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The inbound container space allocation in the automated container terminals

机译:自动集装箱终端中的入站集装箱空间分配

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In this paper, we study an inbound container space allocation problem in the automated container terminals using simulation-embedded optimization. We aim to allocate the container terminal yard space for a batch of arrived inbound containers so as to minimize the total AGV (Automated Guided Vehicle) waiting time in the space allocation process and the external truck waiting time in the future container retrieval process. We propose an integer programming model to characterize the problem and prove the NP-hardness of the problem. A simulation module is employed to estimate the container rehandle number happened in the retrieval process. A simulation-embedded genetic algorithm is developed to solve the problem. Numerical experiment results show that (1) The proposed algorithm can significantly affect the performance of the allocation decision and achieve a trade-off between fast computation and good solution quality. (2) The space allocation schemes of the inbound containers are affected by different factors, such as initial block layout, quantity of arriving containers, and containers' arriving information. (3) The automated container terminal operators who care about the external truck waiting time may consider the simulation-embedded approach when the block yard is congested.
机译:在本文中,我们使用模拟嵌入式优化研究自动集装箱终端中的入站容器空间分配问题。我们的目标是为一批到达的入站容器分配集装箱终端码空间,以便在未来的集装箱检索过程中最小化空间分配过程中的总AGV(自动导向车辆)等待时间和外部卡车等待时间。我们提出了一个整数编程模型来表征问题并证明问题的NP硬度。使用模拟模块来估计在检索过程中发生的容器重建。开发了一种模拟嵌入的遗传算法来解决问题。数值实验结果表明,(1)所提出的算法可以显着影响分配决策的性能,实现快速计算与良好解决方案质量之间的权衡。 (2)入站容器的空间分配方案受不同因素的影响,例如初始块布局,到达容器的数量和容器到达信息。 (3)当块围场拥挤时,关心外部卡车等待时间的自动集装箱终端操作员可以考虑模拟嵌入的方法。

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