Distance and similarity measures of dual hesitant fuzzy sets with their applications to multiple attribute decision making

The Dual Hesitant Fuzzy Sets (DHFSs) is a useful tool to deal with vagueness and ambiguity in the multiple attribute decision making (MADM) problems. The distance and similarity measures analysis are important research topics. In this paper, we propose a variety of distance measures for dual hesitan...

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Bibliographic Details
Published in2014 IEEE International Conference on Progress in Informatics and Computing pp. 88 - 92
Main Authors Lei Wang, Shiming Xu, Qiming Wang, Mingfang Ni
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2014
Subjects
Decision making
distance measures
dual hesitant fuzzy set
Educational institutions
Fuzzy sets
Hamming distance
Programmable logic arrays
similarity measures
TOPSIS
Weight measurement
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Summary:The Dual Hesitant Fuzzy Sets (DHFSs) is a useful tool to deal with vagueness and ambiguity in the multiple attribute decision making (MADM) problems. The distance and similarity measures analysis are important research topics. In this paper, we propose a variety of distance measures for dual hesitant fuzzy sets, based on which the corresponding similarity measures can be obtained. We investigate the connections of the aforementioned distance measures and further develop a number of dual hesitant ordered weighted distance measures. Finally, we present a TOPSIS approach based on proposed distance measures for the weapon selection problem.
ISBN:9781479920334
1479920339
DOI:10.1109/PIC.2014.6972302