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Hierarchical collaborative multi-agent reinforcement learning for hot-rolling production planning with order-splitting flexibility

In mass personalized hot rolling, intricate constraints cause load imbalances and low order fulfilment. While order splitting alleviates these bottlenecks, it increases changeover frequency and planning complexity. We propose a bi-level model: the upper level optimizes production cost and time, while the lower minimize...

Ruilin Pan, Xinyu Jin, Jianhua Cao et al. · 0 citations

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