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dc.contributor.authorLagos, C.
dc.contributor.authorGuerrero, G.
dc.contributor.authorCabrera, E.
dc.contributor.authorNiklander, S.
dc.contributor.authorJohnson, F.
dc.contributor.authorParedes, F.
dc.contributor.authorVega, J.
dc.date.accessioned2025-10-31T18:40:58Z
dc.date.available2025-10-31T18:40:58Z
dc.date.issued2016
dc.identifier.urihttps://hdl.handle.net/20.500.12805/5860
dc.description.abstractA novel matheuristic approach is presented and tested on a well-known optimisation problem, namely, capacitated facility location problem (CFLP). The algorithm combines local search and mathematical programming. While the local search algorithm is used to select a subset of promising facilities, mathematical programming strategies are used to solve the subproblem to optimality. Proposed local search is influenced by instance-specific information such as installation cost and the distance between customers and facilities. The algorithm is tested on large instances of the CFLP, where neither local search nor mathematical programming is able to find good quality solutions within acceptable computational times. Our approach is shown to be a very competitive alternative to solve large-scale instances for the CFLP.en_US
dc.formatapplication/pdf
dc.language.isoeng
dc.publisherHindawi
dc.relation.ispartofurn:issn:1058-9244
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 Facility Location Problemsen_US
dc.titleA Matheuristic Approach Combining Local Search and Mathematical Programmingen_US
dc.typehttps://purl.org/coar/resource_type/c_2df8fbb1
dc.identifier.doihttps://doi.org/10.1155/2016/1506084
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.02.01
dc.type.otherResearch article
dc.identifier.journalScientific Programming
dc.type.versionhttps://purl.org/coar/version/c_970fb48d4fbd8a85


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