 A physician planning framework for polyclinics under uncertaintyMohammad Tohidi, Masoumeh Kazemi Zanjani and Ivan Contreras Omega, 2021, vol. 101, issue C Abstract: In this paper, we present a comprehensive two-level physician planning framework for polyclinics under uncertainty. The first level focuses on clinic scheduling and capacity planning decisions, whereas the second level deals with physician scheduling and operational adjustments decisions. In order to protect the generated schedules against demand uncertainty, the first level is modeled as an adjustable robust scheduling problem, which is solved using an ad hoc cutting plane algorithm. To cope with variability in patients’ treatment times, we formulate the second level as a two-stage stochastic problem and use a sample average approximation scheme to obtain solutions with small optimality gaps. We use a Monte-Carlo simulation algorithm and data obtained from a university health center in Montreal, Canada, to demonstrate the benefits of our planning framework. In particular, we show that the schedule generated by our approach is superior in terms of total cost as compared with the one obtained from a single-level deterministic model. Keywords: OR in health services; Physician scheduling; Robust optimization; Stochastic programming; Monte-Carlo simulation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jomega:v:101:y:2021:i:c:s0305048319308126 Ordering information: This journal article can be ordered from DOI: 10.1016/j.omega.2020.102275 Access Statistics for this article Omega is currently edited by B. Lev More articles in Omega from Elsevier |
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