Modeling of Logistics Networks with Labeled Property Graphs for Simulation in Digital Twins

Digital twins have gained increasing attention in research and practice. This includes the use in logistics networks, which are the parts of supply chains focusing on implementing flows of goods. Digital twins are the digital representation of physical objects and feature a wide array of data. The tasks of digital twins in the domain of logistics include simulation, optimization, and monitoring. To fulfill these tasks, data models are required as a base. Using a common data model for all tasks is a promising approach, but there is a lack of modeling rules and guidelines on how to create appropriate models. In this paper, a modeling framework is proposed and discussed to fill this gap for logistics networks. It is based on labeled property graphs, which are a special graph structure. Also, the proposed modeling framework is applied exemplarily on a real-world use case scenario in the domain of city logistics.