Multi-Attribute Decision-Making Approach Based on Dual Hesitant Fuzzy Information Measures and Their Applications

被引:13
|
作者
Chen, Huiping [1 ,2 ]
Xu, Guigiong [1 ]
Yang, Pingle [1 ,3 ]
机构
[1] Shanghai Univ, Sch Management, Shanghai 200444, Peoples R China
[2] Nantong Univ, Dept Social Resources, Nantong 226019, Peoples R China
[3] Jiangsu Univ Sci & Technol, Sch Elect & Informat Engn, Zhangjiagang 215600, Peoples R China
基金
中国国家自然科学基金; 上海市科技启明星计划;
关键词
dual hesitant fuzzy set; distance measure; entropy; multi-attribute decision-making; CORRELATION-COEFFICIENT; AGGREGATION OPERATORS; SIMILARITY MEASURES; SETS; ENTROPY; DISTANCE;
D O I
10.3390/math7090786
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Combining the ideas and advantages of intuitionistic fuzzy set (IFS) and hesitant fuzzy set (HFS), dual hesitant fuzzy set (DHFS) could express uncertain and complex information given by decision makers (DMs) in a more flexible manner. By virtue of the existing measure methods, elements in DHFSs should be of equal length and thus some values must be added into the shorter elements according to the risk preference of DMs. The extension of values will increase the subjectivity of decision-making to some extent, and different extension methods may produce different results. In order to address this issue, we first propose several new forms of distance and similarity measures without adding values. Subsequently, according to the proposed distance and similarity measures, two entropy measures are presented from the viewpoints of complementary set and the fuzziest set, respectively. Furthermore, based on the new distance and entropy measures, an extended technique for order preference by similarity to an ideal solution (TOPSIS) method is proposed for dealing with multi-attribute decision-making problems in the context of DHFS. Finally, two practical examples are analyzed to show the validity and applicability of the proposed method.
引用
收藏
页数:18
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