AINeutralarXiv – CS AI · 15h ago6/10
🧠
An End-to-End Learning Approach for Solving Capacitated Location-Routing Problems
Researchers propose DRLHQ, a deep reinforcement learning approach with heterogeneous query attention mechanisms to solve capacitated location-routing problems (CLRPs) and their open variants. This marks the first end-to-end learning framework for CLRPs, demonstrating superior performance over traditional and DRL-based baselines on benchmark datasets.