Demand forecasting tool for inventory control smart systems

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dc.contributor.authorBenhamida, Fatima Zohra
dc.contributor.authorKaddouri, Ouahiba
dc.contributor.authorOuhrouche, Tahar
dc.contributor.authorBenaichouche, Mohammed
dc.contributor.authorCasado Mansilla, Diego
dc.contributor.authorLópez de Ipiña González de Artaza, Diego
dc.date.accessioned2025-09-04T10:10:48Z
dc.date.available2025-09-04T10:10:48Z
dc.date.issued2021-06-09
dc.date.updated2025-09-04T10:10:48Z
dc.description.abstractWith the availability of data and the increasing capabilities of data processing tools, many businesses are leveraging historical sales and demand data to implement smart inventory management systems. Demand forecasting is the process of estimating the consumption of products or services for future time periods. It plays an important role in the field of inventory control and Supply Chain, since it enables production and supply planning and therefore can reduce delivery times and optimize Supply Chain decisions. This paper presents an extensive literature review about demand forecasting methods for time-series data. Based on analysis results and findings, a new demand forecasting tool for inventory control is proposed. First, a forecasting pipeline is designed to allow selecting the most accurate demand forecasting method. The validation of the proposed solution is executed on Stock&Buy case study, a growing online retail platform. For this reason, two new methods are proposed: (1) a hybrid method, Comb-TSB, is proposed for intermittent and lumpy demand patterns. CombTSB automatically selects the most accurate model among a set of methods. (2) a clustering-based approach (ClustAvg) is proposed to forecast demand for new products which have very few or no sales history data. The evaluation process showed that the proposed tool achieves good forecasting accuracy by making the most appropriate choice while defining the forecasting method to apply for each product selection.en
dc.identifier.citationBenhamida, F. Z., Kaddouri, O., Ouhrouche, T., Benaichouche, M., Casado-Mansilla, D., & López-De-Ipiña, D. (2021). Demand forecasting tool for inventory control smart systems. Journal of Communications Software and Systems, 17(2), 185-196. https://doi.org/10.24138/JCOMSS-2021-0068
dc.identifier.doi10.24138/JCOMSS-2021-0068
dc.identifier.eissn1846-6079
dc.identifier.issn1845-6421
dc.identifier.urihttps://hdl.handle.net/20.500.14454/3498
dc.language.isoeng
dc.publisherCroatian Communications and Information Society
dc.subject.otherDemand Forecasting
dc.subject.otherIntermittent-Demand Forecasting
dc.subject.otherMachine Learning
dc.subject.otherSmart Systems
dc.subject.otherStatistical Forecasting
dc.subject.otherTime-Series Data
dc.titleDemand forecasting tool for inventory control smart systemsen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.endPage196
oaire.citation.issue2
oaire.citation.startPage185
oaire.citation.titleJournal of Communications Software and Systems
oaire.citation.volume17
oaire.licenseConditionhttps://creativecommons.org/licenses/by-nc/4.0/
oaire.versionVoR
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