Intuitionistic Fuzzy Power Geometric Bonferroni Means and Their Application to Multiple Attribute Group Decision Making

被引:36
作者
He, Yingdong [1 ]
He, Zhen [1 ]
Jin, Chao [1 ]
Chen, Huayou [2 ]
机构
[1] Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China
[2] Anhui Univ, Sch Math Sci, Hefei 230601, Anhui, Peoples R China
基金
中国国家自然科学基金;
关键词
Geometric Bonferroni mean; power geometric average operator; intuitionistic fuzzy power geometric Bonferroni mean; multiple attribute group decision making; VAGUE SET-THEORY; AGGREGATION OPERATORS; PREFERENCE RELATIONS; AVERAGING OPERATORS; OPERATIONS; MODELS;
D O I
10.1142/S0218488515500129
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The geometric Bonferroni mean (GBM) can capture the interrelationships between input arguments, which is an important generalization of Bonferroni mean (BM). In this paper, we combine geometric Bonferroni mean (GBM) with the power geometric average (PGA) operator under intuitionistic fuzzy environment and present the intuitionistic fuzzy geometric power Bonferroni mean (IFPGBM) and the weighted intuitionistic fuzzy power geometric Bonferroni mean (WIFPGBM). The desirable properties of these new extensions of Bonferroni mean and their special cases are investigated. We list the detailed steps of multiple attribute group decision making with the developed IFPGBM or WIFPGBM, and give a comparison of the new extensions of Bonferroni mean by this paper with the corresponding existing intuitionistic fuzzy Bonferroni means. Finally, examples are illustrated to show the validity and feasibility of the new approaches.
引用
收藏
页码:285 / 315
页数:31
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