Routing Problem

Routing problems, encompassing the efficient allocation of resources across networks or the optimization of paths, aim to minimize costs (e.g., distance, time, or monetary expense) while satisfying constraints. Current research emphasizes the development and improvement of neural network-based approaches, including reinforcement learning, mixture-of-experts models, and graph neural networks, to address the challenges of scalability, robustness, and generalization across diverse problem types. These advancements hold significant potential for optimizing various real-world applications, such as logistics, telecommunications, and large language model deployment, by enabling faster and more efficient solutions to complex routing scenarios.