A Digital Twin Approach for Last-Mile Delivery

This study presents a Digital Twin (DT)-based system to solve the last-mile delivery problem. The city is divided in zones, each zone is associated to a hub where the trucks arrive and the last-mile deliveries are performed by a set of robots. The DT architecture is composed of an application layer that optimize the robot initial routes, a simulation layer connected with the physical layer to manage unexpected events, such as traffic congestion and road closures. A Mixed Integer Linear Programming (MILP) optimization model is designed to determine the optimal routes of the robots and a simulation model is implemented for the rerouting application. The system is validated through two case studies conducted in the city of Bari, Italy, using the MILP model to reduce travel distances and energy consumption of robots and the Simulation of Urban Mobility tool for reproducing the DT physical layer. The results demonstrate the effectiveness and adaptability of the proposed approach.