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Abstract

The efficient integrated scheduling of different handling equipment at an automated container terminal (ACT) is crucial for reducing waiting times, lowering energy consumption, and improving operational efficiency. This study focuses on the integrated scheduling problem of double cantilever rail-mounted gantry cranes (DCRCs) and intelligent guided vehicles (IGVs) under a U-shaped layout. Taking into account constraints such as landside collection–distribution operations and operational interference between the dual DCRCs, an adaptive yard partitioning strategy is proposed to separate the operations of the dual DCRCs, thereby mitigating operational interference, balancing their workload, and ultimately enhancing terminal operation efficiency. A mathematical model is established to optimize the dual objectives—minimizing the maximum completion time and total energy consumption, and an improved adaptive nondominated sorting genetic algorithm with chaotic sequences is introduced for solving the model. The results indicate that the integrated scheduling scheme of DCRCs and IGVs using the adaptive partitioning strategy in the yard outperforms the scheduling results using a fixed partitioning strategy considering both the maximum completion time and total energy consumption. Finally, the advantages and disadvantages of the integrated scheduling under the typical ACT layout, U-shaped layout, and double-buffer layout are compared and analyzed through experiments. These research findings not only optimize the operations of existing automated terminals but can also be applied to automation upgrade projects at various ports.

Keywords

marine ports and channels logistics optimization

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Integrated Sustainable Scheduling in U-Shaped Automated Container Terminal Considering Collection–Distribution Operations and Adaptive Partitioning Strategies

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