| 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 |