Vaccine selection for COVID-19 by AHP and novel VIKOR hybrid approach with interval type-2 fuzzy sets

Decisions in the health industry have a significant impact on human lives. With the COVID-19 pandemic, a global war is being waged. Vaccination is a critical component in this fight. The governments are attempting to offer their citizens the best vaccine for the public based on limitations. However, due to the unique characterizations of countries and the people who live in the country, the definition of “the ideal vaccination” is indefinite. Fuzzy set theory has been an ideal tool to cope with problems involving imprecise information such as the meaning of “ideal” in this case. In this study Interval Type-2 Fuzzy Sets (IT2FSs) will be used to describe uncertainty. This IT2FS structure will be the framework of the AHP (Analytic Hierarchy Process), to determine the criteria weights, and the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje), to generate a set of optimal choices. The main objective of this study is to sustain the necessary effect of uncertainty of fuzzy sets via the Interval Type-2 Fuzzy (IT2F) metric to the VIKOR method and thus propose an extended VIKOR. The presented new approach will be applied to the problem of vaccine selection for COVID-19. Hence, for the first time in the literature, an application with a multilevel hierarchy will be used in IT2FAHP-VIKOR. Also, obtained optimal solution set with this hybrid framework will be compared with fuzzy AHP-VIKOR and the rankings evaluated with the IT2FTOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and sensitivity analysis will be performed.