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The Physician Scheduling of Fever Clinic in the Covid-19 Pandemic
IEEE Transactions on Automation Science and Engineering ; 2021.
Article in English | Scopus | ID: covidwho-1515168
ABSTRACT
This article addresses a weekly physician scheduling problem in Covid-19. This problem has arisen in fever clinics in two collaborative hospitals located in Shanghai, China. Because of the coronavirus pandemic, the hospitals must consider some specific constraints in the scheduling problem. For example, due to social distance limitation, the patient queue lengths are much longer in the coronavirus pandemic, even with the same waiting patients. Thus, the hospitals must consider the maximum queue length in the physician scheduling problem. Moreover, the fever clinic's scheduling rules are different from those in the common clinic, and some specific regulatory constraints have to be considered in the epidemic. We first build a mathematical model for this problem, in which a pointwise stationary fluid flow approximation method is used to compute the queue length. Some linearization techniques are designed to make the problem can be solved by commercial solvers, such as Gurobi. We find that solving this model from practical applications of the hospital within an acceptable computation time is challenging. Consequently, we develop an efficient two-phase approach to solve the problem. A staffing model and a branch-and-price algorithm are proposed in this approach. The performances of our models and approaches are discussed. The effectiveness of the proposed algorithms for real-life data from collaborative hospitals is validated. IEEE

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: IEEE Transactions on Automation Science and Engineering Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: IEEE Transactions on Automation Science and Engineering Year: 2021 Document Type: Article