Solving Neutrosophic Fuzzy Transportation Problem Of Type-II

Abstract

Transportation problems offer a structured approach to optimize the allocation of resources, minimize transportation costs, and improve overall efficiency in supply chain and logistics management, leading to several advantages for businesses and organizations. Fuzzy transportation problems are particularly relevant in supply chain and logistics management when dealing with uncertain demand, fluctuating costs, or imprecise data and the intuitionistic fuzzy transportation problem is a more advanced modeling technique that takes into account the nuanced handling of uncertainty and imprecision using intuitionistic fuzzy sets(IFS). It provides a
more realistic approach to decision-making in situations where classical or fuzzy models may not capture the subtleties of uncertainty in data. In this article, we demonstrate a novel approach to resolving transportation problems in a neutrosophic atmosphere. Neutrosophic set is an extension of fuzzy and IFS and it is classified by three independent membership grades: truth, indeterminacy, and falsity membership grade. These sets are better suited to handle imprecise parameters. Transportation cost and demand are taken as neutrosophic numbers. Vogel’s approximation method is used to get the optimum solution of this neutrosophic transportation problem. Also, we performed a numerical instance to figure out the successful outcome of our suggested technique.