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Research Article | Open Access

Decision support system based on fuzzy credibility Dombi aggregation operators and modified TOPSIS method

Muhammad Qiyas1Talha Madrar1Saifullah Khan1Saleem Abdullah1Thongchai Botmart2( )Anuwat Jirawattanapaint3
Department of Mathematics, Abdul Wali Khan University Mardan, Mardan, KP, Pakistan
Department of Mathematics, Faculty of Science, Khon Kean University, Khon Kaen 40002, Thailand
Department of Mathematics, Faculty of Science, Phuket Rajabhat University (PKRU), Thailand
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Abstract

The operational law plays an important role in the aggregation operator for group decision system. The aggregation information has high influence in aggregating group decision information. Therefore, the main objective of the proposed work is to develop some operational laws as aggregation operator for fuzzy credibility numbers based on Dombi norms. Dombi operations can benefit from the best operational parameter flexibility. To the best of our knowledge, Dombi operations have so far not been used in for fuzzy credibility numbers (FCNs). Using these Dombi t-norm and t-conorm to define some different fuzzy credibility aggregation operators. i.e., fuzzy credibility Dombi weighted averaging (FCDWA) operator, fuzzy credibility Dombi ordered weighted averaging (FCDOWA) operator, fuzzy credibility Dombi hybrid weighted averaging (FCDHWA) operator. Next, we used TOPSIS method procedure for multi-attribute grouped decision-making (MAGDM). Finally, we provided an example, as well as a discussion of the comparative result analysis, to ensure that their findings are credible and practical.

CLC number: 03E72, 47S40

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AIMS Mathematics
Pages 19057-19082

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Cite this article:
Qiyas M, Madrar T, Khan S, et al. Decision support system based on fuzzy credibility Dombi aggregation operators and modified TOPSIS method. AIMS Mathematics, 2022, 7(10): 19057-19082. https://doi.org/10.3934/math.20221047

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Received: 17 July 2022
Revised: 10 August 2022
Accepted: 18 August 2022
Published: 15 October 2022
©2022 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)