Type-2 fuzzy preference relation based on new definition and its application in multi-criteria decision-making

被引：0
作者：
Xu, Ting-Ting [1 ]
Qin, Jin-Dong [1 ,2 ]
机构：
[1] School of Management, Wuhan University of Technology, Wuhan
[2] Research Center for Data Science and Intelligent Decision Making, Wuhan University of Technology, Wuhan
来源：
Kongzhi yu Juece/Control and Decision | 2024年 / 39卷 / 10期
关键词：
decision interpretations; tourism product selection; type-2 fuzzy preference relations; type-2 fuzzy sets;
D O I：
10.13195/j.kzyjc.2023.0610
中图分类号：
学科分类号：
摘要：
A type-2 fuzzy set (T2FS) is essentially a set generated by expanding the membership degree of a fuzzy set into a type-1 fuzzy set, and it is an effective tool to deal with decision analysis problems in complex and uncertain environment. First, this paper systematically reviews the proposed new mathematical representation definition of type-2 fuzzy sets (T2FSs), and further demonstrates its geometric interpretations under different universe conditions. Second, aiming at the significant advantages of type-2 fuzzy preference relations in dealing with multi-criteria decision-making problems in complex decision-making scenarios, basic research is conducted on type-2 fuzzy preference relations and their applications in multi-criteria decision-making. More specifically, the definition and decision interpretations of type-2 fuzzy preference relations are given based on the new mathematical representation method, and the additive as well as multiplicative consistency conditions of type-2 fuzzy preference relations are defined simultaneously. Then, according to the theory on fuzzy preference relations, the related methods and properties of type-2 fuzzy preference relations are constructed and analyzed to illustrate the scientificity and rationality of type-2 fuzzy preference relations and the proposed new mathematical representation definition of T2FSs. Finally, the effectiveness and feasibility of the multi-criteria decision-making method based on type-2 fuzzy preference relations under the new definition are verified by a case study on tourism product selection and a comparative analysis. © 2024 Northeast University. All rights reserved.
引用
收藏
页码：3469 / 3478
页数：9
相关论文
共 37 条
  • [1] Zadeh L A., Fuzzy sets, Information and Control, 8, 3, pp. 338-353, (1965)
  • [2] Bellman R E, Zadeh L A., Decision-making in a fuzzy environment, Management Science, 17, 4, pp. 141-164, (1970)
  • [3] Qin J D, Liu X W., Type-2 fuzzy decision-making theories, methodologies and applications, pp. 161-186, (2019)
  • [4] Qin J D, Xu T T., Type-2 fuzzy decision-making theories and methodologies: A systematic review, Control and Decision, 38, 6, pp. 1510-1523, (2023)
  • [5] Xu T T, Zhang H, Li B Q., Fuzzy entropy and hesitancy entropy in probabilistic hesitant fuzzy information and their applications, Soft Computing, 26, 18, pp. 9101-9115, (2022)
  • [6] Ding X F, Zhu L X., A large group emergency fuzzy decision-making method based on theory of clustering by fast search and find of density peaks, Control and Decision, 37, 12, pp. 3307-3313, (2022)
  • [7] Tang G L, Yang W D, Liu P D., Three-way decisions based on decision-theoretic rough sets with interval type-2 fuzzy information, Control and Decision, 37, 5, pp. 1347-1356, (2022)
  • [8] Xu Z S., Uncertain multi-attribute decision making: Methods and applications, (2015)
  • [9] Wang X Z, Wu C P, Xue N., Fuzzy preference relation and its application, (2016)
  • [10] Zhang J W, Liu F, Tu H N, Et al., A decision-making model with sequential incomplete additive pairwise comparisons, Knowledge-Based Systems, 236, (2022)
1234