Type-2 Neutrosophic Aczel-Alsina Hamy Mean Aggregation Operators for Multiple-Attribute Decision-Making Problems

Authors

  • Karahan Kara Department of Business, Faculty of Economics and Administrative Sciences, İzmir Democracy University, 35140 İzmir, Türkiye https://orcid.org/0000-0002-1359-0244
  • Galip Cihan Yalçın Department of Business, Faculty of Economics and Administrative Sciences, OSTIM Technical University, 06374 Ankara, Türkiye https://orcid.org/0000-0001-9348-0709
  • Vladimir Simic Széchenyi István University https://orcid.org/0009-0000-4941-7059
  • Dragan Pamucar Department of Applied Mathematical Science, College of Science and Technology, Korea University, Sejong, 30019, Republic of Korea; Faculty of Engineering, Doğuş University, 34775 Umraniye, Istanbul, Türkiye; UNEC Applied Artificial Intelligence Research Center, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan https://orcid.org/0000-0001-8522-1942

DOI:

https://doi.org/10.29020/nybg.ejpam.v18i4.6753

Keywords:

Type-2 Neutrosophic Number, Aczel-Alsina, Hamy Mean, T2NNAAHM, T2NNAAWHM

Abstract

This study introduces novel aggregation operators for Type-2 Neutrosophic Number Sets (T2NNs) by integrating the Hamy Mean with the Aczel-Alsina t-norm and t-conorm operations. The Hamy Mean, a mathematical averaging technique, is particularly effective in contexts characterized by uncertainty and ambiguity, such as fuzzy set theory. Leveraging this, two aggre-
gation operators are proposed: the T2NN Aczel-Alsina Hamy Mean (T2NNAAHM) and the T2NN Aczel-Alsina Weighted Hamy Mean (T2NNAAWHM). The study presents the formal definitions, underlying operations, theoretical foundations, and proofs of these operators. Their applicability is demonstrated through a Multiple-Attribute Decision-Making (MADM) case study, followed by comparative analyses to evaluate their performance and robustness. The findings indicate that T2NNAAHM and T2NNAAWHM are effective tools for decision-making problems involving T2NNs. This research contributes to the field by providing rigorously defined aggregation operators that address uncertainty and ambiguity, thereby enhancing the methodological toolkit available
for complex decision-making scenarios.

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Published

2025-11-05

Issue

Vol. 18 No. 4: (October 2025)

Section

Mathematical and Fuzzy Logic

License

Copyright (c) 2025 Karahan Kara, Galip Cihan Yalçın, Vladimir Simic, Dragan Pamucar

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How to Cite

Type-2 Neutrosophic Aczel-Alsina Hamy Mean Aggregation Operators for Multiple-Attribute Decision-Making Problems. (2025). European Journal of Pure and Applied Mathematics, 18(4), 6753. https://doi.org/10.29020/nybg.ejpam.v18i4.6753