Please use this identifier to cite or link to this item: http://repositorio.lnec.pt:8080/jspui/handle/123456789/1018387
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dc.contributor.authorCerqueira, S.pt_BR
dc.contributor.authorArsénio, E.pt_BR
dc.contributor.authorHenriques, R.pt_BR
dc.contributor.authorBarateiro, J.pt_BR
dc.date.accessioned2025-02-21T15:43:49Zpt_BR
dc.date.accessioned2025-04-16T13:40:00Z-
dc.date.available2025-02-21T15:43:49Zpt_BR
dc.date.available2025-04-16T13:40:00Z-
dc.date.issued2024-04-15pt_BR
dc.identifier.citationCerqueira, S., Arsénio, E., Henriques, R., Barateiro, J. (2024) Freight demand modeling for green and digital logistics, 10th Transport Research Arena (TRA) Conference, Dublin.pt_BR
dc.identifier.urihttp://repositorio.lnec.pt:8080/jspui/handle/123456789/1018387-
dc.description.abstractFreight transport demand modelling (FTDM) from dispatch logs and partial observations play a key role in providing realistic expectations of freight transport needs and in assessing the environmental impacts of new policies. Shaping freight transport to answer the current challenges of green logistics – decarbonization, energy consumption optimization, intelligent and sustainable management – requires a continuous assessment and adaptation of the whole logistic system. Demand-centric models may support these ends. Understanding advances in freight modelling is thus crucial to overcoming FTDM challenges, including data scarcity. This paper provides two major contributions: i) a review of the state-of-the-art models on freight transport demand modelling, and ii) an integrated overview of how these models can support decision-making aligned with sustainability goals towards green (zero emissions) and digital logistics.pt_BR
dc.language.isoengpt_BR
dc.publisherSpringerpt_BR
dc.relationHorizon Europept_BR
dc.rightsrestrictedAccesspt_BR
dc.subjectFreight demand modellingpt_BR
dc.subjectGreen logisticspt_BR
dc.subjectDigital logisticspt_BR
dc.subjectFreight origin-destination modelspt_BR
dc.subjectZero emissonspt_BR
dc.subjectSustainable transport and logisticspt_BR
dc.subjectArtificial intelligencept_BR
dc.subjectIntelligent transport and supply chainspt_BR
dc.titleFreight demand modeling for green and digital logisticspt_BR
dc.typeworkingPaperpt_BR
dc.description.pages6p.pt_BR
dc.description.commentsEstudo realizado no âmbito do projeto de I&I ADMIRAL financiado pelo programa Horizonte Europa (Grant Agreement 101104163), coordenado no LNEC pela IP Elisabete Arsénio. A comunicação foi aceite para publicação pela Springer.pt_BR
dc.description.sectorDT/CHEFIApt_BR
dc.identifier.proc0701/1101/23484pt_BR
dc.identifier.conftitle10th Transport Research Arena (TRA) Conference 2024 / TRA 2024pt_BR
dc.contributor.peer-reviewedNAOpt_BR
dc.contributor.academicresearchersSIMpt_BR
dc.contributor.arquivoSIMpt_BR
Appears in Collections:DT/Chefia - Comunicações a congressos e artigos de revista

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