Objective Attributes Weights Determining Based on Shannon Information Entropy in Hesitant Fuzzy Multiple Attribute Decision Making
Author(s) -
Yingjun Zhang,
Yizhi Wang,
Jingping Wang
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/463930
Subject(s) - weighting , entropy (arrow of time) , data mining , topsis , fuzzy logic , mathematics , fuzzy set , group decision making , computer science , artificial intelligence , mathematical optimization , operations research , medicine , law , radiology , political science , physics , quantum mechanics
Hesitant fuzzy set has been an important tool in dealing with multiple attribute decision making (MADM) problems, especially for the decision making situation when only some values of membership are possible for an alternative on attributes. However, determining attributes weights in hesitant fuzzy MADM is still an open problem. In this paper, we propose an objective weighting approach based on Shannon information entropy, which expresses the relative intensities of attribute importance to signify the average intrinsic information transmitted to the decision maker. Furthermore, we construct a hesitant fuzzy MADM approach based on the TOPSIS method and a weighted correlation coefficient proposed in this paper. Finally, we utilize a supplier selection example to validate the objective attributes weights determining method and the proposed hesitant fuzzy MADM approach.
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