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The Optimized Social Distance Lab: A Methodology for Automated Building Layout Redesign for Social Distancing
7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021 ; 13164 LNCS:496-501, 2022.
Article in English | Scopus | ID: covidwho-1728598
ABSTRACT
The research considers buildings as a test case for the development and implementation of multi-objective optimized social distance layout redesign. This research aims to develop and test a unique methodology using software Wallacei and the NSGA-II algorithm to automate the redesign of an interior layout to automatically provide compliant social distancing using fitness functions of social distance, net useable space and total number of users. The process is evaluated in a live lab scenario, with results demonstrating that the methodology provides an agile, accurate, efficient and visually clear outcome for automating a compliant layout for social distancing. © 2022, Springer Nature Switzerland AG.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021 Year: 2022 Document Type: Article