Table Organization Optimization in Schools for Preserving the Social Distance during the COVID-19 Pandemic

Autor: Rubén Ferrero-Guillén, Javier Díez-González, Paula Verde, Rubén Álvarez, Hilde Perez
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Applied Sciences, Vol 10, Iss 23, p 8392 (2020)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app10238392
Popis: The COVID-19 pandemic has supposed a challenge for education. The school closures during the initial coronavirus outbreak for reducing the infections have promoted negative effects on children, such as the interruption of their normal social relationships or their necessary physical activity. Thus, most of the countries worldwide have considered as a priority the reopening of schools but imposing some rules for keeping safe places for the school lessons such as social distancing, wearing facemasks, hydroalcoholic gels or reducing the capacity in the indoor rooms. In Spain, the government has fixed a minimum distance of 1.5 m among the students’ desks for preserving the social distancing and schools have followed orthogonal and triangular mesh patterns for achieving valid table dispositions that meet the requirements. However, these patterns may not attain the best results for maximizing the distances among the tables. Therefore, in this paper, we introduce for the first time in the authors’ best knowledge a Genetic Algorithm (GA) for optimizing the disposition of the tables at schools during the coronavirus pandemic. We apply this GA in two real-application scenarios in which we find table dispositions that increase the distances among the tables by 19.33% and 10%, respectively, with regards to regular government patterns in these classrooms, thus fulfilling the main objectives of the paper.
Databáze: Directory of Open Access Journals