文章基本信息

标题：Control-oriented modeling of SKU-level demand in retail food market
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作者：M. Mazzoleni ; S. Formentin ; F. Previdi 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：13003-13008
DOI：10.1016/j.ifacol.2017.08.1951
语种：English
出版社：Elsevier
摘要：AbstractIn food market, modeling the dynamics of Stock-Keeping Unit (SKU) requests is of fundamental importance, not only to understand the market but also for optimization and control purposes. In fact, standing on model-based predictions of future demand, an efficient planning of the promotional calendar can be devised. Moreover, better inventory management can be achieved, by reducing losses due to expired aliments remained unsold and improving distribution operations. In this work, data-driven control-oriented modeling of such a demand is discussed and a novel switching dynamical strategy is proposed. When applied to experimental data from a real food company, the above strategy is shown to accurately predict future sales under fixed promotion events and outperform the state-of-the-art modeling methods.
关键词：KeywordsKnowledge discover (data mining)Identificationmodel reductionProduction planningcontrol