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International Conference on Applied Intelligence and Informatics

AII 2022: Applied Intelligence and Informatics pp 117–126Cite as

Optimized Layout: A Genetic Algorithm for Industrial and Business Application

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1724))

Abstract

Covid-19 epidemic has harmed the global economy. Particularly, the restaurant sector has been severely impacted by the rapid spread of the virus. The use of digital technology (DT) has been utilized to execute risk-reduction methods as service innovation tools. In this work, a genetic algorithm optimization is used to cope with the problems caused by the restrictions due to Covid-19 to optimize the management of the spaces in commercial and industrial structures. The approach through the GA involves the selection of the best members of a population that change genome based on the epochs. The digitization of a commercial or industrial environment becomes an optimal methodology for carrying out virtual design of work environments. Digitization thus becomes a strategy for the reduction of both monetary and time cost. Focusing on the case study, satisfactory results emerge supported by tests that reveal an appreciable robustness and open new scenarios for different applications of the methodology developed in this work, always in the context of optimal management of industrial and commercial spaces.

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Authors and Affiliations

  1. Department of Law, Economics and Human Sciences and Decisions Lab, University Mediterranea of Reggio Calabria, 89125, Reggio Calabria, Italy

    Pasquale Fotia & Massimiliano Ferrara

  2. ICRIOS - The Invernizzi Centre for Research in Innovation, Organization, Strategy and Entrepreneurship, Department of Management and Technology, Bocconi University, Via Sarfatti, 25, 20136, Milan, MI, Italy

    Massimiliano Ferrara

Authors
  1. Pasquale Fotia
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  2. Massimiliano Ferrara
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Corresponding author

Correspondence to Pasquale Fotia .

Editor information

Editors and Affiliations

  1. Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  2. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Cosimo Ieracitano

  3. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  4. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Nadia Mammone

  5. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

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Fotia, P., Ferrara, M. (2022). Optimized Layout: A Genetic Algorithm for Industrial and Business Application. In: Mahmud, M., Ieracitano, C., Kaiser, M.S., Mammone, N., Morabito, F.C. (eds) Applied Intelligence and Informatics. AII 2022. Communications in Computer and Information Science, vol 1724. Springer, Cham. https://doi.org/10.1007/978-3-031-24801-6_9

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