Advances in Graph Theory and Its Applications

Abstract

                    Recent graph theory developments focus on handling very large, complex, and changing data using modern methods and machine learning. Today, graph theory is important in fields like Artificial Intelligence, Bioinformatics, and Cybersecurity, helping to study real-time and complex connections instead of only fixed networks.

                 Graph theory is a part of discrete mathematics that studies connections between objects using Points and links. In recent years, it has grown rapidly because of advances in computer science, data science, and network technologies. New areas like spectral graph theory, random graphs, efficient graph algorithms, and graph neural networks have increased both its theory and real-world use. This paper reviews these recent developments and shows how graph theory is applied in computer networks, social sciences, biology, artificial intelligence, and operations research.