scholarly journals Comments on “Interval Type-2 Fuzzy Sets are Generalization of Interval-Valued Fuzzy Sets: Towards a Wide View on Their Relationship”

2016 ◽  
Vol 24 (1) ◽  
pp. 249-250 ◽  
Author(s):  
Jerry M. Mendel ◽  
Hani Hagras ◽  
Humberto Bustince ◽  
Francisco Herrera
Keyword(s):  
Fuzzy Sets ◽  
Interval Type ◽  
Interval Valued

scholarly journals Interval Type-2 Fuzzy Sets are Generalization of Interval-Valued Fuzzy Sets: Toward a Wider View on Their Relationship

2015 ◽  
Vol 23 (5) ◽  
pp. 1876-1882 ◽  
Author(s):  
Humberto Bustince Sola ◽  
Javier Fernandez ◽  
Hani Hagras ◽  
Francisco Herrera ◽  
Miguel Pagola ◽  
...  
Keyword(s):  
Fuzzy Sets ◽  
Interval Type ◽  
Interval Valued

An interval type-2 hesitant fuzzy best-worst method

2021 ◽  
pp. 1-28
Author(s):  
Ashraf Norouzi ◽  
Hossein Razavi hajiagha
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Uncertain Data ◽  
Interval Type ◽  
Best Worst Method

Multi criteria decision-making problems are usually encounter implicit, vague and uncertain data. Interval type-2 fuzzy sets (IT2FS) are widely used to develop various MCDM techniques especially for cases with uncertain linguistic approximation. However, there are few researches that extend IT2FS-based MCDM techniques into qualitative and group decision-making environment. The present study aims to adopt a combination of hesitant and interval type-2 fuzzy sets to develop an extension of Best-Worst method (BWM). The proposed approach provides a flexible and convenient way to depict the experts’ hesitant opinions especially in group decision-making context through a straightforward procedure. The proposed approach is called IT2HF-BWM. Some numerical case studies from literature have been used to provide illustrations about the feasibility and effectiveness of our proposed approach. Besides, a comparative analysis with an interval type-2 fuzzy AHP is carried out to evaluate the results of our proposed approach. In each case, the consistency ratio was calculated to determine the reliability of results. The findings imply that the proposed approach not only provides acceptable results but also outperforms the traditional BWM and its type-1 fuzzy extension.

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