AI RESEARCH
Towards Generalization-Oriented Models for Vehicle Routing Problems with Mixture-of-Experts
arXiv CS.AI
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ArXi:2605.26776v1 Announce Type: cross In recent years, Deep Reinforcement Learning (DRL) has achieved substantial progress on Vehicle Routing Problems (VRPs). However, existing DRL-based methods are typically trained on instances generated from a uniform distribution, which limits their performance under real-world distribution shifts. In this paper, we aim to develop a generalization-oriented model that partitions the policy network into multiple modules and adaptively recombines modules to form specific policies during inference.