Anuar Wadi Khalid, Lee Lai Soon, Pickl Stefan
Department of Logistics and Transportation, School of Technology Management and Logistics, Universiti Utara Malaysia, Sintok, Kedah 06010, Malaysia.
Laboratory of Computational Statistics and Operations Research, Institute for Mathematical Research, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia.
Data Brief. 2022 Feb 2;41:107901. doi: 10.1016/j.dib.2022.107901. eCollection 2022 Apr.
The dataset for Multi Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity (MDDVRPSRC) is presented in this paper. The data consist of 10 independent designs of evolving road networks ranging from 14-49 nodes. Together with the road networks are the Damage file (DF) for each corresponding road network. The DF simulates the damage level of roads within the networks due to a disaster source, thus affecting travel time and road capacity. We applied this data to test our proposed algorithm and validate our proposed model. This dataset served as an addition to the Vehicle Routing Problem (VRP) datasets that specifically addressed the road capacity problem during a disaster from an epicentre and could be used for other applications that constitute chaotic events and compromised road networks.
本文给出了具有随机道路容量的多配送中心动态车辆路径规划问题（MDDVRPSRC）的数据集。数据由10个独立设计的不断演变的道路网络组成，节点数从14个到49个不等。与道路网络一起的是每个相应道路网络的损坏文件（DF）。DF模拟了由于灾害源导致的网络内道路的损坏程度，从而影响出行时间和道路容量。我们应用这些数据来测试我们提出的算法并验证我们提出的模型。这个数据集是车辆路径规划问题（VRP）数据集的补充，专门解决了震中灾害期间的道路容量问题，可用于构成混沌事件和受损道路网络的其他应用。
