Fajardo Calderín, JennyMasegosa Arredondo, Antonio DavidElejoste Larrucea, Maria PilarMoreno Emborujo, AsierCantero López, XabierAngulo Martínez, Ignacio2026-10-232026-10-232023Fajardo Calderín, J., Masegosa Arredondo, A. D., Elejoste Larrucea, M. P., Moreno Emborujo, A., Cantero López, X., & Angulo Martínez, I. (2023). An Artificial Intelligence-based software module for the optimization of collaborative delivery in last-mile logistics. International Physical Internet Conference - IPIC 2023: Conference papers and posters Contributions Proceedings.https://hdl.handle.net/20.500.14454/6832Ponencia presentada en la 9th International Physical Internet Conference (IPIC 2023), celebrada en Atenas entre el día 13 y el 15 de junio de 2023This paper presents a route delivery planning and simulation module that forms acore part of the ICT Platform of the H2020 SENATOR project, which aims to enhance thesustainability of cities by developing a new urban logistic model. The module utilizes AI-basedoptimization algorithms to support the matching of supply and demand, identify the best fleetmix, and estimate the best delivery route based on real-time conditions. It also allows last-miledelivery planning using different transport modes, inter-modality, and driving restrictions, andsimultaneously optimizes different performance indicators. The paper provides a detaileddescription of the AI-based optimization method and the architecture and components of thesoftware module. Finally, the software module is validated in two scenarios (current operationsand implementation of a Low Emission Zone) using real shipment data from a postal operatorcompany in the living lab that the SENATOR project is implementing in Zaragoza.engLast-mile logisticsVehicle routing problemOptimizationDynamic planningMultimodalCollaborative deliveryconference paper2026-10-23