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dc.contributor.authorXu, W
dc.contributor.authorLuis, M
dc.contributor.authorYuce, B
dc.date.accessioned2024-01-26T15:01:59Z
dc.date.issued2023-12-07
dc.date.updated2024-01-26T13:23:21Z
dc.description.abstractCrow search algorithm for binary optimization (BinCSA) is currently used in some ideal models of the uncapacitated facility location problem (UFLP), but studies on its use in real-world supply chain cases remain limited. Therefore, this study aimed to address the gap by introducing a hybrid method that combined the BinCSA with an exact method to solve a CLSC problem, including location allocation, transportation, and supplier selection challenges. The initial sections of the study included theoretical foundations and experimental results of the BinCSA. Subsequently, how the BinCSA works in the proposed hybrid method was discussed, and the computational results were showed to evaluate the performance of the proposed method.en_GB
dc.format.extent1449-
dc.identifier.citationVol. 14(7), pp. 1449-1460en_GB
dc.identifier.doihttps://doi.org/10.14716/ijtech.v14i7.6710
dc.identifier.urihttp://hdl.handle.net/10871/135155
dc.identifierORCID: 0000-0002-1368-8284 (Luis, Martino)
dc.language.isoenen_GB
dc.publisherInternational Journal of Technologyen_GB
dc.rights© 2023. Open access articleen_GB
dc.subjectCrow search algorithmen_GB
dc.subjectClosed-loop supply chainen_GB
dc.subjectFacility location problemen_GB
dc.subjectHybrid methoden_GB
dc.titleA Hybrid Method for The Closed-loop Supply Chain to Minimize Total Logistics Costsen_GB
dc.typeArticleen_GB
dc.date.available2024-01-26T15:01:59Z
dc.identifier.issn2231-3907
dc.descriptionThis is the final version. Available on open access from the International Journal of Technology via the DOI in this recorden_GB
dc.identifier.eissn2087-2100
dc.identifier.journalInternational Journal of Technologyen_GB
dc.relation.ispartofInternational Journal of Technology, 14(7)
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-12-07
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2024-01-26T14:59:37Z
refterms.versionFCDVoR
refterms.dateFOA2024-01-26T15:02:00Z
refterms.panelBen_GB
refterms.dateFirstOnline2023-12-07


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