Application of interval-valued T-spherical fuzzy Dombi Hamy mean operators in the antiviral mask selection against COVID-19

Abstract

This study introduces Interval-valued T-Spherical Fuzzy Dombi Hamy Mean (IVT-SPFDHM) Operators as a powerful tool for group decision-making. The IVT-SPFDHM operators allow for prioritization of fuzzy data, effectively managing uncertainty. Its framework is applied in diverse group decision-making contexts, presenting its adaptability and robustness in addressing complex real-world problems. This study examines the Multi-Attribute Decision-Making (MADM) issue in the IVT-SPFDHM environment where the qualifications and expertise are at varying levels of necessity. We regard the novel Aczel-Alsina aggregation operators (AOs) as the most recently created AOs, capable of handling considerable uncertainty. To propose some AOs, we investigated the Hamy mean (HM) operator in the following environment: Interval-valued T-Spherical Fuzzy weighted Dombi Hamy mean (IVT-SPWDHM) operator, stretch esteemed interval valued T-Spherical Dual Dombi Hamy Mean (IVT-SPFDDHM), and Interval-valued T-Spherical Fuzzy weighted Dual Dombi Hamy Mean (IVT-SPFWDDHM). The weights for prioritization are derived from the knowledge of experts, and the proposed operators can capture the phenomenon of prioritization among the aggregated arguments. The MADM models are then planned using the IVPWDHM and IVPWDDHM operators. Finally, we provided a sample example within the prioritized ones to select the best antiviral mask for fighting COVID.