A New Algorithm to Determine the Density of a Balanced Neutrosophic Graph and Its Application to Enhance Education Quality

Abstract

The education system of a country to its citizens determines its success. The primary goal of providing education is to mold a person's entire personality and shape his career. Everyone, regardless of caste, creed, religion, gender, or any other factor, must have access to their choice's high-quality and indiscriminate education. At present, poverty, gender discrimination, regional imbalance, family background, and other unknown factors contribute to education inequality. In particular, the regional imbalance concerning academic opportunities and infrastructure plays a vital role. When there is uncertainty, balanced fuzzy graphs can resolve it. Furthermore, if indeterminacy exists, it can be efficiently dealt with by employing balanced neutrosophic graphs. A new algorithm for determining the density of a neutrosophic graph and establishing equilibrium in a neutrosophic graph is proposed in this study. A balanced neutrosophic graph structure is also modelled to demonstrate the proposed algorithm in the field of education to provide quality education with the selected parameters.