Extension of Interval-Valued Fermatean Fuzzy TOPSIS for Evaluating and Benchmarking COVID-19 Vaccines

In order to help curb the spread of COVID-19 pandemic, this paper develops a multi-attribute decision-making framework for vaccine evaluation based on their major clinical characteristics and efficacy. Firstly, new multi-criteria Technique Order Preference by Similarity Ideal Solution (TOPSIS) modification has been constructed in an interval-valued Fermatean fuzzy (IVFF) environment, improving shortcomings traditional TOPSIS. Secondly, conceptual static dynamic vaccines built. The proposed methodology incorporates variety crisp MCDM methods. analysis results two practical examples shows that comparison is feasible effective, finally, some recommendations enhancement government anti-COVID-19 strategies are suggested.