Analyzing Decision‐Making Processes Using the Energy of Bipolar Neutrosophic Soft Sets

Abstract

Bipolar neutrosophic soft sets are powerful tools for modeling data under conditions of uncertainty and imprecision due to theirrich parametric structure and the useful mathematical properties of the operations defned on them. In this paper, motivated bythe limitations of existing decision-making algorithms, we introduce a new numerical characteristic, the energy of a bipolarneutrosophic soft set defned using singular values, analogous to the graph energy and nuclear norm. Our goal is to develop anefcient decision-making algorithm that successfully identifes the optimal alternative even in cases where other algorithmsprovide inaccurate or inconsistent results. Our research is motivated by the need for more reliable decision-making methods incomplex soft environments and the potential of the energy-based approach to overcome the weaknesses of existing methods,which we demonstrate through a comparative analysis using concrete examples.