A Policy And Lower Bound for Scheduling Appointments

Cover A Policy And Lower Bound for Scheduling Appointments
A Policy And Lower Bound for Scheduling Appointments
Gloria F M Lee
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This problem has been studied by the operations research community for more than four decades, and readers are referred to Ho and Lau (1992) for an up-to-date review of the literature. Since the problem appears to be analytically intiactable. Many of the. Se studies consist of simulation experiments that assess the performance of heuristic policies; must ol these policies contain parameters that have been fine tuned via simulation. In an extensive simulation study, Ho and Lau compare over 50 sc...heduling rules (including many rules from the literature) in :1 different operating environments. They find that u. > rule performs consistently well for all environments, and identify eight rules that generate an "efficient frontier" with respect to the tradeoff between the patients' expected waiting time- and the physician's expecVd idle time. The authors also provide rule-of-thumb recommendations for the best scheduling iule for various values of the input parameters. In Section 3 of this paper, we construct a suboptimal scheduling policy by iteratively calculating the probability distribution of a patient's service completion time and then de- riving a myopically optimal appointment time for the next patient.

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