A deep reinforcement learning based multi-agent simulation optimization approach for IGV bidirectional task allocation and charging joint scheduling in automated container terminals

Real-time AGV scheduling optimisation method with deep reinforcement learning for energy-efficiency in the container terminal yard

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Optimization for integrated scheduling of intelligent handling equipment with bidirectional flows and limited buffers at automated container terminals

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Integrated scheduling of automated yard cranes and automated guided vehicles with limited buffer capacity of dual-trolley quay cranes in automated container terminals

Naeem, Doaa, (2022)