Ordered n-dimensional fuzzy graphs
n-Dimensional Fuzzy Graphs, Metrics on n-Dimensional Fuzzy Graphs, n-Dimensional Aggregation Functions, Admissible Orders, Ordered Semi-vector Spaces.
A fuzzy graph is a fuzzy relation between the elements of a set, they are ideal for modeling uncertain data about these sets. The fuzzy graphs appear frequently in the literature, among them, stands out the fuzzy graph of Rosenfeld, and its extensions,
such as: interval-valued fuzzy graphs, bi-polar fuzzy graphs and m-polar fuzzy graphs. The applications of these concepts are vast: cluster analysis, pattern classification, database theory, social science, neural networks, decision analysis, among others. As well
as fuzzy graphs, studies on admissible orders and their extensions are frequent. Originally, admissible orders were introduced in the context of interval-valued fuzzy sets by H. Bustince et al. and since then they have been widely used. Recently, this notion has been
studied in other types of fuzzy sets, such as interval-valued intuitionistic fuzzy sets, hesitant fuzzy sets, multidimensional fuzzy sets and n-dimensional fuzzy sets. In this context, this work proposes to extend the Rosenfeld fuzzy graph to ordered n-dimensional
fuzzy graphs, based on n-dimensional fuzzy sets, as well as equipping the admissible ordered n-dimensional fuzzy graphs with an admissible ordered semi-vector space. We present some methods to generate admissible orders in the ordered n-dimensional set and the concept of n-dimensional aggregation functions with respect to an admissible order. We extend the concept of ordered semi-vector space in a semi-field of non-negative real numbers to an arbitrary weak semi-field. Several properties of these concepts were
investigated, in addition to presenting some applications.