Possibility Degree and Power Aggregation Operators of Single-Valued Trapezoidal Neutrosophic Numbers and Applications to Multi-Criteria Group Decision-Making

被引:0
|
作者
Wang, Jing [1 ,2 ]
Wang, Jian-qiang [1 ]
Ma, Yin-xiang [1 ]
机构
[1] Cent South Univ, Sch Business, Changsha 410083, Peoples R China
[2] Cent South Univ Forestry & Technol, Int Coll, Changsha 410004, Peoples R China
基金
中国国家自然科学基金;
关键词
Single-valued trapezoidal neutrosophic number; Multi-criteria group decision-making; Possibility degree; Power aggregation operator; INTUITIONISTIC FUZZY NUMBERS; CORRELATION-COEFFICIENT; GEOMETRIC OPERATORS; SET;
D O I
10.1007/s12559-020-09736-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Single-valued trapezoidal neutrosophic numbers (SVTNNs) are very useful tools to describe complex cognitive information because of their advantage in maintaining the completeness and accuracy of information. This paper develops a method based on the single-valued trapezoidal neutrosophic power-weighted aggregation operators and possibility degree of SVTNNs for dealing with multi-criteria group decision-making (MCGDM) problems. First, the limitations of the existing operations for SVTNNs are discussed, and then an improved operation is defined. Moreover, the possibility degree of two SVTNNs with consideration of the influence of risk attitudes is proposed, and the comparison rules for SVTNNs are thereby established. Based on the new operation and possibility degree of SVTNNs, the single-valued trapezoidal neutrosophic power average and single-valued trapezoidal neutrosophic power geometric operators are proposed to aggregate the single-valued trapezoidal neutrosophic information. Furthermore, a single-valued trapezoidal neutrosophic MCGDM method is developed. Finally, an example of a company selecting the most suitable green supplier is provided to present a comparative analysis between the proposed approach and other related methods. This example can demonstrate the effectiveness and flexibility of the proposed methodology.
引用
收藏
页码:657 / 672
页数:16
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