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A Clonal Selection Algorithm for the container stacking problem

机译:集装箱堆垛问题的克隆选择算法

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Due to increasing demand, container terminals face the challenges of increasing its service capacity and minimize the time of ships loading and unloading. The assignment of storage locations for reshuffled containers is a problem to the efficiency of container terminals operations, as a wrong assignment may result in several future reshuffles. This paper proposes a meta-heuristic based on the Clonal Selection Algorithm to minimize reshuffle when retrieving containers from a stack. The model competitiveness in accuracy and time are established by extensive numerical experiments comparing with an existing Integer Program model. The preliminary results obtained here suggest the proposed model is a promising optimization tool for the container stacking problem.
机译:由于需求的增长,集装箱码头面临着增加其服务能力并最小化船舶装卸时间的挑战。改组后的集装箱的存放地点的分配是集装箱码头运营效率的问题,因为错误的分配可能会导致未来的几次改组。本文提出了一种基于克隆选择算法的元启发式算法,以最大程度地减少从堆栈中检索容器时的重排。通过与现有Integer程序模型进行比较的大量数值实验,建立了模型在准确性和时间上的竞争力。在此获得的初步结果表明,所提出的模型是解决集装箱堆叠问题的有前途的优化工具。

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