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The spread of COVID-19 and similar viruses poses new challenges for our society. There is a strong incentive towards safety measures that help to mitigate the outbreaks. Many countries have imposed social distancing measures that require a minimum distance between people in given places, such as schools, restaurants, shops, etc. This in turn creates complications for these places, as their function is to serve as many people as they were originally designed for. In this article, we pose the problem of using the available space in a given place, such that the social distancing measures are satisfied, as a p-dispersion problem. We use recent algorithmic advancements, that were developed for the p-dispersion problem, and combine them with discretization schemes to find computationally attainable solutions to the p-dispersion problem and investigate the trade-off between the level of discretization and computational efforts on one side, and the value of the optimal solution on the other.

Social Distancing as p-Dispersion Problem