Izco Berastegui, IreneSerrano Hernández, AdriánFaulín Fajardo, Javier2025-02-072025-01-31Izco, I., Serrano-Hernandez, A., Faulin, J. (2024). Optimal charging station deployment for drone-assisted delivery. In Juan, A. A., Faulin, J., Lopez-Lopez D. (Eds.), Decision Sciences. DSA ISC 2024, Proceedings, Part II (pp. 260-268). Springer. https://doi.org/10.1007/978-3-031-78241-1_24.978-3-031-78241-110.1007/978-3-031-78241-1_24https://academica-e.unavarra.es/handle/2454/53315Last-mile delivery of goods made by drones is considered to be in its experimental phase. Nevertheless, international enterprises such as Amazon, Google, UPS or DHL are expanding new unmanned aerial vehicle technologies related to delivery issues. Flight range of drones is compromised due to the limited battery capacity and the payload of delivered parcels. This challenge is addressed through the placement of charging stations where drone batteries are recharged. As assignment issues have not yet received much attention in the literature, this study will focus on designing drone assignment strategies through optimization. The optimization aims at minimizing charging station installation costs, drone energy consumption, and operational costs. The aim of this work is to design a model to determine the optimal number of the drone hubs, along with their configuration. Moreover, we will determine their location and size, allocating the customer demands to stations and dimensioning the drones¿ fleet in each station to deliver packages efficiently.application/pdfeng© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG.Drone deliveryCharging station infrastructureFacility Location Probleminfo:eu-repo/semantics/conferenceObject2025-02-07info:eu-repo/semantics/embargoedAccess