ADP policies to practical and easy-to-use heuristic decision rules under diverse scenarios. The results indicate that ADP is promising in several scenarios, and that a specific easy-to-use heuristic performs well in the idealized chemotherapy scheduling setting we study. © 2013 Springer Science+Business Media New York.