Informatica

Shadowed set (SHS) theory was introduced by Witold Pedrycz in 1998 to play a vital role in handling vagueness and providing a way to approximate a given fuzzy set (FS) by a construct, which is easy to deal with in practice. Nonetheless, the application of SHSs and shadowed numbers (SHNs) is surprisingly underrepresented in fuzzy multi-attribute decision-making (FMADM) literature. To address this gap, the current research aims to introduce and demonstrate a new FMADM method called the SHAdowed $\boldsymbol{N}\boldsymbol{U}$mber based $\boldsymbol{R}\mathit{anking}\hspace{2.5pt}\mathit{and}\boldsymbol{S}\mathit{election}\hspace{2.5pt}\boldsymbol{A}\mathit{pproach}$ (SHANURSA). The methodology involves, inter alia, transforming FNs into their corresponding SHNs using Grzegorzewski’s (2013) approach, then implementing an efficient weighted Minkowski Distance Metric (MDM) for SHNs to better gauge the proximity/remoteness between them. Additionally, a new and unusual closeness coefficient is introduced and defined to enhance the ranking accuracy of alternatives. Finally, the applicability and effectiveness of this closeness coefficient and proximity-based FMADM method is demonstrated by means of three distinct case studies from literature. The findings of this research show that the suggested method is trustworthy.