Modeling of Decision-Making Based on Hesitant Fuzzy Sets
DOI:
https://doi.org/10.61506/Abstract
The hesitant fuzzy set (HFS) is successfully used as a fuzzy set (FS) extension to demonstrate circumstances where it is permissible to determine a few potential membership de- grees (MDs) of a component in a set due to the uncertainty between distinct values. Aggregation operators (AOs) are widely applied to accumulate vague and uncertain information these days. The hesitant fuzzy weighted aggregation geometric (HFWAG) operator is created by the authors as a new AO for hesitant fuzzy (HF) data. Some of the most important qualities of the suggested operators are highlighted, as well as their extensive interrelationship. Then, using those operators, we develop a methodology for interpreting the HF multiple criteria decision making (MCDM) hurdles. The proposed concepts are demonstrated using a real-life example related to medical di- agnosis, with the results’ believability tested using test criteria and compared. Because the weights of criteria can affect the outcome of a choice, they have a substantial impact on judgments. The De Luca-Termini entropy metric is utilized to estimate the weights of criteria in the current work. Moreover, TOPSIS and VIKOR were also employed to compare the results of our method.
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