Show simple item record

dc.contributor.authorHekimoğlu, Mustafatr_TR
dc.contributor.authorSevim, İsmailtr_TR
dc.contributor.authorAksezer, Çağlar Sezgintr_TR
dc.contributor.authorDurmuş, İpektr_TR
dc.contributor.otherIşık Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.date.accessioned2019-06-07T21:03:25Z
dc.date.available2019-06-07T21:03:25Z
dc.date.issued2019-09
dc.identifier.citationHekimoğlu, M., Sevim, I., Aksezer, 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.issn0969-6989
dc.identifier.otherWOS:000471928200023
dc.identifier.urihttp://dx.doi.org/10.1016/j.jretconser.2019.04.007
dc.identifier.urihttp://hdl.handle.net/11729/1609
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.language.isoengen_US
dc.publisherElsevier Ltden_US
dc.relation.isversionof10.1016/j.jretconser.2019.04.007
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.sourceJournal of Retailing and Consumer Servicesen_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
dc.contributor.departmentIşık Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.contributor.authorID256992
dc.contributor.authorID226849
dc.contributor.authorID31904
dc.identifier.volume50
dc.identifier.startpage199
dc.identifier.endpage214


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record