Determining Electrical Vehicle Charging Stations using Dominance in Neutrosophic Fuzzy Directed Graphs
DOI:
https://doi.org/10.29020/nybg.ejpam.v18i1.5675Keywords:
Neutrosophic Logic, fermatean neutrosophic graph, fermatean neutrosophic digraphs, generalized fermatean neutrosophic digraphsAbstract
In this paper, we begin by describing several forms of effective arcs in neutrosophic fuzzy-directed graphs, based on the fundamental principles introduced in neutrosophic fuzzy-directed graphs. We then investigate several forms of dominance in neutrosophic fuzzy directed graphs, looking at their significance and uses in decision-making situations. Our study fills two
important gaps in the literature: it extends the concept of domination from fuzzy directed graphs to neutrosophic fuzzy directed graphs, and it provides a detailed characterization of dominations within this advanced framework. The concept of dominations in fuzzy graphs, fuzzy directed graphs, intuitionistic fuzzy graphs, neutrosophic fuzzy graphs, and picture fuzzy graphs is well-
documented in the literature. First, we characterize several kinds of effective arcs that are particular to neutrosophic fuzzy directed graphs, such as semi-κ effective arc, semi-φ effective arc, and semi-π effective arc. Next, we provide the notions of dominations and domination numbers connected to these arcs in different types of fuzzy-directed graphs that are neutrosophic.
In particular, our analysis of minimum dominating sets provides valuable characterizations of dominations in these graphs. We also study the smallest dominating sets and dominance numbers for neutrosophic fuzzy dipaths and dicycles, and we provide some interesting results. Finally, we suggest an algorithm to handle decision-making problems, such figuring out the ideal places
to launch EV charging station in different metropolitan regions, by utilizing the ideas presented in this research. In regard to the development of electric mobility and environmentally friendly urban growth, this strategy offers a far superior technique of identifying EV charging stations.
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Copyright (c) 2025 Mohammed Aeyed M Alqahtani
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