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dc.contributor.authorEmirhüseyinoğlu, Görkem
dc.contributor.authorEkici, Ali
dc.date.accessioned2020-07-06T10:24:53Z
dc.date.available2020-07-06T10:24:53Z
dc.date.issued2019-08
dc.identifier.issn0360-8352en_US
dc.identifier.urihttp://hdl.handle.net/10679/6706
dc.identifier.urihttps://www.sciencedirect.com/science/article/abs/pii/S036083521930289X
dc.description.abstractRetailers have to consider several factors when making facility location decisions including suppliers' and customers' locations, customer demand and price offered by suppliers. In this study, we analyze the multi-period facility location decisions of a retailer which procures the products from multiple suppliers under an incremental quantity discount scheme and in turn satisfies an exogenous demand. The retailer decides (i) where and when to open a facility, (ii) how much to order from each supplier in each time period, and (iii) from which facility locations to satisfy the demand. We formulate the problem as a mixed-integer mathematical model. To handle large instances, we develop a decomposition-based solution approach which considers the decisions in the first echelon (suppliers and facilities) and the second echelon (facilities and customers) in an iterative manner until convergence. We propose two implementations of the proposed solution approach. The first one limits the search space by considering only a subset of the facility locations for each customer. In the second implementation of the proposed solution approach, we develop a novel two-phase strategy where we first eliminate some of the facility locations entirely from the problem using a simplified version of the first approach and then implement the first approach to the reduced set of facility locations. We demonstrate the effectiveness of the heuristic approaches through an extensive computational study. The proposed heuristics provide significantly better results compared to a simple heuristic inspired by a related study. Moreover, we observe that for small instances both heuristics provide solutions with quite low optimality gaps and for larger instances they find better solutions in less amount of time when compared against CPLEX results obtained within a 12-h time limit.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.ispartofComputers and Industrial Engineering
dc.rightsrestrictedAccess
dc.titleDynamic facility location with supplier selection under quantity discounten_US
dc.typeArticleen_US
dc.peerreviewedyesen_US
dc.publicationstatusPublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0002-9627-4780 & YÖK ID 124801) Ekici, Ali
dc.contributor.ozuauthorEkici, Ali
dc.identifier.volume134en_US
dc.identifier.startpage64en_US
dc.identifier.endpage74en_US
dc.identifier.wosWOS:000474493600006
dc.identifier.doi10.1016/j.cie.2019.05.023en_US
dc.subject.keywordsDynamic facility locationen_US
dc.subject.keywordsSupplier selectionen_US
dc.subject.keywordsQuantity discounten_US
dc.subject.keywordsIterative algorithmen_US
dc.identifier.scopusSCOPUS:2-s2.0-85067926167
dc.contributor.ozugradstudentEmirhüseyinoğlu, Görkem
dc.contributor.authorMale2
dc.relation.publicationcategoryArticle - International Refereed Journal - Institutional Academic Staff and Graduate Student


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