New q-rung orthopair fuzzy partitioned Bonferroni mean operators and their application in multiple attribute decision making

被引：115
|
作者：
Yang, Wei [1 ]
Pang, Yongfeng [1 ]
机构：
[1] Xian Univ Architecture & Technol, Sch Sci, Dept Math, Yanta Rd, Xian 710055, Shaanxi, Peoples R China
来源：
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS | 2019年 / 34卷 / 03期
基金：
中国国家自然科学基金;
关键词：
aggregation operator; Bonferroni mean; multiple attribute decision making; q-rung orthopair fuzzy sets; AGGREGATION OPERATORS; NUMBERS;
D O I：
10.1002/int.22060
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The q-rung orthopair fuzzy sets are superior to intuitionistic fuzzy sets or Pythagorean fuzzy sets in expressing fuzzy and uncertain information. In this paper, some partitioned Bonferroni means (BMs) for q-rung orthopair fuzzy values have been developed. First, the q-rung orthopair fuzzy partitioned BM (q-ROFPBM) operator and the q-rung orthopair fuzzy partitioned geometric BM (q-ROFPGBM) operator are developed. Some desirable properties and some special cases of the new aggregation operators have been studied. The q-rung orthopair fuzzy weighted partitioned BM (q-ROFWPBM) operator and the q-rung orthopair fuzzy partitioned geometric weighted BM (q-ROFPGWBM) operator are also developed. Then, a new multiple-attribute decision-making method based on the q-ROFWPBM (q-ROFPGWBM) operator is proposed. Finally, a numerical example of investment company selection problem is given to illustrate feasibility and practical advantages of the new method.
引用
收藏
页码：439 / 476
页数：38
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