Multitrip vehicle routing with delivery options: a data-driven application to the parcel industry
研究包裹配送中多行程车辆路径问题，提出数据驱动框架评估不同投递选项（如包裹柜、自提点），通过自适应大邻域搜索求解，并用欧洲包裹公司真实数据证明可降低配送成本、引导客户选择环保方案。
Abstract To make the last mile of parcel delivery more efficient, service providers offer an increasing number of modes of delivery as alternatives to the traditional and often cost-intensive home delivery service. Parcel lockers and pickup stations can be utilized to reduce the number of stops and avoid costly detours. To design smart delivery networks, service providers must evaluate different business models. In this context, a multitrip vehicle routing problem with delivery options and location-dependent costs arises. We present a data-driven framework to evaluate alternative delivery strategies, formulate a corresponding model and solve the problem heuristically using adaptive large neighborhood search. By examining large, real-life instances from a major European parcel service, we determine the potential and benefits of different delivery options. Specifically, we show that delivery costs can be mitigated by consolidating orders in pickup stations and illustrate how pricing can be applied to steer customer demand toward profitable, eco-friendly products.