Abstract: Previous multi-agent deep reinforcement learning (MADRL) algorithms have shown strong performance in symmetric scenarios. However, research on numerically disadvantaged scenarios is limited ...
Abstract: The present study developed an adaptive staff scheduling framework integrating demand time series prediction and operational optimization in sorting centers. A hybrid SARIMA (Seasonal ...
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