Title of Presentation: Mathematical Optimization for Social Distancing
University of Padova, Italy
November 7-13, 2020
The spread of viruses such as SARS-CoV-2 brought new challenges to our society, including a stronger focus on safety across all businesses. In particular, many countries have imposed a minimum social distance between people in order to ensure their safety. This brings new challenges to many customer-related businesses, such as restaurants, offices, etc., on how to located their facilities under distancing constraints. In this talk we propose a parallelism between this problem and the one of locating wind turbines in an offshore area. Even if the two problems may seems very different, there are many analogies between them. In particular, both problems require fitting facilities (turbines or customers) in a given area while ensuring a minimum distance between them. Similarly to nearby customers who can infect each other, also nearby turbines “infect” each other by casting wind shadows (the so-called “wake effect”) that cause production losses. In both problems we want to minimize the overall interference/infection, hence optimal solutions will favor layouts where facilities are as spread as possible. The discovery of this parallelism between the two applications allowed us to apply Mathematical Optimization algorithms originally designed for wind farms, to produce optimized facility layouts subject to social distancing constraints as those arising in the time of COVID-19 pandemic. These methods allow us to challenge the current (manual) layouts and provide new insights on how to improve them. In particular we show that optimized layouts are far from trivial to design and that Mathematical Optimization can make an impact, helping businesses while ensuring safety.
(joint work with Martina Fischetti and Jakob Stoustrup)