Novel EDAS Methodology Based on Single-Valued Neutrosophic Aczel-Alsina Aggregation Information and Their Application in Complex Decision-Making

Shahzaib Ashraf, Shakoor Ahmad, Muhammad Naeem, Muhammad Riaz, Md. Ashraful Alam and Zeljko Stevic

Complexity, 2022, vol. 2022, 1-18

Abstract: In this article, we proposed an extended EDAS (Evaluation based on Distance from Average Solution) method based on the single-valued neutrosophic (SVN) Aczel-Alsina aggregation information. The fundamental concept of a single-valued neutrosophic (SVN) set is a universal mathematical tool for effectively managing uncertain and imprecise information. To accomplish our goal, we first extend the Aczel-Alsina t-norm and t-conorm to SVN scenarios and introduce a few new SVN operations on which we construct novel SVN aggregation operators. Furthermore, a decision support strategy is built in the SVN framework using the EDAS methodology and the suggested Aczel-Alsina aggregation operators. This method computes the aggregated outcomes of each investigated alternative, as well as their score values. Finally, to demonstrate the functionality of the developed SVN- EDAS, an application has been made related to the role of commercial banks in providing loans to their customers, which has recently affected our world, and the results are compared with other existing methods. The results suggest that the proposed method may overcome the inadequacies of the existing decision method’s lack of decision flexibility by using SVN aggregation operators.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:2394472

DOI: 10.1155/2022/2394472

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