Applications of multi-attribute group decision-making models under triangular interval-type 2 fuzzy to risk preference

被引:0
|
作者
Garg, Harish [1 ]
Kanchana, A. [2 ]
Nagarajan, D. [3 ]
机构
[1] Deemed Univ, Thapar Inst Engn & Technol, Dept Math, Patiala 147004, Punjab, India
[2] Saveetha Univ, Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Math, Chennai, India
[3] Rajalakshmi Inst Technol, Dept Math, Chennai, India
来源
ENGINEERING RESEARCH EXPRESS | 2024年 / 6卷 / 04期
关键词
Type; 2; fuzzy; multi attribute decision making; aggregation; fuzzy entropy; DISTANCE MEASURES; TOPSIS METHOD;
D O I
10.1088/2631-8695/ad8069
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Triangular interval type-2 fuzzy sets, which can handle data with greater ambiguity and uncertainty, can be created by extending type-1 fuzzy sets. They are defined by two membership functions, which are also fuzzy sets. The triangular interval type-2 fuzzy set's bottom and upper bounds are represented by the membership functions defined over the universe discourse. An improved fuzzy multi-attribute interval-valued approach to group decision-making that takes the decision-maker's risk preferences into account. The multi-attribute group decision-making problem can be resolved by using triangular interval type-2 fuzzy numbers since the attribute weight information is completely unknown. The triangular type 2 fuzzy entropy and the data from the group decision matrix are used to calculate the attribute and relative weights; the combination of similarity and proximity yields the decision-maker weight of each attribute; the formula for the triangular type 2 fuzzy distance measure yields the overall superiority of each scheme; comparison and sequencing determine which scheme is the best; and finally, a decision pertaining to the manufacturing company's supplier serves as an example to illustrate the rationale and effectiveness of the proposed strategy.
引用
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页数:21
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