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An advanced hybrid meta-heuristic algorithm for the vehicle routing problem with backhauls and time windows

机译:具有回程和时间窗的车辆路径问题的高级混合元启发式算法

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This paper presents an advanced hybrid meta-heuristic algorithm (HMA) to solve the vehicle routing problem with backhauls and time windows (VRPBTW). The VRPBTW is an extension of the vehicle routing problem with time windows (VRPTW) and the vehicle routing problem with backhauls (VRPB) that includes capacity, backhaul and time window constraints. In this problem, the customers are divided into two subsets consisting of linehaul and backhaul customers. Each vehicle starts from the depot, and goods are delivered from the depot to the linehaul customers. Goods are subsequently returned to the depot from the backhaul customers. The objective is to minimize the total distance that satisfies all of the constraints. The proposed meta-heuristic method is tested on a problem data set obtained from Solomon's VRPTW benchmark problems which includes 25, 50 and 100 demand nodes. The results of the computational studies show that the HMA outperforms the existing studies and provides better solutions than the best known solutions in practical computational times.
机译:本文提出了一种先进的混合元启发式算法(HMA),以解决带有回程和时间窗(VRPBTW)的车辆路径问题。 VRPBTW是带有时间窗(VRPTW)的车辆路由问题和带有回程(VRPB)的车辆路由问题的扩展,其中回程包括容量,回程和时间窗约束。在此问题中,客户被分为由线路回程和回程客户组成的两个子集。每辆车都从仓库出发,货物从仓库运送到线路运输客户。随后,货物从回程客户处返回仓库。目的是最小化满足所有约束条件的总距离。在从所罗门的VRPTW基准问题获得的问题数据集上测试了提出的元启发式方法,该问题数据集包括25个,50个和100个需求节点。计算研究的结果表明,在实际计算时间内,HMA优于现有研究,并提供了比最知名解决方案更好的解决方案。

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