Optimal charging station deployment for drone-assisted delivery

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dc.contributor.authorIzco Berastegui, Irene
dc.contributor.authorSerrano Hernández, Adrián
dc.contributor.authorFaulín Fajardo, Javier
dc.contributor.departmentEstadística, Informática y Matemáticases_ES
dc.contributor.departmentEstatistika, Informatika eta Matematikaeu
dc.contributor.departmentInstitute of Smart Cities - ISCen
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
dc.date.accessioned2025-02-07T10:47:03Z
dc.date.issued2025-01-31
dc.date.updated2025-02-07T10:39:21Z
dc.description.abstractLast-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.en
dc.description.sponsorshipThis work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (PID2022-140278NB-I00 project and RED2022-134703-T network). Additionally, we acknowledge the support from the Public University of Navarre for Young Researchers Projects Program (PJUPNA26-2022) and the UNED Pamplona (UNEDPAM/PI/ PR24/04P project).
dc.embargo.lift2026-01-31
dc.embargo.terms2026-01-31
dc.format.mimetypeapplication/pdfen
dc.identifier.citationIzco, 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.
dc.identifier.doi10.1007/978-3-031-78241-1_24
dc.identifier.isbn978-3-031-78241-1
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/53315
dc.language.isoeng
dc.publisherSpringer
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-140278NB-I00/ES/
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/RED2022-134703-T/
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-031-78241-1_24
dc.rights© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG.
dc.rights.accessRightsinfo:eu-repo/semantics/embargoedAccess
dc.subjectDrone deliveryen
dc.subjectCharging station infrastructureen
dc.subjectFacility Location Problemen
dc.titleOptimal charging station deployment for drone-assisted deliveryen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePublication
relation.isAuthorOfPublication5209329f-a11e-4496-94ae-c1d3c54fe887
relation.isAuthorOfPublicationa5bd4bdf-1145-4413-84b6-682cbe997245
relation.isAuthorOfPublication2f9b6dfd-9ac6-42b0-bff1-82079b8a03b8
relation.isAuthorOfPublication.latestForDiscovery2f9b6dfd-9ac6-42b0-bff1-82079b8a03b8

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