Şimşek, ŞeydaÖzceylan, ErenYalçın, Neşe2025-01-062025-01-062022978-303093246-62367-337010.1007/978-3-030-93247-3_372-s2.0-85122526122https://doi.org/10.1007/978-3-030-93247-3_37https://hdl.handle.net/20.500.14669/13804th International Conference on Intelligent Computing and Optimization, ICO 2021 -- 30 December 2021 through 31 December 2021 -- Virtual, Online -- 270349In the COVID-19 era, social distance has become a new source of concern for people. Decision-makers have a limited idea of how to allocate people according to social distance due to the lack of preparedness for the pandemic. It is essential to think about both distributing as many individuals as possible in a particular area and minimizing the infection risk. This new concern’s multi-objective state affords decision-makers the opportunity to solve the problem using enhanced methodologies. The AUGMECON2 method, one of the recent popular generation methods, is used to produce the exact Pareto sets for the problem. The scale and time constraints of the challenge have been examined, and recommendations have been made to decision-makers on the trade-off between the number of people and the infection risk. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.eninfo:eu-repo/semantics/closedAccessAUGMECON2COVID-19Layout optimizationMulti-objective optimizationSocial distancingConference Object390Q4381371