Journal
HEALTH CARE MANAGEMENT SCIENCE
Volume 17, Issue 1, Pages 60-76Publisher
SPRINGER
DOI: 10.1007/s10729-013-9253-z
Keywords
Chemotherapy scheduling; Markov decision processes; Approximate dynamic programming
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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.
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