Modified EDAS Method for MAGDM Based on MSM Operators with 2-Tuple Linguistic $T$-Spherical Fuzzy Sets

Abstract

The coronavirus (COVID-19) pandemic, which began in China and is fast spreading around the world, has increased the number of cases and deaths. Governments have suffered substantial damage and losses not only in the health sector but also in a variety of other areas. In this situation, it is critical to determine the most crucial vaccine that doctors and specialists should implement. In order to evaluate the many vaccines to control the COVID-19 epidemic, a decision problem based on the decisions of many experts, with some contradicting and multiple criteria, should be taken into account. This decision process is characterized as a multiattribute group decision-making (MAGDM) problem that includes uncertainty in this study. T -spherical fuzzy sets are utilized for this, allowing decision-experts to make evaluations over a larger area and better deal with complicated data. The T -spherical fuzzy set is a useful tool for dealing with uncertainty and ambiguity, especially where additional answers of the type “yes,” “no,” “abstain,” and “refusal” are required, and the 2-tuple linguistic terms are useful for the qualitative evaluation of uncertain data. From the perspective of the uncertainty surrounding the problems of MAGDM, we propose the notion of 2-tuple linguistic T -spherical fuzzy numbers (2TL T -SFNs) generated with the integration of T -spherical fuzzy numbers and 2-tuple linguistic terms. Then, the assessment based on distance from average solution (EDAS) for the ranking of alternatives based on the 2TL T -SFNs is investigated as a new decision-making strategy. This study provides the following significant contributions: (1) the procedure for constructing a 2TL T -SFNs is described, together with their aggregation operators, ranking criteria, relevant attributes, and some operational laws. (2) The traditional Maclaurin symmetric mean (MSM) operator is useful for modeling attribute interrelationships and aggregating 2TL T -SF information to tackle the MAGDM problems. A few recent MSM and dual MSM operators are being built to evaluate the 2TL T -SF information. Thus, 2-tuple linguistic T -spherical fuzzy Maclaurin symmetric mean (2TL T -SFMSM) operator, 2-tuple linguistic T -spherical fuzzy weighted Maclaurin symmetric mean (2TL T -SFWMSM) operator, 2-tuple linguistic T -spherical fuzzy dual Maclaurin symmetric mean (2TL T -SFDMSM) operator, and 2-tuple linguistic T -spherical fuzzy weighted dual Maclaurin symmetric mean (2TL T -SFWDMSM) operator are proposed. (3) We incorporate the 2TL T -SFNs into the EDAS approach and develop a new 2TL T -SF-EDAS method for solving the MAGDM problems based on the proposed aggregation operators in a 2TL T -SF environment. A case study for the selection of an optimal vaccine to control the outbreak of the COVID-19 epidemic is also presented to show the validity of the proposed methodology. Furthermore, the comparative analysis with existing approaches shows the advantages and superiority of the proposed framework.

Retracted: Modified EDAS Method for MAGDM Based on MSM Operators with 2‐Tuple Linguistic T‐Spherical Fuzzy Sets

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”

Multiple criteria decision analytic methods in management with T-spherical fuzzy information

“…A problem concerning smart grids in a T-SF uncertain environment was investigated by Naseem et al ( 2022 ), who employed T-SF (power) Maclaurin symmetric averaging procedures to support group judgments when evaluating the smart grid networks in Pakistan. Naz et al ( 2022 ) coupled 2-tuple linguistic terminology with the T-SF model to present a group choice technique grounded in extended 2-tuple linguistic T-SF (dual) Maclaurin symmetric averaging operations. Wang ( 2021 ) considered the intentions of group experts and interactions among individual experts under symmetric and complete information, proposed a distance metric and preordering rule for T-SF rough numbers, and generalized the interaction operational laws for Heronian mean-based group decision analyzation.…”

“…T-SF sets can be deployed to cope with exceedingly uncertain information, enabling decision-makers (or analysts) to evaluate in a broader variety, with more flexibility, and to manage complex data (Ali et al 2022 ; Naseem et al 2022 ; Wang and Ullah 2022 ). T-SF sets are a beneficial tool for dealing with ambiguity and uncertainty when extra answers of the four forms, i.e., positivity, neutrality, negativity, and refusal, are sought in multiple-criteria assessment and selection issues (Chen 2022a ; 2022c ; Naz et al 2022 ). Natural language expressions in T-SF settings are also beneficial for identifying the qualitative evaluation of unclear data (Akram et al 2023 ; Naz et al 2022 ; Wang 2022 ).…”

“…T-SF sets are a beneficial tool for dealing with ambiguity and uncertainty when extra answers of the four forms, i.e., positivity, neutrality, negativity, and refusal, are sought in multiple-criteria assessment and selection issues (Chen 2022a ; 2022c ; Naz et al 2022 ). Natural language expressions in T-SF settings are also beneficial for identifying the qualitative evaluation of unclear data (Akram et al 2023 ; Naz et al 2022 ; Wang 2022 ). T-SF theory can produce a successful decision-making technique for assessing and choosing options in sophisticated fuzzy environments through varied T-SF decision-analysis tools created by numerous academics (Abid et al 2022 ; Chen 2022b ; 2022d ; Karaaslan and Al-Husseinawi 2022 ; Yang and Pang 2022 ).…”

MAGDM for selecting machine learning techniques: A novel approach utilizing the 2-tuple linguistic cubic q-rung orthopair fuzzy set

“…After this, the q-ROF linguistic family of point aggregation operators (AOs) was developed by Liu et al [19]. In order to address the ambiguity surrounding the MAGDM difficulties, Naz et al [20] presented the idea of 2TL T -spherical fuzzy numbers, which were proposed by combining T -spherical fuzzy numbers and 2TL terms. Akram et al [21] developed a new class of fuzzy graphs called linguistic q-ROF graphs, which is inspired by the concept of linguistic q-ROFS and make use of the flexible nature of the Einstein operator to further explore effective solutions for MAGDM problems.…”