Similarity Measures for Hesitant Fuzzy Sets and Their Extensions

2018 ◽  
pp. 59-67
Author(s):  
Bahram Farhadinia ◽  
Zeshui Xu
Keyword(s):  
Fuzzy Sets ◽  
Similarity Measures ◽  
Hesitant Fuzzy Sets

Some Novel Similarity Measures of Hesitant Fuzzy Sets And Their Applications To MADM

2019 ◽  
Vol 67 (9) ◽  
pp. 31-37
Author(s):  
Xiaoqiang Zhou ◽  
Chunyong Wang ◽  
Zichuang Huang ◽  
Yameng Deng
Keyword(s):  
Fuzzy Sets ◽  
Similarity Measures ◽  
Hesitant Fuzzy Sets

Distance and similarity measures for hesitant fuzzy sets

2011 ◽  
Vol 181 (11) ◽  
pp. 2128-2138 ◽  
Author(s):  
Zeshui Xu ◽  
Meimei Xia
Keyword(s):  
Fuzzy Sets ◽  
Similarity Measures ◽  
Hesitant Fuzzy Sets

Selection of an alternative based on interval-valued hesitant picture fuzzy sets

2021 ◽  
pp. 1-11
Author(s):  
Tabasam Rashid ◽  
M. Sarwar Sindhu
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Multiple Criteria Decision Making ◽  
Similarity Measures ◽  
Hesitant Fuzzy Sets ◽  
Ambiguous Information ◽  
Cosine Similarity Measures ◽  
Picture Fuzzy Sets ◽  
Interval Valued ◽  
Selection Of

Motivated by interval-valued hesitant fuzzy sets (IVHFSs) and picture fuzzy sets (PcFSs), a notion of interval-valued hesitant picture fuzzy sets (IVHPcFSs) is presented in this article. The concept of IVHPcFSs is put forward and some operational rules are developed to deal with it. The cosine similarity measures (SMs) are modified for IVHPcFSs to deal with interval-valued hesitant picture fuzzy (IVHPcF) data and the linear programming (LP) methodology is used to find out the criteria’s weights. A multiple criteria decision making (MCDM) approach is then developed to tackle the vague and ambiguous information involved in MCDM problems under the framework of IVHPcFSs. For the validation and strengthen of the proposed MCDM approach a practical example is put forward to select the educational expert at the end.

scholarly journals Multiple Criteria Decision-Making Based on Vector Similarity Measures under the Framework of Dual Hesitant Fuzzy Sets

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Juan Luis García Guirao ◽  
M. Sarwar Sindhu ◽  
Tabasam Rashid ◽  
Agha Kashif
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Multiple Criteria Decision Making ◽  
Similarity Measures ◽  
Smart Phone ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Hesitant Fuzzy Sets ◽  
Investment Companies ◽  
Selection Of

Similarity measures have a great importance in the decision-making process. In order to identify the similarity between the options, many experts have established several types of similarity measures on the basis of vectors and distances. The Cosine, Dice, and Jaccard are the vector similarity measures. The present work enclosed the modified Jaccard and Dice similarity measures. Founded on the Dice and Jaccard similarity measures, we offered a multiple criteria decision-making (MCDM) model under the dual hesitant fuzzy sets (DHFSs) situation, in which the appraised values of the alternatives with respect to criteria are articulated by dual hesitant fuzzy elements (DHFEs). Since the weights of the criteria have a much influence in making the decisions, therefore decision makers (DMs) allocate the weights to each criteria according to their knowledge. In the present work, we get rid of the doubt to allocate the weights to the criteria by taking an objective function under some constraints and then extended the linear programming (LP) technique to evaluate the weights of the criteria. The Dice and Jaccard weighted similarity measures are practiced amongst the ideal and each alternative to grade all the alternatives to get the best one. Eventually, two practical examples, about investment companies and selection of smart phone accessories are assumed to elaborate the efficiency of the proposed methodology.

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