Assortment optimization with log-linear demand: application at a Turkish grocery store

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dc.authorid0000-0001-9446-0582
dc.authorid0000-0001-6783-6783
dc.authorid0000-0002-1150-7064
dc.contributor.authorHekimoğlu, Mustafaen_US
dc.contributor.authorSevim, İsmailen_US
dc.contributor.authorAksezer, Sezgin Çağlaren_US
dc.contributor.authorDurmuş, İpeken_US
dc.date.accessioned2019-06-07T21:03:25Z
dc.date.available2019-06-07T21:03:25Z
dc.date.issued2019-09
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.description.abstractIn retail sector, product variety increases faster than shelf spaces of retail stores where goods are presented to consumers. Hence, assortment planning is an important task for sustained financial success of a retailer in a competitive business environment. In this study, we consider the assortment planning problem of a retailer in Turkey. Using empirical point-of-sale data, a demand model is developed and utilized in the optimization model. Due to nonlinear nature of the model and integrality constraint, we find that it is difficult to obtain a solution even for moderately large product sets. We propose a greedy heuristic approach that generates better results than the mixed integer nonlinear programming in a reasonably shorter period of time for medium and large problem sizes. We also proved that our method has a worst-case time complexity of O(n 2 )while other two well-known heuristics’ complexities are O(n 3 )and O(n 4 ). Also numerical experiments reveal that our method has a better performance than the worst-case as it generates better results in a much shorter run-times compared to other methods.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationHekimoğlu, M., Sevim, İ., Aksezer, S. Ç. & Durmuş, İ. (2019). Assortment optimization with log-linear demand: Application at a turkish grocery store. Journal of Retailing and Consumer Services, 50, 199-214. doi:10.1016/j.jretconser.2019.04.007en_US
dc.identifier.doi10.1016/j.jretconser.2019.04.007
dc.identifier.endpage214
dc.identifier.issn0969-6989
dc.identifier.issn1873-1384
dc.identifier.scopus2-s2.0-85065862389
dc.identifier.scopusqualityQ1
dc.identifier.startpage199
dc.identifier.urihttps://hdl.handle.net/11729/1609
dc.identifier.urihttp://dx.doi.org/10.1016/j.jretconser.2019.04.007
dc.identifier.volume50
dc.identifier.wosWOS:000471928200023
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakSocial Sciences Citation Index (SSCI)en_US
dc.institutionauthorAksezer, Sezgin Çağlaren_US
dc.institutionauthorDurmuş, İpeken_US
dc.institutionauthorid0000-0002-1150-7064
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofJournal of Retailing and Consumer Servicesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectOptimal-Algorithmsen_US
dc.subjectGenetic algorithmen_US
dc.subjectRetail assortmenten_US
dc.subjectModelen_US
dc.subjectPriceen_US
dc.subjectSubstitutionen_US
dc.subjectMethodologyen_US
dc.subjectProductsen_US
dc.titleAssortment optimization with log-linear demand: application at a Turkish grocery storeen_US
dc.typeArticleen_US
dspace.entity.typePublication

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