VGU RESEARCH REPOSITORY
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https://epub.vgu.edu.vn/handle/dlibvgu/2115| Title: | Implementation of artificial neural network for demand disaggregation to enhance demand forecasting performance in FMCG industry | Authors: | Tran Quang Linh | Keywords: | Artificial Neural Networks (ANN);Supply chain planning;Time-series forecasting;Demand disaggregation | Issue Date: | 2024 | Abstract: | Accurate demand forecasting is essential for supply chain efficiency, particularly in the fast-moving consumer goods (FMCG) industry, where product availability directly influences customer purchase decisions. While traditional time-series forecasting focuses on predicting aggregated demand, disaggregating forecasts to finer time horizons is crucial for tactical planning, production scheduling, and inventory management. This thesis develops a demand forecasting architecture that leverages Artificial Neural Networks (ANNs) to enhance the accuracy of demand disaggregation from higher-level forecasts (monthly/yearly) to lower-level horizons (weekly). The research includes a review of current demand planning practices and the application of deep learning in supply chain contexts, the development of an ANN-based disaggregation model, and an evaluation of its integration into production and supply chain information systems. Furthermore, the study discusses production strategies that align with the ANN-based architecture. The proposed approach aims to improve operational efficiency, reduce stock-outs, and increase supply chain reliability by optimizing forecast granularity. |
URI(1): | https://epub.vgu.edu.vn/handle/dlibvgu/2115 | Rights: | https://creativecommons.org/licenses/by-nc/4.0/ |
| Appears in Collections: | Global Production Engineering & Management (GPEM) |
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| File | Description | Size | Format | Existing users please Login |
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| Implementation of artificial neural network for demand disaggregation to enhance demand forecasting performance in FMCG industry.pdf | 1.86 MB | Adobe PDF |
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