Graph Coloring Algorithm Based on Minimal Cost Graph Neural Network Introduction: The Graph Coloring Problem (GCP) is a foundational puzzle in computer science and mathematics. It’s simple to describe—assign colors to the nodes of a graph so that no two adjacent nodes share the same color, and use the fewest colors possible—but incredibly challenging to solve efficiently, especially for large and complex graphs. GCP has significant real-world applications: wireless spectrum allocation, exam and event scheduling, and register allocation in compilers, to name a few. Traditional algorithms like greedy methods, simulated annealing, or evolutionary strategies often struggle with scalability and optimality. Enter deep learning. Specifically, Graph Neural Networks (GNNs) —a breakthrough in h...