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THE QUAY CRANE DEPLOYMENT PROBLEM AT A MARITIME CONTAINER TERMINAL

机译:Quay Crane部署问题在海上集装箱码头

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Container unloading/loading at marine container terminals (MCTs) is a key logistic process, to which some research efforts have been addressed by using mathematical programming models formulated in a deterministic-static environment. Vice versa, DES models in a stochastic-dynamic environment are well capable of representing the entire process. Hence, simulation results to be an effective planning and control tool for decision making at all decisional levels. Here we remark that optimal decisions in MCTs may be practically pursued by modelling the whole MCT and focusing attention on the core logistic processes, while representing in a simplified manner the remainder. We focus on the operational management of the cranes deployed along the quay, during the container unloading/loading process at a given number of vessels according to a previously planned berth-schedule. We suggest a two-phase approach to the quay crane deployment problem: in the first phase an IP model is used to decide when and how many cranes must be assigned to each vessel; afterwards, we propose a heuristics to determine which specific crane should be assigned to a vessel. We indicate how this approach can be successfully integrated in a DES model, already available, to support dynamic assignment of cranes to berthed vessels.
机译:集装箱卸载/装载在海上集装箱码头(MCTS)是一个关键的物流过程,对其中的一些研究成果已得到解决通过使用一个确定性的静态环境制定的数学规划模型。反之亦然,在一个随机动态环境DES模型是公能够表示的全过程。因此,仿真结果成为决策的所有决策层次进行有效的计划和控制的工具。在这里,我们此话中的MCT是最优决策可以通过模拟整个MCT并把注意力集中在核心的物流过程被实际推行,而在一个简化的方式代表的其余部分。我们专注于根据先前计划泊位时间表在血管的给定数内的容器卸载/装载过程沿码头展开时,起重机的操作管理。我们提出一个两阶段的方法来码头起重机部署问题:在第一阶段的IP模型来决定时必须有多少起重机分配给每个容器;之后,我们提出了一个启发式,以确定哪些特定的起重机应被分配到一个容器。我们表明这种方法如何可以成功地集成在DES模式,已经上市,以支持对停泊船只起重机的动态分配。

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