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A Hybrid Genetic Algorithm for Integrated Truck Scheduling and Product Routing on the Cross-Docking System with Multiple Receiving and Shipping Docks

机译:具有多个接收和运输船坞的交叉扩展系统中集成卡车调度和产品路由的混合遗传算法

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In this research, a truck scheduling problem for a cross-docking system with multiple receiving and shipping docks is studied. Until recently, single-dock cross-docking problems are studied mostly. This research is focused on the multiple-dock problems. The objective of the problem is to determine the best docking sequences of inbound and outbound trucks to the receiving and shipping docks, respectively, which minimize the maximal completion time. We propose a new hybrid genetic algorithm to solve this problem. This genetic algorithm improves the solution quality through the population scheme of the nested structure and the new product routing heuristic. To avoid unnecessary infeasible solutions, a linked-chromosome representation is used to link the inbound and outbound truck sequences, and locus-pairing crossovers and mutations for this representation are proposed. As a result of the evaluation of the benchmark problems, it shows that the proposed hybrid GA provides a superior solution compared to the existing heuristics.
机译:在本研究中,研究了具有多个接收和运输码头的交叉扩展系统的卡车调度问题。直到最近,大多数研究单码头交叉对接问题。该研究专注于多码头问题。问题的目的是分别确定入站和出站卡车的最佳对接序列,分别为接收和运输码头,最小化最大完井时间。我们提出了一种新的混合遗传算法来解决这个问题。这种遗传算法通过嵌套结构的人口方案和新产品路由启发式提高解决方案质量。为了避免不必要的不​​可行的解决方案,使用链接染色体表示来连接入站和出站卡车序列,并提出了该表示的基因座配对交叉和突变。由于基准问题的评估,它表明,与现有的启发式相比,所提出的混合动力GA提供了优异的解决方案。

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