Resilience optimisation for next generation drone logistic networks

The paper will present a novel approach to the design optimisation of a resilient Drone Logistic Network (DLN) for the delivery of medical equipment. It is proposed a digital blueprint methodology that integrates Digital Twin (DT) models and optimisation tools, with the goal to optimise both the network topology and the delivery planningscheduling over the defined network. The DLN is a complex system being composed of a high number of different classes of drones and ground infrastructures which interconnections give rise to the whole network behaviour. Uncertainty, that comes in different forms, affects at different levels the subsystems and the whole network. The paper will present the generative network optimisation which is the approach used to define, by design, the network topology and configuration that are optimal for the defined Key Performance Indicators. It will then focus on the operational optimisation problem which, for a predefined DLN, aims at determining the optimal drone’s planning and scheduling considering also the uncertainty on the environment and the possible unexpected events.