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

Author

Listed:
  • Shahzaib Ashraf
  • Shakoor Ahmad
  • Muhammad Naeem
  • Muhammad Riaz
  • Md. Ashraful Alam

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.

Suggested Citation

  • Shahzaib Ashraf & Shakoor Ahmad & Muhammad Naeem & Muhammad Riaz & Md. Ashraful Alam, 2022. "Novel EDAS Methodology Based on Single‐Valued Neutrosophic Aczel‐Alsina Aggregation Information and Their Application in Complex Decision‐Making," Complexity, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:2394472
    DOI: 10.1155/2022/2394472
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    References listed on IDEAS

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    1. Muhammad Jabir Khan & Poom Kumam & Peide Liu & Wiyada Kumam & Shahzaib Ashraf, 2019. "A Novel Approach to Generalized Intuitionistic Fuzzy Soft Sets and Its Application in Decision Support System," Mathematics, MDPI, vol. 7(8), pages 1-21, August.
    2. Juan-juan Peng & Jian-qiang Wang & Jing Wang & Hong-yu Zhang & Xiao-hong Chen, 2016. "Simplified neutrosophic sets and their applications in multi-criteria group decision-making problems," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(10), pages 2342-2358, July.
    3. Peide Liu & Peng Wang, 2017. "Some Improved Linguistic Intuitionistic Fuzzy Aggregation Operators and Their Applications to Multiple-Attribute Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 817-850, May.
    4. Muhammad Qiyas & Saleem Abdullah & Shahzaib Ashraf & Lazim Abdullah, 2019. "Linguistic Picture Fuzzy Dombi Aggregation Operators and Their Application in Multiple Attribute Group Decision Making Problem," Mathematics, MDPI, vol. 7(8), pages 1-22, August.
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    1. Shahzaib Ashraf & Razia Choudhary & Muhammad Sohail & Gokul K. C., 2025. "Optimizing Business Investments Using a Novel Approach Based on Picture Hesitant Fuzzy Soft Aggregation Information," Journal of Mathematics, John Wiley & Sons, vol. 2025(1).

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