2E-VRP-SCS Data

Inspired by the lane-sharing phenomenon in the city logistics practices, a concept named the “sharing-lane crossdock satellite” (SCS) is introduced. We introduce the two-echelon vehicle routing problem with SCSs (2E-VRP-SCS). On the first echelon, 1st-echelon vehicles depart from the city distribution center (CDC) to serve SCSs. At authorized time windows, 1st-echelon vehicles can park at SCSs for cargo transshipment between vehicles. On the second echelon, 2nd-echelon vehicles receive cargoes to service customers. SCSs are used to perform the direct transshipment that is defined as moving cargoes directly from 1st-echelon vehicles to 2nd-echelon vehicles, with no storing. Each SCS has several time windows. The 2E-VRP-SCS network includes one CDC, a number of SCSs, a number of customers, and arcs. A homogeneous fleet of 1st-echelon vehicles is available at the CDC. Second-echelon vehicles departing from each SCS serve customers. At SCSs, there is a constant transshipment speed of cargoes being moved from 1st-echelon vehicles to 2nd-echelon vehicles, and the transshipment speed is determined by the cargo volume per hour. At a time window of one SCS, “the available transshipment capacity” = “the transshipment speed” × “the remaining time of the time window”. In a route, a vehicle can visit an SCS or one customer at most once, and constraints on route duration must be respected. At a time window of an SCS, there parks no more than one 1st-echelon vehicle. Direct transshipment is considered a one-to-one operation. The 2E-VRP-SCS objective is to minimize the vehicle working time. We design 35 small-scale instances. The number (NumS) of included SCSs is 1, 2 or 3. The number (NumC) of customers is 5, 6, 8, 9 or 10. Each small-scale instance is named by S-NumS-NumC-No. (No. is 1, 2, 3, 4 or 5). The network is abstracted on a graph with a grid of 1 km. The CDC is located at the center node of the graph. Other nodes are randomly selected to act as SCS and customer locations. Customer demand is randomly estimated. The whole time window of SCS m is confirmed beforehand. Large-scale instances are designed by referring to practical data. We observe the situation of traffic flows on some roads on several working days. Several lane-spaces are empirically chosen to make up the SCS set. The included SCSs are randomly chosen from the SCS set. The distance between any two nodes on the first echelon is calculated through the latitudes and longitudes of nodes. We supplement some data by the method of generating small-scale instances. We design 42 large-scale instances that are denoted as L-NumS-NumC-No. (No. is 1, 2 or 3). Of the large-scale instances, NumS is 5, 10, 20 or 30. NumC is 50, 75, 100, 150, 200, 250, 300, 400, 500 or 600, which is chosen by referring to NumS.受城市物流实践中的共享车道现象启发，本文提出了“共享车道越库卫星节点（sharing-lane crossdock satellite, SCS）”这一概念，并构建了考虑SCS的两阶段车辆路径问题（two-echelon vehicle routing problem with SCSs, 2E-VRP-SCS）。在第一阶段，第一梯队车辆从城市配送中心（city distribution center, CDC）出发，前往服务各SCS节点。在指定的时间窗内，第一梯队车辆可停靠于SCS节点，完成车辆间的货物转运。第二阶段中，第二梯队车辆接收货物后为客户提供配送服务。SCS节点用于执行直接转运操作，即直接将货物从第一梯队车辆转移至第二梯队车辆，全程不进行货物存储。每个SCS节点均设有多个时间窗。 2E-VRP-SCS的网络结构包含1个CDC、若干SCS节点、若干客户节点以及弧段。CDC处配备一支同质化的第一梯队车辆车队。从各SCS节点出发的第二梯队车辆负责为客户提供配送服务。在SCS节点处，货物从第一梯队车辆转运至第二梯队车辆的转运速度固定，该速度由每小时的货物吞吐量决定。在单个SCS节点的时间窗内，“可用转运容量”=“转运速度”ד该时间窗的剩余时长”。 在一条配送路径中，车辆最多仅可访问一次SCS节点或客户节点，且需遵守路径时长约束。在SCS节点的单个时间窗内，停靠的第一梯队车辆数量不得超过1台。直接转运被视为一对一的操作。2E-VRP-SCS的优化目标为最小化车辆总作业时长。 本文共设计了35个小规模算例。其中，包含的SCS节点数量（NumS）为1、2或3，客户数量（NumC）为5、6、8、9或10。每个小规模算例的命名格式为S-NumS-NumC-No.（其中No.取值为1、2、3、4或5）。网络以1km为网格单位抽象为图结构，CDC位于该图的中心节点，其余节点均随机选取作为SCS节点或客户节点。客户需求为随机生成的估算值，SCS节点m的整体时间窗均预先设定。 大规模算例则参考实际运营数据进行设计。研究人员通过多个工作日的道路车流观测数据，依据经验选取若干共享车道区域构建SCS集合，再从该集合中随机选取所需的SCS节点。第一梯队节点间的距离通过节点的经纬度计算得到。部分数据通过生成小规模算例的方法进行补充。本文共设计了42个大规模算例，命名格式为L-NumS-NumC-No.（其中No.取值为1、2或3）。在大规模算例中，NumS取值为5、10、20或30，NumC取值为50、75、100、150、200、250、300、400、500或600，具体取值参考NumS的规模进行匹配。