Interval valued hesitant fuzzy uncertain linguistic aggregation operators in multiple attribute decision making
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- 作者：Guiwu Wei
- 关键词：Multiple attribute decision making (MADM) ; Interval valued hesitant fuzzy uncertain linguistic values ; Interval valued hesitant fuzzy uncertain linguistic arithmetic aggregation operators ; Interval valued hesitant fuzzy uncertain linguistic geometric aggregation operators ; Prioritized aggregation ; Power aggregation
- 刊名：International Journal of Machine Learning and Cybernetics
- 出版年：2016
- 出版时间：December 2016
- 年：2016
- 卷：7
- 期：6
- 页码：1093-1114
- 全文大小：577 KB
- 刊物类别：Engineering
- 刊物主题：Artificial Intelligence and Robotics
Statistical Physics, Dynamical Systems and Complexity
Computational Intelligence
Control , Robotics, Mechatronics - 出版者：Springer Berlin / Heidelberg
- ISSN：1868-808X
- 卷排序：7
文摘
In this paper, we investigate the multiple attribute decision making problem based on the arithmetic and geometric aggregation operators with interval valued hesitant fuzzy uncertain linguistic information. Then, motivated by the ideal of traditional arithmetic and geometric operation, we shall develop some aggregation operators for aggregating interval valued hesitant fuzzy uncertain linguistic information: interval valued hesitant fuzzy uncertain linguistic arithmetic aggregation operators, interval valued hesitant fuzzy uncertain linguistic geometric aggregation operators, interval valued hesitant fuzzy uncertain linguistic correlated aggregation operators, induced interval valued hesitant fuzzy uncertain linguistic aggregation operators, induced interval valued hesitant fuzzy uncertain linguistic correlated aggregation operators, interval valued hesitant fuzzy uncertain linguistic prioritized aggregation operators, interval valued hesitant fuzzy uncertain linguistic power aggregation operators. The prominent characteristic of these proposed operators are studied. Then, we shall utilize these operators to develop some approaches to solve the interval valued hesitant fuzzy uncertain linguistic multiple attribute decision making problems. Finally, a practical example is given to verify the developed approach and to demonstrate its practicality and effectiveness.