使用具有自定义成本矩阵的分层TSP预测Amazon最后一英里交付轨迹
Amazon Last-Mile Delivery Trajectory Prediction Using Hierarchical TSP with Customized Cost Matrix
摘要：
为了应对亚马逊最后一英里路由挑战，Team Permission Denied提出了一个具有自定义成本矩阵的分层流动推销员问题（TSP）优化。较高级别的TSP求解区域序列，而较低级别的TSP求解区域内停止序列。修改成本矩阵以考虑最短旅行时间以外的路径模式。最后，进行一些后处理以编辑序列以匹配通常观察到的路由模式，例如当旅行时间相似时，驾驶员通常从具有更多包裹的站点开始，而不是具有更少包裹的站点。该模型在从训练集中随机选择的1223条路线上进行了测试，得分为0.0381。在给定模型应用集中的13条路线上，得分为0.0375。
英文摘要：
In response to the Amazon Last-Mile Routing Challenge, Team Permission Denied proposes a hierarchical Travelling Salesman Problem (TSP) optimization with a customized cost matrix. The higher level TSP solves for the zone sequence while the lower level TSP solves the intra-zonal stop sequence. The cost matrix is modified to account for routing patterns beyond the shortest travel time. Lastly, some post-processing is done to edit the sequence to match commonly observed routing patterns, such as when travel times are similar, drivers usually start with stops with more packages than those with fewer packages. The model is tested on 1223 routes that are randomly selected out of the training set and the score is 0.0381. On the 13 routes in the given model apply set, the score was 0.0375.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
