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arXiv Machine Learning By Zhenwei Wang, Tiehua Zhang, Jing Liu, Heng Yu, Kaizhu Huang, Ruibin Bai

Learning Constraints-Based Adaptive Hypergraph Neural Networks for Solving Vehicle Routing Problems

Read the original on arXiv Machine Learning →

The paper presents an end‑to‑end framework that uses constraint‑oriented hypergraphs and reinforcement learning to solve vehicle routing problems. It introduces a dynamic hyperedge reconstruction strategy for better hypergraph representation and a double‑pointer attention decoder for iterative solution generation. Experiments on benchmark datasets show that the method removes the need for complex heuristic operators while improving solution quality.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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