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Freight demand modeling for green and digital logistics

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dc.contributor.author Cerqueira, S. pt_BR
dc.contributor.author Arsénio, E. pt_BR
dc.contributor.author Henriques, R. pt_BR
dc.contributor.author Barateiro, J. pt_BR
dc.date.accessioned 2025-02-21T15:43:49Z pt_BR
dc.date.accessioned 2025-04-16T13:40:00Z
dc.date.available 2025-02-21T15:43:49Z pt_BR
dc.date.available 2025-04-16T13:40:00Z
dc.date.issued 2024-04-15 pt_BR
dc.identifier.citation Cerqueira, 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.uri http://repositorio.lnec.pt:8080/jspui/handle/123456789/1018387
dc.description.abstract Freight 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.iso eng pt_BR
dc.publisher Springer pt_BR
dc.relation Horizon Europe pt_BR
dc.rights restrictedAccess pt_BR
dc.subject Freight demand modelling pt_BR
dc.subject Green logistics pt_BR
dc.subject Digital logistics pt_BR
dc.subject Freight origin-destination models pt_BR
dc.subject Zero emissons pt_BR
dc.subject Sustainable transport and logistics pt_BR
dc.subject Artificial intelligence pt_BR
dc.subject Intelligent transport and supply chains pt_BR
dc.title Freight demand modeling for green and digital logistics pt_BR
dc.type workingPaper pt_BR
dc.description.pages 6p. pt_BR
dc.description.comments Estudo 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.sector DT/CHEFIA pt_BR
dc.identifier.proc 0701/1101/23484 pt_BR
dc.identifier.conftitle 10th Transport Research Arena (TRA) Conference 2024 / TRA 2024 pt_BR
dc.contributor.peer-reviewed NAO pt_BR
dc.contributor.academicresearchers SIM pt_BR
dc.contributor.arquivo SIM pt_BR


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