In this paper, we investigate vehicle routing problems with third-party transshipment facilities that arise in the context of city logistics. Contrary to classical vehicle routing problems, where each customer request is delivered directly to its destination, the problems considered in this paper feature the alternative possibility of delivering customer requests to third-party transshipment facilities, such as urban consolidation centers, for a fee. We present an adaptive large neighborhood search with an embedded random variable neighborhood descent as a local search component and a set-partitioning problem for the recombination of routes to solve various versions of the problem. Thereby, we consider location-dependent time windows as well as heterogeneous fleets and propose several new procedures that consider transshipment facilities within the components of our adaptive large neighborhood search. The proposed method is tested on benchmark instances from the literature as well as newly created benchmark instances. It shows promising results, leading to multiple improvements over existing algorithms from the literature. Moreover, a real-world study is presented to gain managerial insights on the impact of transshipment fees, order size, and heterogeneous fleets on the transshipment decisions.

在本文中，我们研究了在城市物流背景下出现的第三方转运设施的车辆路线问题。与经典的车辆路线问题相反，每个客户的请求都直接交付到目的地，本文中考虑的问题的特点是将客户请求交付给第三方转运设施（如城市集运中心）的另一种可能性，例如收费。我们提出了一种自适应大型邻域搜索，其中嵌入了随机变量邻域下降作为局部搜索组件，并提出了一个用于重新组合路线的集合分割问题，以解决该问题的各种版本。从而，我们考虑了位置相关的时间窗口以及异构船队，并提出了几个新程序，这些程序在我们的自适应大型邻域搜索的组件中考虑了转运设施。所提出的方法在文献中的基准实例以及新创建的基准实例上进行了测试。它显示了有希望的结果，导致对文献中现有算法的多项改进。此外，还提出了一项真实世界的研究，以获得有关转运费用、订单规模和异类船队对转运决策的影响的管理见解。导致对文献中现有算法的多项改进。此外，还提出了一项真实世界的研究，以获得有关转运费用、订单规模和异类船队对转运决策的影响的管理见解。导致对文献中现有算法的多项改进。此外，还提出了一项真实世界的研究，以获得有关转运费用、订单规模和异类船队对转运决策的影响的管理见解。