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Article | Open Access

Fermatean Hesitant Fuzzy Sets for Multiple Criteria Decision-Making with Applications

Department of Biostatistics and Medical Informatics, Istanbul University-Cerrahpaşa, Istanbul 34442, Turkey
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Abstract

The Fermatean hesitant fuzzy set idea obtained by combining Fermatean fuzzy sets and hesitant fuzzy sets can be used in practice to simplify the solution of complicated multi-criteria decision-making problems. Initially, the notion of a Fermatean hesitant fuzzy set has been given, and the operations related to this concept have been presented. The basic properties of aggregation operators based on Fermatean hesitant fuzzy sets have been studied. To choose the best alternative in practice, a novel multi-criteria decision-making method that is obtained with operators has been created. Finally, numerical examples were examined to indicate the effectiveness of the suggested techniques. The main advantages of this work include three points: (1) extending hesitant fuzzy sets to the Fermatean fuzzy case and proposing two types of aggregation operators for the Fermatean hesitant fuzzy information; (2) considering the interaction among decision-makers and among attributes in decision problems, and dealing with this interrelationship by fuzzy measure; (3) introducing the new decision method for the Fermatean hesitant fuzzy environment and enriching the mathematical tools to solve multiple attributes decision-making problems.

Keywords

multiple criteria decision-makingFermatean hesitant fuzzy setFermatean hesitant fuzzy aggregation operatorinfectious disease

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Fuzzy Information and Engineering
Volume 15 Issue 2,
June 2023
Pages 100-127
DOI: 10.26599/FIE.2023.9270011
Cite this article:
Kirişci M. Fermatean Hesitant Fuzzy Sets for Multiple Criteria Decision-Making with Applications. Fuzzy Information and Engineering, 2023, 15(2): 100-127. https://doi.org/10.26599/FIE.2023.9270011

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Received: 07 December 2022
Revised: 17 February 2023
Accepted: 12 March 2023
Published: 30 June 2023
© The Author(s) 2023. Published by Tsinghua University Press.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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