An Intelligent DDMRP Model using Machine Learning techniques

In this paper is proposed a hybrid algorithm for the inventory management. Our proposal is based on the DBPM (Demand-Driven Manufacturing Resources Planning) model and machine learning techniques, in order to determine when and how much to purchase a product. The DBPM model optimize the inventory using predictive models to determine the product demands, and the behavior of the providers. With these predictions, our DBPM model can determine when and how much to purchase to keep an inventory in the levels defined by the users. The preliminary results are very encouraged because in comparison with previous works the inventory follows the optimal levels by products.

Keywords: Inventory Management, Demand-Driven Manufacturing Resources Planning model, Machine Learning, Supply Chain

Aguilar, Jose
Dos Santos, Ricardo
Rodrigo, Garcia
Gomez, Carlos
Jerez, Marxjhony
Jimenez, Marvin
Puerto, Eduard

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