Decision Support System Based on CoCoSo Method with the Picture Fuzzy Information

Abstract

Coronavirus disease 2019 (COVID-19) is currently threatening the entire world, and a novel coronavirus is a virus from the corona family that has spread a new infection. The number of instances of this disease is increasing at an exponential, but there are now commercially accessible COVID-19 vaccines. The weak symptoms of COVID-19 disease, on the other hand, are treated with a variety of antiviral treatments. It is still choosing the optimal antiviral medicine to manage COVID-19s. It is a challenging and difficult alternative to reduce the risk of infection. In this study, an improved combined compromise solution (CoCoSo) method is proposed to identify the ranking of alternatives. The introduction of a logarithmic picture fuzzy set is a more effective technique for representing variance, represented by three memberships (positive, neutral, and negative membership) degrees. This work introduces a fresh logarithmic picture fuzzy score function, to deal with the problem of comparison. The CoCoSo method-based logarithmic picture fuzzy decision-making algorithm is given. To achieve so, a new divergence measure for the logarithmic picture fuzzy number is introduced. To demonstrate the viability and efficacy of the established approach in real-world applications, a case study of COVID-19 disease drug selection is discussed.