Type-2 Neutrosophic Aczel-Alsina Hamy Mean Aggregation Operators for Multiple-Attribute Decision-Making Problems
EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS, vol.18, no.4, 2025 (ESCI, Scopus)
- Publication Type: Article / Article
- Volume: 18 Issue: 4
- Publication Date: 2025
- Doi Number: 10.29020/nybg.ejpam.v18i4.6753
- Journal Name: EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS
- Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
- Open Archive Collection: Digital Heritage Collection
- Azerbaijan State University of Economics (UNEC) Affiliated: Yes
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 aggregation 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.