Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments

dc.contributor.author	Priore Moreno, Paolo
dc.contributor.author	Ponte Blanco, Borja
dc.contributor.author	Rosillo Camblor, Rafael
dc.contributor.author	Fuente García, David Alfonso de la
dc.date.accessioned	2019-03-05T13:07:47Z
dc.date.available	2019-03-05T13:07:47Z
dc.date.issued	2018
dc.identifier.citation	International Journal of Production Research, 57(11), p. 3663-3677 (2018); doi:10.1080/00207543.2018.1552369
dc.identifier.issn	0020-7543
dc.identifier.uri	http://hdl.handle.net/10651/50519
dc.format.extent	p. 3663-3677
dc.language.iso	eng
dc.relation.ispartof	International Journal of Production Research, 57
dc.rights	© 2018 Taylor & Francis
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058171214&doi=10.1080%2f00207543.2018.1552369&partnerID=40&md5=4d8ad4acbbc117b201f9506fbb843986
dc.title	Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments
dc.type	journal article
dc.identifier.doi	10.1080/00207543.2018.1552369
dc.relation.publisherversion	http://dx.doi.org/10.1080/00207543.2018.1552369

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