An approach to neutrosophic graph theory with applications

Graph theory that can be used to describe the relationships among several individuals has numerous applications in diverse fields such as modern sciences and technology, database theory, data mining, neural networks, expert systems, cluster analysis, control theory, and image capturing. As a generalization of fuzzy set (FS) and intuitionistic fuzzy set (IFS), the concept of neutrosophic set is a more functional tool for handling indeterminate, inconsistent and uncertain information that exist in real life compared to FSs and IFSs. In this paper, we apply the graph theory to the single-valued neutrosophic sets and investigate a new kind of graph structure which is called single-valued neutrosophic graphs and is generalized the results concerning crisp graphs, fuzzy graphs and intuitionistic fuzzy graphs. Then we describe some of their theoretical properties, such as the Cartesian product, composition, union and join. By applying two different procedures to solve single-valued neutrosophic decision-making problems, a neutrosophic graph-based multicriteria decision-making model is developed to consider relationships among the multi-input arguments which cannot be handled well by means of the existing methods. Finally, two illustrative examples are given to demonstrate the applicability, feasibility, effectiveness and advantages of these two proposed approaches.