Proposed of a grey system for return WEEE product quantity forecasting in reverse logistics network

dc.authorid0000-0002-8098-3611en_US
dc.contributor.authorAyvaz, Berk
dc.contributor.authorBoltürk, Eda
dc.contributor.authorKaçtıoğlu, Sibkat
dc.date.accessioned2019-08-09T08:56:57Z
dc.date.available2019-08-09T08:56:57Z
dc.date.issued2014en_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractReverse Logistics (RL) has gained much attention in recent years due to economic, social and governmental reasons. For firms, it has become essential to manage the reverse flow of materials in an efficient way to gain competitive advantage. One important aspect of RL is to provide a correct and timely estimation of return waste product quantity. Improved forecast accuracy leads to a better decision making in strategic, tactic and operational areas of an organization. Intrinsic and extrinsic forecasting are some of the well-known and frequently used forecasting techniques to predict return product in RL networks. In this study, we presented a grey forecasting system to predict return waste product quantity in RL network. To the best of our knowledge, this study is the first in return product forecasting literature by using grey system to predict return quantity. Solutions showed that grey forecasting system is very efficient to predict return quantity.en_US
dc.identifier.endpage81en_US
dc.identifier.startpage72en_US
dc.identifier.urihttps://hdl.handle.net/11467/2863
dc.language.isoenen_US
dc.publisherETMen_US
dc.relation.ispartofProceedings of the Global Conference on Engineering and Technology Managementen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectReverse Logisticsen_US
dc.subjectUncertaintiyen_US
dc.subjectGrey Systemsen_US
dc.subjectReturn Product Forecastingen_US
dc.subjectE-Wasteen_US
dc.titleProposed of a grey system for return WEEE product quantity forecasting in reverse logistics networken_US
dc.typeConference Objecten_US

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