Multicriteria decision‐making with proportional distribution based spherical fuzzy fairly aggregation operators

Abstract

Spherical fuzzy sets (SFSs) are strong models for modeling uncertain information in the computational intelligence and decision-making analysis. The key features of SFSs include the sum of the squares of membership grades (positive, neutral, and negative)

Decision algorithm for educational institute selection with spherical fuzzy heronian mean operators and Aczel-Alsina triangular norm

“…There are many types of T-NM and TC-NM, which are the modifications of triangular norms such as Lukasiewicz [ 13 ] T-NM and TC-NM, Drastic [ 14 ] T-NM and TC-NM, Archimedean [ 15 ] and Frank [ 16 ] T-NM and TC-NM. Riaz and Farid [ 17 ] illustrated advanced decision-making approaches and established new strategies using the basic operations of relatively aggregation tools. Seikh and Mandal [ 18 ] anticipated new mathematical methods for q-rung orthopair fuzzy theory by utilizing the properties of Archimedean t-norms.…”

Complex spherical fuzzy Aczel Alsina aggregation operators and their application in assessment of electric cars

“…Zhang et al [ 31 ] proposed new approaches to SF information based on Dombi power Heronian mean and also studied an application of a MAGDM technique. Riaz and Farid [ 32 ] developed a structure of new AOs to overcome dubious and complicated information in a computational and intelligent system based on SF circumstances. An application of vendor management classification and a list of new approaches based on CPFSs was established by Hussain et al [ 33 ].…”

Spherical Fuzzy Information Aggregation Based on Aczel–Alsina Operations and Data Analysis for Supply Chain

“…Farid and Riaz [22] developed several new Einstein interactive geometric AOs for q-rung orthopair fuzzy numbers. Riaz and Farid [23] proposed some proportional distribution based spherical AOs. Farid et al [24] introduced some AOs for the thermal power equipment supplier selection.…”