Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/70503

TítuloDemand forecasting: a case study in the food industry
Autor(es)Silva, Juliana C.
Figueiredo, Manuel
Braga, A. C.
Palavras-chaveARIMA
Combining forecasts
Exponential smoothing
Forecasting demand
Data2019
EditoraSpringer Verlag
RevistaLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
CitaçãoSilva J.C., Figueiredo M.C., Braga A.C. (2019) Demand Forecasting: A Case Study in the Food Industry. In: Misra S. et al. (eds) Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science, vol 11621. Springer, Cham. https://doi.org/10.1007/978-3-030-24302-9_5
Resumo(s)The use of forecasting methods is nowadays regarded as a business ally since it supports both the operational and the strategic decision-making processes. This paper is based on a research project aiming the development of demand forecasting models for a company (designated here by PR) that operates in the food business, more specifically in the delicatessen segment. In particular, we focused on demand forecasting models that can serve as a tool to support production planning and inventory management at the company. The analysis of the company’s operations led to the development of a new demand forecasting tool based on a combination of forecasts, which is now being used and tested by the company.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/70503
ISBN9783030243012
DOI10.1007/978-3-030-24302-9_5
ISSN0302-9743
Versão da editorahttps://link.springer.com/chapter/10.1007%2F978-3-030-24302-9_5
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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