Generative optimisation of resilient drone logistic networks

Filippi, Gianluca and Vasile, Massimiliano and Patelli, Edoardo and Fossati, Marco; (2022) Generative optimisation of resilient drone logistic networks. In: 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings . IEEE, ITA. ISBN 9781665467087 (

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This paper presents a novel approach to the gener-ative design optimisation of a resilient Drone Logistic Network (DLN) for the delivery of medical equipment in Scotland. A DLN is a complex system composed of a high number of different classes of drones and ground infrastructures. The corresponding DLN model is composed of a number of interconnected digital twins of each one of these infrastructures and vehicles, forming a single digital twin of the whole logistic network. The paper proposes a multi-agent bio-inspired optimisation approach based on the analogy with the Physarum Policefalum slime mould that incrementally generates and optimise the DLN. A graph theory methodology is also employed to evaluate the network resilience where random failures, and their cascade effect, are simulated. The different conflicting objectives are aggregated into a single global performance index by using Pascoletti-Serafini scalarisation.


Filippi, Gianluca, Vasile, Massimiliano ORCID logoORCID:, Patelli, Edoardo ORCID logoORCID: and Fossati, Marco ORCID logoORCID:;