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Research Article | Open Access

Multiple attribute decision-making based on Fermatean fuzzy number

Aliya Fahmi1Fazli Amin2( )Sayed M Eldin3Meshal Shutaywi4Wejdan Deebani5Saleh Al Sulaie6
Department of Mathematics, University of Faisalabad, Faisalabad, Pakistan
Department of Mathematics and Statistics Hazara University Mansehra, Pakistan
Center of Research, Faculty of Engineering, Future University in Egypt New Cairo 11835, Egypt
Department of Mathematics, College of Science & Arts, King Abdul Aziz University, Rabigh, Saudi Arabia
Department of Mathematics, College of Science & Arts, King Abdul Aziz University, Rabigh, Saudi Arabia
Department of Industrial Engineering, College of Engineering in Al-Qunfudah, Umm Al-Qura University, Makkah 21955, Saudi Arabia
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Abstract

Multiple attribute decision-making concerns with production significant in our everyday life. To resolve the problems that decision makers might feel uncertain to choose the suitable assessment values among several conceivable ideals in the procedure. Fuzzy model, and its extensions are extensively applied to MADM problems. In this study, we proposed an innovative Schweizer-Sklar t-norm and t-conorm operation of FFNs, Fermatean fuzzy Schweizer-Sklar operators. They were used as a framework for the development of an MCDM method, which was illustrated by an example to demonstrate its effectiveness and applicability. Finally, a complete limitation study, rational examination, and comparative analysis of the presented approaches has been exhibited, we originate that our technique is superior in offering DMs a better decision-making choice and reducing the restrictions on stating individual partialities.

CLC number: 03B52, 47S40

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AIMS Mathematics
Pages 10835-10863

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Cite this article:
Fahmi A, Amin F, M Eldin S, et al. Multiple attribute decision-making based on Fermatean fuzzy number. AIMS Mathematics, 2023, 8(5): 10835-10863. https://doi.org/10.3934/math.2023550

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Received: 07 November 2022
Revised: 31 January 2023
Accepted: 02 February 2023
Published: 15 May 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)