RT Journal Article ID 0611c1bf5a829166 A1 Garg, Harish A1 Arora, Rishu T1 DISTANCE AND SIMILARITY MEASURES FOR DUAL HESITANT FUZZY SOFT SETS AND THEIR APPLICATIONS IN MULTICRITERIA DECISION MAKING PROBLEM JF International Journal for Uncertainty Quantification JO IJUQ YR 2017 FD 2017-08-01 VO 7 IS 3 SP 229 OP 248 K1 dual hesitant fuzzy soft set K1 decision-making K1 distance measure K1 pattern recognition AB The dual hesitant fuzzy set is one of the successful extensions of the fuzzy set in which elements are represented in terms of a set of possible values instead of a single number. However, their theory is restricted to their parameterized tool and hence it cannot be effectively applied to a real-life problem. In order to handle it, dual hesitant fuzzy soft set theory has been utilized in this manuscript and hence, based on it, some axioms of distance and similarity measures based on Hamming, Euclidean, and Hausdorff metrics have been proposed here. Various desirable relations between them have also been presented. The proposed distance measures are applied to the field of decision-making under dual hesitant fuzzy soft set environment. Finally, practical examples of pattern recognition and medical diagnoses are given to demonstrate the effectiveness of the proposed measures. A comparative study as well as advantages of the proposed distance measures over existing measures have been presented. PB Begell House LK https://www.dl.begellhouse.com/journals/52034eb04b657aea,0a2633174192d2ab,0611c1bf5a829166.html