Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104270
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorChen, YTen_US
dc.creatorChan, FTSen_US
dc.creatorChung, SHen_US
dc.creatorPark, WYen_US
dc.date.accessioned2024-02-05T08:47:43Z-
dc.date.available2024-02-05T08:47:43Z-
dc.identifier.issn0736-5845en_US
dc.identifier.urihttp://hdl.handle.net/10397/104270-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2017 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Chen, Y. T., Chan, F. T. S., Chung, S. H., & Park, W.-Y. (2018). Optimization of product refurbishment in closed-loop supply chain using multi-period model integrated with fuzzy controller under uncertainties. Robotics and Computer-Integrated Manufacturing, 50, 1339–1351 is available at https://doi.org/10.1016/j.rcim.2017.05.005.en_US
dc.subjectClosed-loop supply chainen_US
dc.subjectDecision support systemen_US
dc.subjectFuzzy logicen_US
dc.subjectProduct recoveryen_US
dc.subjectProduct refurbishmenten_US
dc.subjectSimulationen_US
dc.titleOptimization of product refurbishment in closed-loop supply chain using multi-period model integrated with fuzzy controller under uncertaintiesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1339en_US
dc.identifier.epage1351en_US
dc.identifier.volume50en_US
dc.identifier.doi10.1016/j.rcim.2017.05.005en_US
dcterms.abstractNowadays, product refurbishment is one of the most profitable and environmental benefit processes, drawing more and more attention from both product manufacturers and customers. This paper structures and optimizes the process of product refurbishment, considering inventories and uncertainties. A multi-period model is established. To deal with the uncertainties, an innovative fuzzy controller embedded with a quality indicator is proposed. Numerical experiments have been carried out to test and demonstrate the optimization quality of the proposed method. The results of numerical experiments proved the effectiveness of the proposed fuzzy controller, that can deal with the uncertainties of supply and demand in an efficient way.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRobotics and computer - integrated manufacturing, Apr. 2018, v. 50, p. 1339-1351en_US
dcterms.isPartOfRobotics and computer - integrated manufacturingen_US
dcterms.issued2018-04-
dc.identifier.scopus2-s2.0-85019656792-
dc.identifier.eissn1879-2537en_US
dc.description.validate202402 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberISE-0672-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6747668-
dc.description.oaCategoryGreen (AAM)en_US
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