Archimedean t-norm and t-conorm coupled q-rung orthopair fuzzy TOPSIS method for unknown criteria weighting information

作     者：Komal 

作者机构：Doon Univ Sch Phys Sci Dept Math Dehra Dun 248001 Uttaranchal India 

出 版 物：《EXPERT SYSTEMS WITH APPLICATIONS》 (专家系统及其应用)

年 卷 期：2024年第257卷

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The author is thankful to the anonymous referees for providing their valuable comments and suggestions to improve the quality of the paper 

主　　题：Archimedean t-norm and t-conorm Maximizing deviation method MCDM q-ROFS TOPSIS method 

摘      要：To evaluate some real-life multi-criteria decision-making (MCDM) problems, the decision-makers (DMs) need an interactive and flexible MCDM approach that works well for extended decision-making space and has the ability to apply any suitable operational laws to fuse the information under incomplete criteria weighting information. The objective of this study is to propose a multi-criteria group decision-making (MCGDM) approach to evaluate any real-life MCDM problem under incomplete criteria weighting information. To achieve the objective, the paper proposes an integrated MCGDM approach in which the q-rung orthopair fuzzy set (q-ROFS) is used to provide the extended decision-making space to the DMs, a transformative approach is applied to find the DMs weights, the maximizing deviation method is implemented to find the criteria weights, Archimedean t-norm and t-conorm (ATU)-based operational laws are adopted to fuse the information, and the TOPSIS method is applied to rank the alternatives. The proposed integrated MCGDM approach has been applied to a real-life MCDM problem associated with the evaluation of different strategies implemented by governments to contain the COVID-19 pandemic. A sensitivity analysis is conducted to examine the impact of changes in the parameters involved in the proposed MCGDM approach on the results. A comparative analysis is also performed with some existing classical and aggregation operator-based MCDM methods to demonstrate the consistency of the proposed approach. Findings suggest that the proposed MCGDM approach is general and flexible enough to evaluate any real-life MCDM problem under unknown criteria weighting conditions.