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      Intuitionistic fuzzy fairly operators and additive ratio assessment-based integrated model for selecting the optimal sustainable industrial building options

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          Abstract

          In the past few years, the private sectors and industries have focused their attention on sustainable development goals to achieve the better and more sustainable future for all. To accomplish a sustainable community, one requires to better recognize the fundamental indicators and selects the most suitable sustainable policies in diverse regions of the community. Considering the huge impact of construction industry on sustainable development, very less research efforts have been made to obtain worldwide sustainable elucidations for this type of industry. As a large sector of construction industry, industrial buildings consume enormous amounts of energy and financial assets, and play a key character in job creation and life quality improvement in the community. In order to assess the sustainable industrial buildings by means of multiple indicators, the present study introduces a hybrid multi-criteria decision-making methodology which integrates the fairly aggregation operator, the MEthod based on the Removal Effects of Criteria (MEREC), the stepwise weight assessment ratio analysis (SWARA) and the additive ratio assessment (ARAS) methods with intuitionistic fuzzy set (IFS). In this respect, firstly new intuitionistic fuzzy weighted fairly aggregation operators are proposed and then employed to aggregate the decision information in the proposed hybrid method. This operator overcomes the limitations of basic intuitionistic fuzzy aggregation operators. To find the criteria weights, an integrated model is presented based on the MEREC for objective weights and the SWARA for subjective weights of indicators under IFS context. To rank the sustainable industrial buildings, an integrated ARAS method is employed from uncertain perspective. Further, a case study concerning sustainable industrial buildings evaluation is presented to illustrate the superiority and practicality of the developed methodology. The advantages of the developed approach are highlighted in terms of stability and reliability by comparison with some of the existing methods.

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          Fuzzy sets

          L.A. Zadeh (1965)
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            Intuitionistic fuzzy sets

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              Best-worst multi-criteria decision-making method

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                Author and article information

                Contributors
                cavallaro@unimol.it
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                28 March 2023
                28 March 2023
                2023
                : 13
                : 5055
                Affiliations
                [1 ]Department of Mathematics, Government College Raigaon, Satna, Madhya Pradesh 485441 India
                [2 ]GRID grid.449504.8, ISNI 0000 0004 1766 2457, Department of Engineering Mathematics, , Koneru Lakshmaiah Education Foundation, ; Guntur, Andhra Pradesh 522302 India
                [3 ]GRID grid.10373.36, ISNI 0000000122055422, Department of Economics, , University of Molise, ; Via De Sanctis, 86100 Campobasso, Italy
                [4 ]GRID grid.56302.32, ISNI 0000 0004 1773 5396, Department of Statistics and Operations Research, College of Sciences, , King Saud University, ; Riyadh, Saudi Arabia
                Article
                31843
                10.1038/s41598-023-31843-x
                10043870
                d561f80d-d5da-41fa-86e6-12ff25337f25
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 January 2023
                : 17 March 2023
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                © The Author(s) 2023

                Uncategorized
                computational science,environmental impact
                Uncategorized
                computational science, environmental impact

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