EDAS method for decision support modeling under the Pythagorean probabilistic hesitant fuzzy aggregation information

Abstract

The significance of emergency decision-making (EmDM) has been experienced recently due to the continuous occurrence of various emergency situations that have caused significant social and monetary misfortunes. EmDM assumes a manageable role when it is important to moderate property and live misfortunes and to reduce the negative effects on the social and natural turn of events. Genuine world EmDM issues are usually described as complex, time-consuming, lack of data, and the effect of mental practices that make it a challenging task for decision-makers. This article shows the need to manage the various types of vulnerabilities and to monitor practices to resolve these concerns. In clinical analysis, how to select an ideal drug from certain drugs with efficacy values for coronavirus disease has become a common problem these days. To address this issue, we are establishing a multi-attribute decision-making approach (MADMap) based on the EDAS method under Pythagorean probabilistic hesitant fuzzy information. In addition, an algorithm is developed to address the uncertainty in the selection of drugs in EmDM issues with regards to clinical analysis. The actual contextual analysis of the selection of the appropriate drug to treat coronavirus ailment is utilized to show the practicality of our proposed technique. Finally, with the help of a comparative analysis of the TOPSIS technique, we demonstrate the efficiency and applicability of the established methodology.

New Logarithmic Operational Laws-Based Complex q-Rung Orthopair Fuzzy Aggregation Operators and Their Application in Decision-Making Process

“…Finally, to improve the quality of the explored approaches, comparative analysis, advantages, and graphical representations are also demonstrated. In the future, we will extend the investigated approaches in different fuzzy environments to solve the problems related to decision-making, consensus problems, and so forth [34][35][36][37][38][39][40][41]. 9.…”

Cloud vendor selection for the healthcare industry using a big data-driven decision model with probabilistic linguistic information

“…Balali & Valipour [ 4 ] ordered passive sustainable measures for energy optimization in the Shiraz health center by collecting primary data and using the BWM-EDAS model. Batool et al [ 5 ] selected a suitable drug for the coronavirus as a part of the emergency decision by adopting the aggregation and EDAS methods under the Pythagorean probabilistic hesitant fuzzy information. Chinram et al, [ 10 ] put forward the weighted average operator with EDAS in an intuitionistic rough set context for small hydropower project assessment and selection.…”

New method for emergency decision making with an integrated regret theory-EDAS method in 2-tuple spherical linguistic environment

“…Ashraf and Abdullah [ 54 ] proposed an integrated methodology using spherical fuzzy sets, TOPSIS and grey relational analysis (GRA) methods for dealing with EDM problems. An EDM model based on the Pythagorean probabilistic hesitant fuzzy sets and EDAS method was established by Batool et al [ 2 ]. A dynamic reference point method with the probabilistic linguistic information based on regret theory was presented by Xue et al [ 7 ] for public health EDM.…”

“…In this section, a comparative analysis with some existing EDM methods is conducted to further demonstrate the effectiveness of our proposed method. Four EDM methods, including the spherical fuzzy GRA (SF-GRA) [ 54 ], the interval-valued Pythagorean fuzzy prospect theory (IVPF-PT) [ 2 ], the hesitant fuzzy TODIM (HF-TODIM) [ 1 ] and the Z-uncertain probabilistic fuzzy TOPSIS (ZUPF-TOPSIS) [ 58 ], are applied to rank the emergency alternatives presented in this study. Among them, different fuzzy theories are utilized to depict uncertain EDM information and the ranking orders derived by the listed methods are displayed in Fig.…”