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首页> 外文期刊>Computers & operations research >Metaheuristics for the waste collection vehicle routing problem with time windows, driver rest period and multiple disposal facilities
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Metaheuristics for the waste collection vehicle routing problem with time windows, driver rest period and multiple disposal facilities

机译:具有时间窗,驾驶员休息时间和多重处置设施的废物收集车辆路线问题的元启发式

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摘要

In this problem there is a set of waste disposal facilities, a set of customers at which waste is collected and an unlimited number of homogeneous vehicles based at a single depot. Empty vehicles leave the depot and collect waste from customers, emptying themselves at the waste disposal facilities as and when necessary. Vehicles return to the depot empty. We take into consideration time windows associated with customers, disposal facilities and the depot. We also have a driver rest period. The problem is solved heuristically. A neighbour set is defined for each customer as the set of customers that are close, but with compatible time windows. A procedure that attempts to fully utilise a vehicle is used to obtain an initial solution, with this initial solution being improved using an interchange procedure. We present two metaheuristic algorithms using tabu search and variable neighbourhood search that are based around the neighbour sets. We also present a metaheuristic based on variable neighbourhood tabu search, where the variable neighbourhood is searched via tabu search. Computational results are presented for publicly available waste collection problems involving up to 2092 customers and 19 waste disposal facilities, which indicate that our algorithms produce better quality solutions than previous work presented in the literature.
机译:在这个问题中,存在一套废物处理设施,一套收集废物的客户以及一个单一仓库中数量不限的同类车辆。空的车辆离开仓库,从客户那里收集废物,并在必要时在废物处理设施中将其倒空。车辆空着返回仓库。我们考虑与客户,处置设施和仓库相关的时间窗口。我们也有驾驶员休息时间。该问题通过启发式解决。为每个客户定义的邻居集是相近但具有兼容时间窗口的一组客户。尝试充分利用车辆的过程用于获得初始解决方案,该初始解决方案使用互换过程进行了改进。我们提出两种基于禁忌搜索和变量邻域搜索的元启发式算法,它们基于邻居集。我们还提出了基于变邻域禁忌搜索的元启发式方法,其中通过禁忌搜索来搜索可变邻域。针对涉及多达2092位客户和19个废物处理设施的公共废物收集问题,给出了计算结果,这表明我们的算法比文献中先前的工作提供了更好的质量解决方案。

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