A Generalized Triangular Intuitionistic Fuzzy Geometric Averaging Operator for Decision-Making in Engineering and Management

Abstract

Triangular intuitionistic fuzzy number (TIFN) is a more generalized platform for expressing imprecise, incomplete, and inconsistent information when solving multi-criteria decision-making problems, as well as for expressing and reflecting the evaluation information in several dimensions. In this paper, the TIFN has been applied for solving multi-criteria decision-making (MCDM) problems, first, by defining some existing triangular intuitionistic fuzzy geometric aggregation operators, and then developing a new triangular intuitionistic fuzzy geometric aggregation operator, which is the generalized triangular intuitionistic fuzzy ordered weighted geometric averaging (GTIFOWGA) operator. Based on these operators, a new approach for solving multicriteria decision-making problems when the weight information is fixed is proposed. Finally, a numerical example is provided to show the applicability and rationality of the presented method, followed by a comparative analysis using similar existing computational approaches.

Evaluation of Renewable Energy Technology Based on Reliability Attributes Using Hybrid Fuzzy Dynamic Decision-Making Model

“…Different improvements have been made on OWA operator; two new versions of OWA are weighted OWA (WOWA) operator and its interpolation function [18], and the ordered weighted geometric averaging (OWGA) operator [19]. Other efforts that have been made on operator usage are reported in the works of Park et al [20], Xu and Yager [21], Zhou and Chen [22], Aikhuele and Odofin [23], Gümüş and Bali [24], and Yin et al [25]. Among these works, Gümüş and Bali's [24] is selected for the current problem.…”

Intuitionistic fuzzy model for reliability management in wind turbine system

“…Þ for all ði ¼ 1; 2; 3; :::; nÞ be a collection of Triangular Intuitionistic Fuzzy Numbers on X. The triangular intuitionistic hybrid fuzzy weighted geometric (TIHFWG) operator of dimension n is a mapping TIHFWG: Ω n → Ω , and associated with the weighting vector ω ¼ ðω 1 ; ω 2 ; ω 3 ; Á Á Á ; ω n Þ T to it, such that ω i ∈ ½0; 1; P n i¼1 ω i ¼ 1; and is defined to aggregate a collection of intuitionistic fuzzy values ðα 1 ; α 2 ; α 3 ; Á Á Á ; α n Þ, [32,34].…”

“…and is defined to aggregate a collection of intuitionistic fuzzy values ðα 1 ; α 2 ; α 3 ; Á Á Á ; α n Þ, [32,34].…”

Prediagnosis of Disease Based on Symptoms by Generalized Dual Hesitant Hexagonal Fuzzy Multi-Criteria Decision-Making Techniques

“…In addition to medical diagnosis, a great deal of study in other areas [14,15] involving hesitant fuzzy sets has been carried out. Additionally, many studies have been conducted on generalized fuzzy numbers, including generalized triangular intuitionistic fuzzy numbers (GTIFN) [16], generalized trapezoidal hesitant fuzzy numbers (GTrHFN) [2], generalized hesitant fuzzy numbers (GHFN) [8], and generalized hexagonal fuzzy numbers (GH χ FN) [17]. However, as far as we know, there is currently no research on the use of a generalized dual hesitant hexagonal fuzzy (GDHH χ F) MCDM technique for disease recognition.…”