We study routing for on-demand last-mile logistics with two crucial novel features: i) Multiple depots, optimizing where to pick-up every order, ii) Allowing vehicles to perform depot returns prior to being empty, thus adapting their routes to include new orders online. Both features result in shorter distances and more agile planning. We propose a scalable dynamic method to deliver orders as fast as possible. Following a rolling horizon approach, each time step the following is executed. First, define potential pick-up locations and identify which groups of orders can be transported together, with which vehicle and following which route. Then, decide which of these potential groups of orders will be executed and by which vehicle by solving an integer linear program. We simulate one day of service in Amsterdam that considers 10,000 requests, compare results to several strategies and test different scenarios. Results underpin the advantages of the proposed method
翻译:我们研究了一种新型的即时配送路由问题,具有两个关键的新特性:i)多个配送中心,优化每个订单的取货位置,ii)允许回仓库以便在空车的情况下返回仓库,因此可以在线适应新的订单,从而实现更短的路程和更灵活的计划。我们提出了一种可扩展的动态方法,以尽快交付订单。按照滚动的时间序列方法,每个时间步骤执行以下操作。首先,确定潜在的取货位置,并确定哪些订单组可以在哪辆车上一起运输,如何安排其路线。然后,通过求解整数线性规划,决定将执行哪些潜在订单和由哪个车辆执行。我们模拟了阿姆斯特丹的一天服务,考虑了10,000个请求,将结果与几种策略进行了比较,并测试了不同的情况。结果证明了所提出方法的优点。