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Collaborative scheduling of dual-trolley quay cranes and AGVs via speed-control strategy
Collaborative scheduling of dual-trolley quay cranes and AGVs via speed-control strategy
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Collaborative scheduling of dual-trolley quay cranes and AGVs via speed-control strategy
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Collaborative scheduling of dual-trolley quay cranes and AGVs via speed-control strategy
Collaborative scheduling of dual-trolley quay cranes and AGVs via speed-control strategy

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Collaborative scheduling of dual-trolley quay cranes and AGVs via speed-control strategy
Collaborative scheduling of dual-trolley quay cranes and AGVs via speed-control strategy
Journal Article

Collaborative scheduling of dual-trolley quay cranes and AGVs via speed-control strategy

2025
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Overview
Conflicts may impede AGVs from reaching DQCs promptly during automated terminal operations. This challenge may lead to congestion on the transfer platform and diminish the operational efficiency of unmanned terminals. This research proposes a cooperative scheduling approach integrating a speed control strategy for DQCs and AGVs. Considering the capacity of transfer platforms, time windows for AGVs are established, and tasks are allocated accordingly. A speed control-based conflict resolution model is created with the dual objectives of minimizing energy consumption during travel and maximizing the fulfillment of time windows. The Dijkstra algorithm is employed to plan travel routes, anticipate potential conflicts during AGV operations, and assign priorities based on the satisfaction of task time windows. AGV speeds are dynamically adjusted to generate conflict-free scheduling plans that align with the operational times of the dual-trolley quay cranes. Experimental results demonstrate that the proposed speed-control strategy effectively resolves conflicts while consuming less energy than traditional stop-and-wait methods. Additionally, this strategy reduces the frequency of AGV starts and stops, ensures timely task completion, decreases quay crane waiting times, and enhances overall terminal operational efficiency.