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dc.creatorCastro-Zuluaga, Carlos A.
dc.creatorBotero-Escobar, Sara C.
dc.date.available2015-02-20T16:10:23Z
dc.date.issued2014-05-09
dc.identifier.citationCASTRO-ZULUAGA, Carlos A. BOTERO-ESCOBAR, Sara C, (2014). An approach to make statistical forecasting of products with stationary/seasonal patterns. Proceedings of 25th Annual Production Operations Management Society (POMS) Conference. Atlanta, Ge, USA. May 9– 12th, 2014.spa
dc.identifier.urihttp://hdl.handle.net/10784/5015
dc.descriptionAt any company there are hundreds, maybe thousands of products that must be forecasted with the best accuracy, in order to make a good demand management process, which are required at all planning levels in a company -- Statistical forecasting must be done fast and sometimes there are not enough resources to do it well -- In In this paper we make a proposal of an approach to define the parameter of the exponential smoothing model for products with a behavior pattern stationary or seasonal/stationary in the historical data, to obtain “good forecasting" A numerical example is used to show the effectiveness of the proposed method
dc.language.isoengeng
dc.publisherProduction and Operations Management Society (POMS)spa
dc.relation.ispartofProceedings of 25th Annual Production Operations Management Society (POMS) Conference, May. 2014spa
dc.relation.isversionofhttp://www.pomsmeetings.org/ConfProceedings/051/FullPapers/final_full_paper.htmspa
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.titleAn approach to make statistical forecasting of products with stationary/seasonal patternsspa
dc.typeconferenceObjecteng
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.rights.accessRightsrestrictedAccessspa
dc.publisher.programGrupo de Investigación Gestión de Producción y Logísticaspa
dc.publisher.departmentEscuela de Ingenieríaspa
dc.type.spaDocumento de conferenciaspa
dc.subject.keywordForecastingspa
dc.subject.keywordExponential Smoothingspa
dc.subject.keywordStationaryspa
dc.subject.keywordSeasonalspa
dc.rights.accesoAcceso cerradospa
dc.date.accessioned2015-02-20T16:10:23Z
dc.type.hasVersionpublishedVersionspa
dc.contributor.departmentUniversidad EAFIT. Grupo de Investigación Gestión de Producción y Logística
dc.contributor.eafitauthorccastro@eafit.edu.cospa
dc.contributor.eafitauthorsboter11@eafit.edu.cospa
dc.tipo.versionObra publicadaspa


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