Dynamic scheduling with due dates and time windows: an application to chemotherapy patient appointment booking
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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.
KeywordsChemotherapy scheduling Markov decision processes Approximate dynamic programming
This research was supported by Martin L. Puterman’s NSERC Discovery Grant and the NSERC CREATE Program in Healthcare Operations and Information Management program. We wish to also thank Antoine Saure for providing us the ADP GAMS code he wrote for solving the kind of problem studied in this research.
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