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Scheduling of lifting vehicles with time windows in an automated port container terminal

机译:在自动港口集装箱码头中安排带有时间窗的起重车辆调度

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A port container terminal is generally exploited with three types of equipments: Quay Cranes (QCs), vehicles and Yard Cranes (YCs). In this paper, we present a particular type of vehicles which is used at terminal of Normandy in Le Havre port in France. In this terminal, containers are transported from the marshalling yard to ship by the lifting vehicles (LV), capable of raising and of depositing a single container at various heights. This study discusses how to schedule LVs in loading or unloading operation by using information about pickup and delivery locations. Our goal is to organize the transfer of containers in order to minimize the total travel time of all LV, respecting the time window of every LV for a given number of containers. In order to solve this problem we propose a new modeling and a genetic algorithm adapted to the studied problem called “Genetic Algorithm for Loading or Unloading Operation GALUO”. We applied special types of crossover and mutation inspired from various data of our problem. GALUO is compared with a simulated annealing algorithm (SA) inspired from the same problem. Computational results on real instances show the good quality of the solutions obtained by the proposed method.
机译:通常使用三种类型的设备来开发港口集装箱码头:码头起重机(QC),车辆和堆场起重机(YC)。在本文中,我们介绍了一种特殊类型的车辆,该车辆在法国勒阿弗尔港口的诺曼底码头上使用。在该航站楼中,由起重车辆(LV)将集装箱从编组场运输到船上,该起重车辆可以在不同的高度抬起并放置单个集装箱。这项研究讨论了如何通过使用有关取件和交付位置的信息来安排装载或卸载操作中的LV。我们的目标是组织集装箱的运输,以最大程度减少所有LV的总行驶时间,同时尊重给定数量的集装箱每个LV的时间窗。为了解决该问题,我们提出了一种新的建模方法和一种遗传算法,该遗传算法适合于所研究的问题,称为“装载或卸载操作GALUO的遗传算法”。我们根据问题的各种数据应用了特殊类型的交叉和变异。将GALUO与受相同问题启发的模拟退火算法(SA)进行了比较。在实际实例上的计算结果表明,所提方法获得的解决方案具有良好的质量。

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