A Strategic Inventory Management Model base on Deep Learning

Subject Areas :

Hamidreza Hajali ¹ , Mohammad Ali Afshar Kazemi ^{2 *} , Adel Azar ³ , Abbas Toloie Eshlaghy ⁴ , Reza Radfar ⁵

1 - PhD Candidate Faculty of Industrial Management, Science and Research Branch, Islamic Azad University
2 -
3 - Tarbiat modares university
4 - Faculty of Management, Science and Research Branch, Islamic Azad University
5 - Faculty of Management, Science and Research Branch, Islamic Azad University

Received: 2024-11-06 Accepted : 2025-03-12 Published : 2025-03-12

Keywords: Inventory control, big data, artificial intelligence, deep learning, supply chain,

Abstract :

Inventory management as a live subset of whole organization would be organize the expectation of supply chain base on an intelligent platform. This article was created with the aim of facing the challenges of industrial big data on data which are effective in decision-making based on historical records, but are not linear data due to the valuable content they have.

As consequence, it is obvious that are not exploited by traditional methods such as time series for forecasting and decision-making. Accordingly, in this article, to present a strategic model based on artificial intelligence techniques, long short-Term Memory (LSTM), while we discussed the use of industrial big data, which enables the ability to use non-linear data to predict orders. Moreover, the methods of economic order quantity (EOQ) and economic production quantity model (EPQ) in order to prepare and training data have been used. In continue for getting better processing in order to identify strengths and weaknesses in inventory management, "ABC" analysis has also been used. The findings show that the integration of the traditional approach with deep learning method improves learning performance for complex big data analysis tasks. Many evaluations of the proposed deep network have reached an acceptable error value. Finally, this model has provided promising results for predicting expectation of fields that related to controlling amount of production based on objective in inventory management sector.

References:



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