arXiv Machine Learning By Haomiao Sun, Fang He, Congyuan Ji, Xindi Tang

Learning to Optimize: Joint Routing and Flow Allocation on Sparse Non-Euclidean Networks

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arXiv:2607. 23467v1 Announce Type: new Abstract: We study an integrated pickup-and-delivery problem on sparse, non-Euclidean networks that jointly optimizes cyclic routing, cargo flow allocation, and cross-cycle service.

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arXiv Machine Learning
Sep 4

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

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.

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