Maclaurin Symmetric Mean Aggregation Operators Based on Spherical Fuzzy Information and Application to Decision-Making

Lemnaouar Zedam; Kifayat Ullah; Hafiz Muhammad Sajjad; Amir Hussain; Azra Parveen

doi:10.47852/bonviewJCCE3202551

Authors

Lemnaouar Zedam Department of Data Analysis and Mathematical Modeling, University of Ghent, Belgium https://orcid.org/0000-0002-1420-9249
Kifayat Ullah Department of Mathematics, Riphah International University, Pakistan https://orcid.org/0000-0002-1438-6413
Hafiz Muhammad Sajjad Department of Mathematics, Riphah International University, Pakistan
Amir Hussain Department of Mathematics, Riphah International University, Pakistan https://orcid.org/0000-0002-3535-9414
Azra Parveen Department of Mathematics, Riphah International University and Department of Business Administration, Bahauddin Zakariya University, Pakistan

DOI:

https://doi.org/10.47852/bonviewJCCE3202551

Keywords:

Maclaurin symmetric mean, aggregation of information, spherical fuzzy information

Abstract

In contemporary information fusion theory, the Maclaurin symmetric mean (MSM) operator is a traditional mean type aggregation operator (AO) that is an appropriate-able technique for aggregating numerical quantities. The MSM operator’s ability to record the relationships between the several input arguments is one of its standout features. The spherical fuzzy set (SFS) is also a remarkable technique that covers the maximum information from real-life scenarios with the help of four grades. This manuscript consists of the development of the MSM and weighted MSM for the information obtained by SFS. Consequently, the spherical fuzzy MSM (SFMSM) and spherical fuzzy weighted MSM (SFWMSM) operators are developed, and their basic properties are studied. Finally, the developed SFMSM and SFWMSM operators have been applied to the real-life problem of the multi-attribute decision-making problem. All the results are compared and then clearly tabulated and graphed.

Received: 24 November 2022 | Revised: 6 January 2023 | Accepted: 23 January 2023

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.