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A hybrid genetic-heuristic algorithm for scheduling of automated guided vehicles and quay cranes in automated container terminals

机译:一种混合遗传 - 启发式算法,用于自动集装箱终端中自动导向车辆和码头起重机的调度

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Containers have been used in past decades increasingly as one of the most important transportation tools. Containers have revolutionized cargo shipping and thus changed the world trade systematically. Container terminals as the transhipment facility play a valuable role in performance of this transportation system. Improvement of this facility has been widely considered in literatures. Automated container terminals (ACTs) have been introduced to pursue this purpose. In ACTs various transport vehicles are automated and integrated to each other. Automated guided vehicles (AGVs) are used in ACTs to handle containers between quay cranes and storage yards. Usually scheduling of the AGVs is known as the key factor to improve the performance of ACTs. This paper proposed a heuristic algorithm to schedule the AGVs concurrently with quay cranes. A genetic algorithm is proposed to optimize the simultaneous scheduling of AGVs and QCs. The results showed that proposed genetic algorithm can be used in practical implications while its running time is reasonably low.
机译:在过去的几十年里,集装箱越来越多地作为最重要的运输工具之一。集装箱已经彻底改变了货物运输,从而系统地改变了世界贸易。随着转运设施的集装箱码头在这种运输系统的性能下起着宝贵的作用。在文献中已被广泛考虑该设施的改进。已经引入了自动集装箱码头(行为)以追求此目的。在行为中,各种运输车辆彼此自动化并整合。自动引导车辆(AGVS)用于处理码头起重机和储存码之间的容器。通常称为提高行为性能的关键因素。本文提出了一种启发式算法,可以与Quay起重机同时安排AGV。提出了一种遗传算法来优化AGV和QCS的同时调度。结果表明,在其运行时间合理低位的同时,可以在实际意义中使用提出的遗传算法。

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