A smart DDMRP model using machine learning techniques

被引：1

作者：

Aguilar, Jose ^{[1
,2
]}

Guillen, Ricardo Jose Dos Santos ^{[1
]}

Garcia, Rodrigo ^{[2
,3
]}

Gomez, Carlos ^{[4
]}

Jerez, M. ^{[1
]}

Narvaez, Marvin Luis Jimenez ^{[3
]}

Puerto, Eduard ^{[5
]}

机构：

[1] Univ Los Andes, CEMISID Fac Ingn, Merida, Venezuela

[2] Univ EAFIT, GIDITIC, Medellin, Colombia

[3] Univ Sinu, Fac Ciencias Ingn, Monteria, Colombia

[4] EXEK Co, Medellin, Colombia

[5] Univ Francisco Paula Santander, Grp GIA, Cucuta, Colombia

来源：

INTERNATIONAL JOURNAL OF VALUE CHAIN MANAGEMENT | 2023年 / 14卷 / 02期

关键词：

inventory management; demand-driven model; machine learning; supply chain; DDMRP; INVENTORY MANAGEMENT; DEMAND; TIME;

D O I：

10.1504/IJVCM.2023.130973

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

This paper proposes a hybrid algorithm based on the demand-driven manufacturing resources planning (DDMRP) model and machine learning techniques to determine when and how much to purchase a product. The DDMRP model optimises the inventory using predictive models to determine the product demands, and the behaviour of the providers. Then, our DDMRP model determines when and how much to purchase. Thus, our approach defines a smart inventory management to establish what should be purchased and when. The preliminary results are very encouraging because the inventory follows the optimal levels by product based on demand, avoiding a lack of inventory.

引用

页码：107 / 142

页数：37

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