Abstract
The accurate understanding of future demand in a supply chain is certainly a crucial key to enhance the commercial competitiveness. Indeed, for any member of the supply chain system, a clear vision regarding the future demand affects its planning, performance, and profit. However, supply chains usually suffer from issues of coordination between its members and the uncertain character of customer’s demand. To solve these two problems, this paper examines the combination of two concepts: neural networks and multi-agent systems in order to model information sharing as a coordination mechanism in supply chain and to implement a daily demand-predicting tool. The proposed approach resulted in an MSE of 0.002 in the training set and 0.0086 in the test set, and is used on a real dataset provided by a supermarket in Morocco.
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Bousqaoui, H., Slimani, I., Achchab, S. (2018). Information Sharing as a Coordination Tool in Supply Chain Using Multi-agent System and Neural Networks. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 745. Springer, Cham. https://doi.org/10.1007/978-3-319-77703-0_62
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DOI: https://doi.org/10.1007/978-3-319-77703-0_62
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