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A Hybrid Metaheuristic Algorithm for the Integrated Vehicle Routing and Three-Dimensional Container-Loading Problem

机译:集成车辆路径与三维集装箱装载问题的混合元启发式算法

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This paper examines a recently addressed practical variant of the capacitated vehicle routing problem (VRP) called the Capacitated Vehicle Routing Problem with 3-D Loading Constraints (3L-CVRP). This problem considers customer demand to be formed by 3-D rectangular items. Additional loading constraints often encountered in real-life applications of transportation logistics are imposed on the examined problem model. In addition to 3L-CVRP, we also introduce and solve a new practical problem version that was dictated by a transportation logistics company and covers cases in which transported items are manually unloaded from the loading spaces of the vehicles. Both problem versions are solved by a hybrid metaheuristic methodology that combines the strategies of tabu search (TS) and guided local search (GLS). The loading characteristics are tackled by employing a collection of packing heuristics. The proposed algorithm's robustness was tested for both problem versions, solving benchmark instances derived from the literature and new benchmark problems with diverse features in terms of customer set size and transported-item dimensions. It produced fine results, improving most of the best solutions that were previously reported.
机译:本文研究了最近解决的容量化车辆路线问题(VRP)的一种实用变体,称为“具有3-D加载约束的容量化车辆路线问题”(3L-CVRP)。此问题认为客户需求由3-D矩形项目形成。在运输物流的实际应用中经常遇到的其他装载约束条件被强加到检查的问题模型上。除了3L-CVRP,我们还介绍并解决由运输物流公司规定的新的实际问题版本,并涵盖了从车辆的装卸空间手动卸下运输物品的情况。通过混合元启发式方法解决了两个问题版本,该方法结合了禁忌搜索(TS)和指导性局部搜索(GLS)的策略。通过采用打包启发法来解决加载特性。针对这两个问题版本测试了所提出算法的鲁棒性,解决了来自文献的基准实例和具有新特征的新基准问题,这些新基准问题具有客户集大小和运输项目尺寸方面的特征。它产生了出色的结果,改进了先前报告的大多数最佳解决方案。

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