A Novel and an Efficient CODAS Technique to Solve Real-Life  MAGDM Problems in Fermatean Neutrosophic Environment

S. Bhuvaneshwari; C. Antony Crispin Sweety; Akanksha Singh; Said Broumi; Mohamed  Talea; Prasanta Kumar Raut

Authors

S. Bhuvaneshwari Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India.
C. Antony Crispin Sweety Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India.
Akanksha Singh Department of Mathematics, UIS, Chandigarh University, Gharuan, Mohali, India,
Said Broumi Laboratory of Information Processing, Faculty of Science Ben M’Sik, University of Hassan II, Casablanca
Mohamed Talea Laboratory of Information Processing, Faculty of Science Ben M’Sik, University of Hassan II, Casablanca, Morocco
Prasanta Kumar Raut Trident Academy of Technology, Bhubaneswar, Odisha, India.

Keywords:

Fermatean Neutrosophic Set (FNS); Multi-Criteria Decision Making (MCDM); Multiple Attribute Group Decision Making ; Decision Matrix (D-Mx); Negative Ideal Solution (NIS); Positive Ideal Solution (PIS); FNWAM; FNWGM; Score function (SF); Accuracy Function (AF)

Abstract

As a generalization of fuzzy sets and intuitionistic fuzzy sets, neutrosophic sets, and their
combinations have been developed to represent uncertain, imprecise, incomplete, and inconsistent
information existing in the real world. A neutrosophic set has the potential to be a general
framework for uncertainty analysis in various spectra. On the other hand, the idea of Fermatean
neutrosophic sets (FNSs) is the hybrid model of Fermatean fuzzy sets and neutrosophic sets,
developed to enable the analytical management of ambiguous data from relatively typical real
world decision-making scenarios. In this work, we develop an algorithm to compare the Fermatean
neutrosophic set and the neutrosophic set, Fermatean Neutrosophic Weighted Arithmetic Mean
(FNWAM) and Fermatean Neutrosophic Weighted Geometric Mean (FNWGM) operators as an
accuracy function in addition to the conventional aggregating operators are designed. Further, the
CODAS technique for Multiple Attribute Group Decision Making (MAGDM) problems according
to the defined operators is proposed. Additionally, to make a clear understanding of the presented
study, a university faculty selection problem is studied to illustrate the proposed methodology.
Finally, the results of the above two sets prove the authenticity of this study.

DOI: 10.5281/zenodo.13380314