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Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet

机译:用偏向随机化解决异构机群的二维装车路径问题

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This paper discusses the two-dimensional loading capacitated vehicle routing problem (2L-CVRP) with heterogeneous fleet (2L-HFVRP). The 2L-CVRP can be found in many real-life situations related to the transportation of voluminous items where two-dimensional packing restrictions have to be considered, e.g.: transportation of heavy machinery, forklifts, professional cleaning equipment, etc. Here, we also consider a heterogeneous fleet of vehicles, comprising units of different capacities, sizes and fixed/variable costs. Despite the fact that heterogeneous fleets are quite ubiquitous in real-life scenarios, there is a lack of publications in the literature discussing the 2L-HFVRP. In particular, to the best of our knowledge no previous work discusses the non-oriented 2L-HFVRP, in which items are allowed to be rotated during the truck-loading process. After describing and motivating the problem, a literature review on related work is performed. Then, a multi-start algorithm based on biased randomization of routing and packing heuristics is proposed. A set of computational experiments contribute to illustrate the scope of our approach, as well as to show its efficiency.
机译:本文讨论了具有异构车队(2L-HFVRP)的二维负载限制的车辆路径问题(2L-CVRP)。 2L-CVRP可以在许多与大型物品运输相关的现实生活中使用,必须考虑二维包装限制,例如:重型机械,叉车,专业清洁设备的运输等。在这里,我们还考虑由不同容量,大小和固定/可变成本的单位组成的异构车辆队。尽管在现实生活中异构舰队无处不在,但有关2L-HFVRP的文献却缺乏出版物。特别是,据我们所知,以前没有工作讨论无方向性2L-HFVRP,在卡车装载过程中允许旋转物品。在描述和激发了问题之后,进行了有关工作的文献综述。然后,提出了一种基于路由和打包启发式算法的偏向随机化的多启动算法。一组计算实验有助于说明我们方法的范围,并显示其效率。

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