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arXiv AI By Yuheng Li, Di Yang, Haipeng Chen, Yanhai Xiong

HyCO: A Hybrid Neural Solver for Combinatorial Optimization

Read the original on arXiv AI →

HyCO is a hybrid neural solver that combines a sequential reinforcement learning (RL) solver with a global diffusion model (DM) to tackle combinatorial optimization problems. The RL component builds an initial solution prefix, after which HyCO switches to a conditional DM to finish the remaining decisions. The authors provide a theoretical framework showing that this hybrid approach yields lower expected regret than either method alone, identify an optimal trigger step for the switch, and implement a lightweight adaptive trigger based on policy entropy and RL‑DM disagreement, achieving consistent performance gains across benchmarks.

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 AI.

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