An extended MABAC method for multiple-attribute group decision making under probabilistic T-spherical hesitant fuzzy environment

Abstract

PurposeThe purpose of this article is to present the idea of a T-spherical hesitant fuzzy set associated with probability and to develop an extended multi-attributive border approximation area comparison (MABAC) method under probabilistic T-spherical hesitant fuzzy (Pt-SHF) settings.Design/methodology/approachThe authors define some basic operational laws for Pt-SHF sets (Pt-SHFSs) and a comparison method of two probabilistic T-spherical hesitant fuzzy numbers (Pt-SHFNs) is proposed. Moreover, some Pt-SHF aggregation operators and the multi-attributive border approximation area comparison (MABAC) method are established under Pt-SHF scenario to solve group decision making problems.FindingsThe developed Pt-SHF MABAC method for multi-attribute group decision making (MAGDM) can overcome the drawbacks of conventional MABAC method and limitations for decision makers, which they face while providing their assessment concerning any object.Research limitations/implicationsClearly, this paper is devoted to MABAC method, MAGDM and probabilistic T-spherical hesitant fuzzy set theory.Practical implicationsThe approach established can be used in a variety of scenarios, including decision making, engineering, and economics. An explanatory example is illustrated which shows the superiority and effectiveness of our proposed technique.Originality/valueIf a T-spherical fuzzy MAGDM problem under the probabilistic scenario needs to be evaluated, the involvement of probabilities in fuzzy system will be lost because of no information. This work fills a gap in literature by establishing the notion of probabilistic t-spherical hesitant fuzzy set to deal with the ambiguity, uncertainty in decision making problems.

Enhancing group decision-making for emergency medical supplies supplier selection using T-spherical fuzzy information: An interaction and feedback mechanism-based approach

“…Debnath et al 57 In 59 , T-SF Power Muirhead mean operator-based MAGDM is established to tackle the decision problem of daily life. Researchers who are interested are directed to some decent literature on MAGDM using T-SFSs [60][61][62][63] .…”

An Improved FMEA-MABAC Method Based on Prospect Theory in a Q-Rung Orthopair Hesitant Fuzzy Environment: A Case Study on Risk Assessment of Aircraft Landing System

“…It is based on the distance of evaluation matrix obtained from each decision maker to the border approximation area matrix. Numerous studies based on application of MABAC method to decision making theory are available in the literature (Java et al, 2022;Jiang et al, 2022;Su et al, 2022;Liu and Wang, 2022;Gurmani et al, 2022).…”

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

“…Chen et al (2021) unfolded generalized and group-generalized T-SF geometric aggregation operations (including (ordered) weighted and hybrid geometric operations) to support multiple-criteria assessments. Next, in the circumstances of probabilistic T-spherical hesitant ambiguity, Gurmani et al (2022) initiated aggregation operators and advanced an extended approach for boundary approximation region comparison in treating group decision issues. In intervalvalued T-SF circumstances, Hussain et al (2022a) utilized Frank aggregation operators to propose a method of assessing business proposals.…”

“…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.…”