Different variants of pandemic and prevention strategies: A prioritizing framework in fuzzy environment

Abstract

In this trying time for the world battling different variants of the COVID'19 pandemic, different intervention strategies are being taken by government, to limit the spread of infection. Closing educational institutes, stay at home orders, campaigns for emphasis on vaccination, usage of medical mask and frequently sanitizing hands, etc. are the endeavors made by the authorities to decrease the number of cases in the country. In this regard, the contribution aims to help the decision-makers to identify a potential prevention strategy, based on public acceptance and intervention effectiveness. To achieve this objective, feasible judgments of professionals from three different sectors are brought together through meetings. Opinions, based on ten criteria, are recorded in linguistic form for prioritizing six alternatives. The linguistic terms are then evaluated and manipulated by entailing triangular fuzzy numbers and a group multi-criteria decision making (GMCDM) approach. After using the fuzzy analytical hierarchy process (F-AHP) for the complex decisions, the fuzzy VIšekriterijumsko KOmpromisno Rangiranje method (F-VIKOR) is utilized to attain the closest ideal stratagem. Consequently, through the ranking orders of defuzzified scores, intuitive preference of compromise solutions is suggested. The tactic gaining more priority with respect to the group utility to the majority and F-VIKOR index is complete lockdown for the short term. Furthermore, a comparison analysis is also added in the discussion to verify the attained prioritized outcomes. This comparative study is carried out through the technique for order of preference by similarity to ideal solution (TOPSIS), which evidently produces the same preference of alternatives. In addition, this strategy can be apparently discovered to be an effective strategy adopted by different countries in successfully decreasing the number of cases.

From Traditional to Electrified Urban Road Networks: The Integration of Fuzzy Analytic Hierarchy Process and GIS as a Tool to Define a Feasibility Index—An Italian Case Study

“…The last step is consistency validation, that ensures the coherence of the decisionmaking process [16,43], by calculating the Consistency Index (CI)-Equation (8). The matrix A is consistent if CI is equal to 0.…”

“…As regards the consistency verification, CI is equal to 0.093 (λ max = 8.65). Therefore, CR is computed and it is equal to 0.065 (considering RI is equal to 1.41 [43]). Thus, the judgement is consistent (CR < 0.1).…”

Developing Universally Applicable Service Quality Assessment Model Based on the Theory of Consumption Values, and Using Fuzzy Linguistic Preference Relations to Empirically Test Three Industries

“…The crisp analytical hierarchy process (AHP) cannot reflect the thinking style in capturing the expert's knowledge; the triangular fuzzy importance scale can cover the uncertainty of assigning crisp concepts in related decision-making topics [53]. Therefore, it is often used in MCDM studies, e.g., [54][55][56].…”