The operational properties of linguistic interval valued q-Rung orthopair fuzzy information and its VIKOR model for multi-attribute group decision making
被引:11
|
作者:
Gurmani, Shahid Hussain
论文数: 0引用数: 0
h-index: 0
机构:
Anhui Univ, Sch Math Sci, Hefei, Anhui, Peoples R ChinaAnhui Univ, Sch Math Sci, Hefei, Anhui, Peoples R China
Gurmani, Shahid Hussain
[1
]
Chen, Huayou
论文数: 0引用数: 0
h-index: 0
机构:
Anhui Univ, Sch Math Sci, Hefei, Anhui, Peoples R ChinaAnhui Univ, Sch Math Sci, Hefei, Anhui, Peoples R China
Chen, Huayou
[1
]
Bai, Yuhang
论文数: 0引用数: 0
h-index: 0
机构:
Anhui Univ, Sch Math Sci, Hefei, Anhui, Peoples R ChinaAnhui Univ, Sch Math Sci, Hefei, Anhui, Peoples R China
Bai, Yuhang
[1
]
机构:
[1] Anhui Univ, Sch Math Sci, Hefei, Anhui, Peoples R China
Linguistic interval-valued q-rung orthopair fuzzy sets;
multiple attribute group decision making;
aggregation operators;
VIKOR model;
linguistic variable;
BONFERRONI MEAN OPERATORS;
AGGREGATION OPERATORS;
EXPONENTIAL OPERATIONS;
SETS;
CONSENSUS;
NUMBERS;
TOPSIS;
D O I:
10.3233/JIFS-210940
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
As a generalization of linguistic q-rung orthopair fuzzy set (Lq-ROFS), linguistic interval valued q-Rung orthopair fuzzy set (LIVq-ROFS) is a new concept to deal with complex and uncertain decision making problems which Lq-ROFS cannot handle. Due to the lack of information in decision making process, decision makers mostly prefer to give their preferences in interval form rather than a crisp number. In this situations, LIVq-ROFS appears up as a useful tool. In this work, we define operational laws of LIVq-ROFS and prove some properties. Furthermore, we propose the conception of the LIVq-ROF weighted averaging operator and give its formula by mathematical induction. To compare two or more linguistic interval valued q-Rung orthopair fuzzy numbers (LIVq-ROFNs), the improved form of score function is also given. Considering the powerfulness of LIVq-ROFSs handling ambiguity and complex uncertainty in practical problems, the key innovation of this paper is to develop the linguistic interval-valued q-rung orthopair fuzzy VIKOR model that is significantly different from the existing VIKOR methodology. The computing steps of this newly created model are briefly presented. Finally, the effectiveness of model is verified by an example and through comparative analysis, the superiority of VIKOR method is further illustrated.