Shortest Path

The shortest path problem focuses on finding the most efficient route between two points in a network, minimizing distance, time, or cost. Current research emphasizes efficient algorithms for various contexts, including those with obstacles (e.g., A*, Floyd's algorithm, adaptations for graphs of convex sets), multiple destinations, and uncertainty in edge weights or dynamic environments (e.g., reinforcement learning, neural networks). These advancements have significant implications for diverse fields, such as robotics, autonomous navigation (drones, vehicles), and network optimization, by enabling faster and more robust path planning in complex scenarios.