Forecasting Intermittent Demand by Hyperbolic-Exponential Smoothing

dc.contributor.author Prestwich, S. D.
dc.contributor.author Tarim, S. A.
dc.contributor.author Rossi, R.
dc.contributor.author Hnich, B.
dc.date.accessioned 2023-06-16T12:59:32Z
dc.date.available 2023-06-16T12:59:32Z
dc.date.issued 2014
dc.description.abstract Croston's method is generally viewed as being superior to exponential smoothing when the demand is intermittent, but it has the drawbacks of bias and an inability to deal with obsolescence, where the demand for an item ceases altogether. Several variants have been reported, some of which are unbiased on certain types of demand, but only one recent variant addresses the problem of obsolescence. We describe a new hybrid of Croston's method and Bayesian inference called Hyperbolic-Exponential Smoothing, which is unbiased on non-intermittent and stochastic intermittent demand, decays hyperbolically when obsolescence occurs, and performs well in experiments. (C) 2014 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved. en_US
dc.identifier.doi 10.1016/j.ijforecast.2014.01.006
dc.identifier.issn 0169-2070
dc.identifier.issn 1872-8200
dc.identifier.scopus 2-s2.0-84904700448
dc.identifier.uri https://doi.org/10.1016/j.ijforecast.2014.01.006
dc.identifier.uri https://hdl.handle.net/20.500.14365/1241
dc.language.iso en en_US
dc.publisher Elsevier Science Bv en_US
dc.relation.ispartof Internatıonal Journal of Forecastıng en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Intermittent demand en_US
dc.subject Croston's method en_US
dc.subject Bayesian inference en_US
dc.subject Modified Croston Procedure en_US
dc.subject Accuracy en_US
dc.title Forecasting Intermittent Demand by Hyperbolic-Exponential Smoothing en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Rossi, Roberto/0000-0001-7247-1010
gdc.author.id Tarim, S. Armagan/0000-0001-5601-3968
gdc.author.id Hnich, Brahim/0000-0001-8875-8390
gdc.author.id Prestwich, Steven/0000-0002-6218-9158
gdc.author.scopusid 7004234709
gdc.author.scopusid 6506794189
gdc.author.scopusid 35563636800
gdc.author.scopusid 6602458958
gdc.author.wosid Rossi, Roberto/B-4397-2010
gdc.author.wosid Tarim, S. Armagan/B-4414-2010
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gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::journal::journal article
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gdc.description.department İzmir Ekonomi Üniversitesi en_US
gdc.description.departmenttemp [Prestwich, S. D.] Natl Univ Ireland Univ Coll Cork, Insight Ctr Data Analyt, Cork, Ireland; [Tarim, S. A.] Hacettepe Univ, Inst Populat Studies, Ankara, Turkey; [Rossi, R.] Univ Edinburgh, Sch Business, Edinburgh, Midlothian, Scotland; [Hnich, B.] Izmir Univ Econ, Dept Comp Engn, Izmir, Turkey en_US
gdc.description.endpage 933 en_US
gdc.description.issue 4 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 928 en_US
gdc.description.volume 30 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W2010074812
gdc.identifier.wos WOS:000345060200006
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gdc.oaire.keywords FOS: Computer and information sciences
gdc.oaire.keywords Computer Science - Other Computer Science
gdc.oaire.keywords Other Computer Science (cs.OH)
gdc.oaire.keywords Bayesian inference
gdc.oaire.keywords Croston’s method
gdc.oaire.keywords Intermittent demand
gdc.oaire.popularity 1.4892025E-8
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gdc.oaire.sciencefields 0502 economics and business
gdc.oaire.sciencefields 05 social sciences
gdc.oaire.sciencefields 0211 other engineering and technologies
gdc.oaire.sciencefields 02 engineering and technology
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gdc.opencitations.count 26
gdc.plumx.crossrefcites 6
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