Improving the efficiency of food supplies for a trading company based on an artificial neural network

Kassekeyeva Aislu Bisenovna, Sadvakassov Arman Ashatuly, Lamasheva Zhanar Beibutovna, Kerimkhulle Seyit Yesilbayuly, Abdrakhmanova Alfiya Zagievna, Makpal Zhartybayeva Galymbekovna, Oralkhanov Berdibek Oralkhanuly


This article presents the proper organization of the supply chain to meet consumer demand, which is crucial for modern commercial enterprises involved in the sale of various products. Studies indicate that a company's success is linked to the satisfaction of its customers. To optimize the supply chain, this study will consider the use of artificial neural network models. The results of this model will seek a balance between demand and supply, helping determine the necessary quantity of goods to satisfy demand and prevent overproduction. By using this model, the company can fully meet the needs of its customers. Additionally, the company saves its resources and labor costs and reallocates them to other tasks. The model demonstrates the optimization of production and supply business processes, as well as an increase in efficiency.


Artificial neural networks; Automated systems; Supply chain management; Trading network; Trading system

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).