Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence
Optimizing e-commerce last-mile vehicle routing and scheduling under uncertain customer presence
复制标题
在客户存在不确定的情况下优化电子商务最后一英里的车辆路线和调度
DOI：
10.1016/j.tre.2021.102263
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
G. Laporte
中科院分区：
文献类型：
--
作者：
Sami Serkan Özarık;Lucas P. Veelenturf;T. Woensel;G. Laporte
最近电子商务在线订单的增加导致了物流方面的挑战，例如低命中率（成功交付的比例）。我们考虑了最后一英里车辆路线和调度问题，其中考虑了客户到场概率数据。其目的是通过在计划阶段同时考虑路由和调度决策来减少低命中率导致的预期成本。我们对问题进行建模，并采用自适应大邻域搜索元启发式算法在问题的路由和调度组件之间迭代求解。计算实验表明，与传统的车辆路径解决方案相比，大量使用与客户相关的存在数据可以节省多达40%的系统成本。
The recent increase in online orders in e-commerce leads to logistical challenges such as low hit rates (proportion of successful deliveries). We consider last-mile vehicle routing and scheduling problems in which customer presence probability data are taken into account. The aim is to reduce the expected cost resulting from low hit rates by considering both routing and scheduling decisions simultaneously in the planning phase. We model the problem and solve it by the means of an adaptive large neighborhood search metaheuristic which iterates between the routing and scheduling components of the problem. Computational experiments indicate that using customer-related presence data significantly can yield savings as large as 40% in system-wide costs compared with those of traditional vehicle routing solutions.
影响因子：
4.6
作者：
Savelsbergh, Martin;Van Woensel, Tom
通讯作者：
Van Woensel, Tom