Decision-making algorithm based on the scored-energy of neutrosophic soft sets

Abstract

Neutrosophic soft sets are a potent tool for data modeling and have therefore been the focus of extensive research, both in practical applications and from a theoretical mathematical perspective. This study aims to determine a numerical characteristic of neutrosophic soft sets that parallels the concept of energy found in graph theory and fuzzy soft set theory. This study aims to develop a decision-making algorithm that surpasses the efficiency of existing algorithms. The energy of graphs and fuzzy soft sets is determined using the singular values of a matrix, with the sum of these values representing a norm function, known as the nuclear norm in optimization problems. This concept inspires the introduction of neutrosophic soft set energy and an exploration of its potential applications. The created algorithm has been compared with a large number of existing algorithms, and in all these comparisons, the advantages of the energy-based algorithm have been highlighted.