Q-rung orthopair hesitant fuzzy preference relations and its group decision-making application

Complex & Intelligent Systems - Trang 1-22 - 2023
Benting Wan1,2, Jiao Zhang2, Harish Garg3,4,5,6,7, Weikang Huang2
1Shenzhen Research Institute, Jiangxi University of Finance and Economics, ShenZhen, China
2School of Software and IoT Engineering, Jiangxi University of Finance and Economics, Nanchang, China
3School of Mathematics, Thapar Institute of Engineering & Technology (Deemed University), Punjab, India
4Department of Mathematics, Graphics Era Deemed to Be University, Dehradun, India
5Applied Science Research Center, Applied Science Private University, Amman, Jordan
6College of Technical Engineering, The Islamic University, Najaf, Iraq
7College of Technical Engineering, Department of Medical Devices Engineering Technologies, National University of Science and Technology, Dhi Qar, Iraq

Tóm tắt

To express the opinions of decision-makers, q-rung orthopair hesitant fuzzy sets (q-ROHFSs) have been employed extensively. Therefore, it is necessary to construct q-rung orthopair hesitant fuzzy preference relations (q-ROHFPRs) as a crucial decision-making tool for decision-makers. The goal of this paper aims to define a new consistency and consensus approach for solving q-ROHFPR group decision-making (GDM) problems. To do this, we first state the definitions of q-ROHFPRs and additive consistent q-ROHFPRs based on q-ROHFSs, an additive consistency index and acceptable additive consistent q-ROHFPRs. Second, based on minimizing the deviation, we establish an acceptable goal programming model for unacceptable additive consistent q-ROHFPRs. Third, an iterative algorithm is created for achieving acceptable consistency and reaching a rational consensus. The degree of rational consensus among individual q-ROHFPRs is quantified by a distance-based consensus index. Afterward, a non-linear programming model is formulated to derive the priority vector of alternatives, which are q-rung orthopair hesitant fuzzy numbers (q-ROHFNs). Based on this model, a GDM model for q-ROHFPRs is then developed. To demonstrate the validity and utility of the proposed GDM model, a case study on the risk assessment of hypertension is provided. The finding of sensitivity and comparison analyses supports the feasibility and efficacy of the suggested approach.

Tài liệu tham khảo

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