2026
RADAR: Learning to Route with Asymmetry-aware Distance Representations
ICLR 2026poster
Recent neural solvers have achieved strong performance on vehicle routing problems (VRPs), yet they mainly assume symmetric Euclidean distances, restricting applicability to real-world scenarios. A core challenge is encoding the relational features in asymmetric distance matrices of VRPs. Early atte…