title: Dynamic scheduling with due dates and time windows: an application to chemotherapy patient appointment booking.
abstract: 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.
authors.affiliation: Centre for Maintenance Optimization Reliability Engineering, Department of Mechanical Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, ON, M5S 3G8, Canada, gocgun@mie.utoronto.ca.
authors.forename: Yasin
authors.initials: Y
authors.lastname: Gocgun
authors.forename: Martin L
authors.initials: ML
authors.lastname: Puterman
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000008:administration & dosage*; D001071:Appointments and Schedules; D003198:Computer Simulation; D003365:Costs and Cost Analysis; D017598:Efficiency, Organizational; D008390:Markov Chains; D013597:Systems Analysis
chemical_list: D000970:Antineoplastic Agents