An Integrated Group Decision-making Method for Hypertension Risk Management Under Interval-valued q-rung Othopair Fuzzy

Abstract

This paper develops a new group decision-making (GDM) method for multi-attribute group decision-making (MAGDM) problems with unknown weights, which integrates Yager operator, CRITIC and WASPAS decision methods under interval-valued q-rung orthopair fuzzy sets (IVq-ROFS). The main contributions of this paper are concluded as below: (1) We first extend the distance measurement to interval-valued q-rung fuzzy numbers (IVq-ROFNs), and proves its properties. And we develop a new score function which is used to measure IVq-ROFNs, and the new score function overcomes the deficiencies of the existing score function. (2) We extend Yager weighted average operator (IVq-ROFYWA) and Yager weighted geometric average operator (IVq-ROFYWG) under IVq-ROFS, and we discuss the properties of IVq-ROFYWA and IVq-ROFYWG operators. (3) We propose a new method to derive expert weights of different alternatives, which can avoid the deficiency of overall decision-making perspective. And we extend deriving attribute weights method based on CRITIC under IVq-ROFS. (4) A new integrated MAGDM method is proposed. The MAGDM method integrates Yager operator, score function, distance measurement, expert weights deriving method, CRITIC method, and WASPAS method. (5) Finally, the group decision-making algorithm is used for hypertension risk management. The results are consistent with experts’ opinions. And comparing and analyzing results show that the proposed MAGDM method is effective and feasible.

Interval-valued q-rung orthopair fuzzy Weber operator and its group decision-making application

“…IVq-ROFS, proposed by Joshi et al (2018), is an extension of interval-valued intuitionistic fuzzy sets (Atanassov 1999) and q-rung orthopair fuzzy sets (Yager 2016). The use of IVq-ROFSs can reduce the time of preparing and processing data for decision-making (Rawat and Komal 2022; Wan et al 2022;Seker et al 2023;Zhong et al 2023), which is widely used in multi-attribute decision-making (MADM) and multi-attribute group decision-making (MAGDM) problems. However, fuzzy operators are required to fuse decision makers (DMs) and attribute information (Wang et al 2019;Gao et al 2020;Javed et al 2022) for solving MAGDM problems.…”