Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/31137
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Campo DC | Valor | Idioma |
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dc.contributor.author | Elvas, L. B. | - |
dc.contributor.author | Tokkozhina, U. | - |
dc.contributor.author | Martins, A. | - |
dc.contributor.author | Ferreira, J. | - |
dc.contributor.editor | Luís de Picado Santos | - |
dc.contributor.editor | Jorge Pinho de Sousa | - |
dc.contributor.editor | Elisabete Arsenio | - |
dc.date.accessioned | 2024-02-21T12:07:53Z | - |
dc.date.available | 2024-02-21T12:07:53Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Elvas, L. B., Tokkozhina, U., Martins, A., & Ferreira, J. (2023). Implementation of disruptive technologies for the last mile delivery efficiency achievement. Em L. P. Santos, J. P. Sousa, & E. Arsenio (Eds.). 2022 Conference Proceedings Transport Research Arena, TRA Lisbon 2022 (Vol.72, pp. 32-39). Elsevier. https://doi.org/10.1016/j.trpro.2023.11.319 | - |
dc.identifier.issn | 2352-1457 | - |
dc.identifier.uri | http://hdl.handle.net/10071/31137 | - |
dc.description.abstract | he last mile delivery (LMD) is one of the most tangled procedures in logistics. The reason is that it involves various uncertainties, including weather and road conditions, traffic hours and route selection, car accidents, delivery vehicle anomalies, at the same time needing to avoid parcel damages and delivery errors, while communicating with the recipient of the parcel. Above-mentioned factors cause the difficulties of successful parcels delivery to customers' doorsteps. Therefore, businesses need to search for technology solutions that will enable increase of last mile delivery efficiency. All intelligent solutions are built upon big data, as huge volumes of data allow the prediction of future behavior based on historical knowledge. In this study we propose a last-mile solution where the combination of disruptive technologies allow a better distribution without costs increasing. | eng |
dc.language.iso | eng | - |
dc.publisher | Elsevier | - |
dc.relation.ispartof | 2022 Conference Proceedings Transport Research Arena, TRA Lisbon 2022 | - |
dc.rights | openAccess | - |
dc.subject | Inteligência artificial -- Artificial intelligence | eng |
dc.subject | Internet of Things (IoT) | eng |
dc.subject | Blockchain | eng |
dc.subject | Big data | eng |
dc.subject | Last mile delivery | eng |
dc.subject | Otimização -- Optimization | eng |
dc.title | Implementation of disruptive technologies for the last mile delivery efficiency achievement | eng |
dc.type | conferenceObject | - |
dc.event.type | Conferência | pt |
dc.event.date | 2022 | - |
dc.pagination | 32 - 39 | - |
dc.peerreviewed | yes | - |
dc.volume | 72 | - |
dc.date.updated | 2024-02-21T12:06:33Z | - |
dc.description.version | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.doi | 10.1016/j.trpro.2023.11.319 | - |
dc.subject.fos | Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Civil | por |
iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-100122 | - |
iscte.alternateIdentifiers.scopus | 2-s2.0-85182924457 | - |
Aparece nas coleções: | BRU-CRI - Comunicações a conferências internacionais ISTAR-CRI - Comunicações a conferências internacionais |
Ficheiros deste registo:
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conferenceObject_100122.pdf | 636,93 kB | Adobe PDF | Ver/Abrir |
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