Antivirus Mask Selection Under Spherical Fuzzy Information

Abstract

Many individuals are facing antivirus mask scarcity with the exponential spread of COVID-19. A functional antivirus mask needs to be selected and made usable for everyone. Selection mask problem contains qualitative criteria, therefore utilizing fuzzy logic for this problem is a useful approach. To optimize the efficiency of choosing antivirus masks, we propose using one of the new types of ordinary fuzzy sets, named Spherical fuzzy sets. For this purpose, we determine 4 different alternatives and 6 criteria. Then, we gather the data under spherical information and applied the Spherical fuzzy AHP method to the problem. Then, we propose an entropy based Spherical fuzzy AHP method. We compare the results of Spherical fuzzy AHP method, and an entropy based Spherical fuzzy AHP method. Moreover, we present a sensitivity analysis to explain how our model is influenced by changes in different weights of criteria. Finally, the best antivirus mask is determined for public use and we present the advantages of the proposed method in results section.