Performance Measure Using a Multi-Attribute Decision-Making Approach Based on Complex T-Spherical Fuzzy Power Aggregation Operators

Abstract

Performance measurement has a vital role in almost every field of life especially when uncertainty is involved in processing information. The purpose of this research is to use the concept of power aggregation operators (PAOs) of complex T-spherical fuzzy sets (CTSFSs) to analyze the performance measures of software packages. In comparison to other studies, the main advantage of the PAOs of CTSFSs is its ability to feature four possible aspects of the information under uncertainty. In a CTSFSs, each component has further two aspects denoted by their amplitude and phase terms and hence provide us a better ground to deal with practical problems. Another advantage of using PAOs for performance evaluation is the involvement of the relationship of the input arguments that play an essential role in aggregation. Other traditional aggregation operators do not have such capabilities. We aim to develop complex T-spherical fuzzy (TSF) power weighted averaging (CTSFPWA) and complex TSF power weighted geometric (CTSFPWG) operators and evaluated their validity using some tests. Ultimately, using the recommended operators, multi-attribute decision-making (MADM) algorithm is established for the performance evaluation of the software packages. With the help of a numerical example, we demonstrated the proposed MADM algorithm using complex uncertain information. The results show a positive impact by analyzing them after a comparative analysis where the results obtained using complex TSF PAOs seems to be more reliable than the results obtained by using previously developed aggregation operators (AOs).To see the effectiveness of the algorithm, the results are numerically compared by using some existing approaches, and conclusions are drawn.

Multi-attribute decision-making using Archimedean aggregation operator in T-spherical fuzzy environment

“…We aim to apply the proposed technique in complex TSFs power AOs (Khan et al, 2022a), and intervalvalued TSF frank AOs (Hussain et al, 2022).…”

An Uncertain Multiple-Criteria Choice Method on Grounds of T-Spherical Fuzzy Data-Driven Correlation Measures

“…Karaaslan and Al-Husseinawi (2022) presented arithmetic and geometric averaging operations in hesitant T-spherical Dombi fuzzy settings for group decision-making. Khan et al (2022) employed power-weighted averaging and geometric operations in complex T-SF settings to suggest a performance measurement method under uncertainties. Liu et al (2021c) explored Maclaurin symmetric (weighted) mean operators for normal T-SF numbers and utilized such operators for multiple-criteria decision assistance.…”

“…In particular, based on Table 1, it can be easily observed that many researchers discussed the modularization of multiple-criteria choice methods in the context of T-SF sets with aggregation operations or averaging (i.e. mean) operations, such as Akram and Martino (2022), Al-Quran (2021), Chen et al (2021), Gurmani et al (2022), Hussain et al (2022aHussain et al ( , 2022b, Karaaslan and Al-Husseinawi (2022), Khan et al (2022), Liu et al (2021c), Mahnaz et al (2022), Wang (2021), Wang and Zhang (2022), Yang and Pang (2022), Yang et al (2021), Zedam et al (2022), andZeng et al (2021). That is, many of the above works of literature focus on models of aggregating or averaging operations, which belong to a measurement of the central tendency of a finite set of T-SF information.…”

Reliability, Availability, Maintainability, and Dependability Analysis of Cold Standby Series-Parallel System

“…Tsarouhas (2018) analyzed the reliability, availability, and maintainability of wine packaging production system. Khan et al (2022) dealt with performance measure decision-making approach on T-spherical operators. Garg and Garg (2022) discussed the optimization of profit and availability of a single-unit system with imperfect switch over.…”