Safe distancing in the time of COVID-19

Martina Fischetti, Matteo Fischetti and Jakob Stoustrup

European Journal of Operational Research, 2023, vol. 304, issue 1, 139-149

Abstract: The spread of viruses such as SARS-CoV-2 brought new challenges to our society, including a stronger focus on safety across all businesses. Many countries have imposed a minimum social distance among people in order to ensure their safety. This brings new challenges to many customer-related businesses, such as restaurants, offices, theaters, etc., on how to locate their facilities (tables, seats etc.) under distancing constraints. We propose a parallel between this problem and that of locating wind turbines in an offshore area. The discovery of this parallel allows us to apply Mathematical Optimization algorithms originally designed for wind farms, to produce optimized facility layouts that minimize the overall risk of infection among customers. In this way we can investigate the structure of the safest layouts, with some surprising outcomes. A lesson learned is that, in the safest layouts, the facilities are not equally distanced (as it is typically believed) but tend to concentrate on the border of the available area—a policy that significantly reduces the overall risk of contagion.

Keywords: Combinatorial optimization; Social distancing; Mathematical optimization; Mixed integer linear programming; COVID-19 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:304:y:2023:i:1:p:139-149

DOI: 10.1016/j.ejor.2021.07.010

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