Hesitant fuzzy prioritized operators and their application to multiple attribute decision making

被引：430
|
作者：
Wei, Guiwu [1 ]
机构：
[1] Chongqing Univ Arts & Sci, Dept Econ & Management, Chongqing 402160, Peoples R China
来源：
KNOWLEDGE-BASED SYSTEMS | 2012年 / 31卷
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Multiple attribute decision making (MADM); Hesitant fuzzy values; Prioritized aggregation operators; Hesitant fuzzy prioritized weighted average (HFPWA) operator; Hesitant fuzzy prioritized weighted geometric (HFPWG) operator; RELATIONAL ANALYSIS METHOD; PROGRAMMING METHODOLOGY; RANKING METHOD; AGGREGATION; INFORMATION; DISTANCE; MODELS; NUMBERS; MADM;
D O I：
10.1016/j.knosys.2012.03.011
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we investigate the hesitant fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Motivated by the ideal of prioritized aggregation operators ERR. Yager, Prioritized aggregation operators, International Journal of Approximate Reasoning 48 (2008) 263-274], we develop some prioritized aggregation operators for aggregating hesitant fuzzy information, and then apply them to develop some models for hesitant fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approaches and to demonstrate its practicality and effectiveness. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码：176 / 182
页数：7
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