An intelligent decision support system for road freight transport

doi:10.1007/978-3-031-21753-1_15

Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/85707

Registo completo

Campo DC	Valor	Idioma
dc.contributor.author	Carvalho, Hugo Silva	por
dc.contributor.author	Pilastri, André Luiz	por
dc.contributor.author	Matta, Arthur	por
dc.contributor.author	Matos, Luís Miguel	por
dc.contributor.author	Novais, Rui	por
dc.contributor.author	Cortez, Paulo	por
dc.date.accessioned	2023-07-26T09:05:53Z	-
dc.date.available	2023-07-26T09:05:53Z	-
dc.date.issued	2022	-
dc.identifier.isbn	978-3-031-21752-4	-
dc.identifier.issn	0302-9743	-
dc.identifier.uri	https://hdl.handle.net/1822/85707	-
dc.description.abstract	This paper presents an Intelligent Decision Support System (IDSS) to optimize transport and logistics activities in a set of Portuguese companies currently operating in the freight transport sector. This IDSS comprises three main modules that can be used individually or chained together, dedicated to: a geographic clustering detection of transport services; a transport driver suggestion; and a route and truck-load optimization. The IDSS was entirely designed and developed to support real-time data and it consists of an end-to-end solution (E2ES), given that it covers all the main transport and logistics processes since the registration in the database to the optimized transport plan. The entire set of functionalities inserted in the IDSS was designed and validated by freight transport sector experts from the different companies that will use the proposed system.	por
dc.description.sponsorship	ERDF - European Regional Development Fund(undefined)	por
dc.description.sponsorship	The authors would like to express the most significant recognition to the project on which this IDSS has arisen, “aDyTrans - Dynamic Transportations Platform” reference NORTE-01-0247-FEDER-045174, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF	por
dc.language.iso	eng	por
dc.publisher	Springer	por
dc.relation	NORTE-01-0247-FEDER-045174	por
dc.rights	openAccess	por
dc.subject	Intelligent decision support system	por
dc.subject	Transport and logistics	por
dc.subject	Geospatial clustering	por
dc.subject	Resource optimization	por
dc.subject	Route optimization	por
dc.subject	TAM 3	por
dc.title	An intelligent decision support system for road freight transport	por
dc.type	conferencePaper	por
dc.peerreviewed	yes	por
dc.relation.publisherversion	https://link.springer.com/chapter/10.1007/978-3-031-21753-1_15	por
oaire.citationStartPage	146	por
oaire.citationEndPage	156	por
oaire.citationVolume	13756	por
dc.date.updated	2023-07-17T16:12:32Z	-
dc.identifier.doi	10.1007/978-3-031-21753-1_15	por
dc.subject.wos	Science & Technology	-
sdum.export.identifier	12634	-
sdum.journal	Lecture Notes in Computer Science	por
sdum.conferencePublication	International Conference on Intelligent Data Engineering and Automated Learning	por
sdum.bookTitle	Intelligent Data Engineering and Automated Learning – IDEAL 2022	por
Aparece nas coleções:	CAlg - Artigos em livros de atas/Papers in proceedings

Ficheiros deste registo:

Ficheiro	Descrição	Tamanho	Formato
IDEAL_2022_paper_4408.pdf		3,07 MB	Adobe PDF	Ver/Abrir

Ver registo simples Sugerir correção Estatísticas

Citations

Altmetrics