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dc.contributor.authorLagos, C.
dc.contributor.authorParedes, F.
dc.contributor.authorNiklander, S.
dc.contributor.authorCabrera, E.
dc.date.accessioned2025-10-31T18:41:13Z
dc.date.available2025-10-31T18:41:13Z
dc.date.issued2015
dc.identifier.urihttps://hdl.handle.net/20.500.12805/5880
dc.description.abstractDistribution network design (DND) attempts to integrate tactical issues such as inventory policies and/or vehicle routing decisions with strategic ones such as the problem of locating facilities and allocate customers to such facilities. When inventory policy decision making is considered the problem is also known as inventory location modelling (ILM) problem. During the last two decades, mathematical programming as well as (meta-)heuristic approaches have been considered to address different DND problem. In this article we consider a hybrid algorithm of Lagrangian Relaxation and artificial ants to solve an ILM problem previously proposed in the literature. We use ACS to allocate customers to a subset of warehouses that is previously generated by the Lagrangian relaxation. Results show that the hybrid approach is quite competitive, obtaining near-optimal solutions within an acceptable time.en_US
dc.formatapplication/pdf
dc.language.isoeng
dc.publisherNational Institute for R and D in Informatics
dc.relation.ispartofurn:issn:1841-429X
dc.rightshttps://purl.org/coar/access_right/c_abf2
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectOptimized Logistics and Vehicle Routing Solutionsen_US
dc.subjectOptimization Models for Supply Chain Network Designen_US
dc.titleSolving a distribution network design problem by combining ant colony systems and Lagrangian relaxationen_US
dc.typehttps://purl.org/coar/resource_type/c_2df8fbb1
dc.identifier.doihttps://doi.org/10.24846/v24i3y201502
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.11.04
dc.type.otherResearch article
dc.identifier.journalStudies in Informatics and Control
dc.type.versionhttps://purl.org/coar/version/c_970fb48d4fbd8a85


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