AN APPROACH BASED ON MACHINE LEARNING AND DISCRETE EVENT SIMULATION FOR SUPPLY CHAIN OPTIMIZATION: THE CASE OF ON-STOCK CHAINS

Authors

  • Zineb Nafi LISA Laboratory, National School of Applied Sciences of Marrakech, Cadi Ayyad University, Avenue Abdelkrim Khattabi, Marrakech 40000, Morocco
  • Fatima Ezzahra Essaber LISA Laboratory, National School of Applied Sciences of Marrakech, Cadi Ayyad University, Avenue Abdelkrim Khattabi, Marrakech 40000, Morocco
  • Fatine Elharouni LISA Laboratory, National School of Applied Sciences of Marrakech, Cadi Ayyad University, Avenue Abdelkrim Khattabi, Marrakech 40000, Morocco
  • Benmoussa Rachid LISA Laboratory, National School of Applied Sciences of Marrakech, Cadi Ayyad University, Avenue Abdelkrim Khattabi, Marrakech 40000, Morocco

DOI:

https://doi.org/10.23055/ijietap.2023.30.6.8613

Keywords:

Supply chain (SC), Machine learning, Mathematical Models, Optimization., Discrete-Event Simulation

Abstract

The complexity of supply chain problems, more specifically the case of on-stock chains, is due to performance indicators variety, antagonism, and the difficulty of understanding the effects and interactions of different performance drivers with regard to these indicators. As mathematical formalization is essential to optimize the performance of these chains, this paper generally aims to study the contribution of Machine Learning to mathematically link the evaluation parameters of an on-stock supply chain to its action parameters. This work is based on an academic case study that seeks to mathematically formalize the problem of delivery delay in an on-stock supply chain. To this end, several Machine Learning algorithms have been tested and compared. This experience highlighted the impossibility of obtaining a labeled dataset through data collection from the real system. It thus demonstrates the necessity to use a simulation system, in particular, discrete event simulation, to generate this dataset.

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Published

2023-12-24

How to Cite

Nafi, Z., Essaber, F. E., Elharouni, F., & Rachid , B. (2023). AN APPROACH BASED ON MACHINE LEARNING AND DISCRETE EVENT SIMULATION FOR SUPPLY CHAIN OPTIMIZATION: THE CASE OF ON-STOCK CHAINS. International Journal of Industrial Engineering: Theory, Applications and Practice, 30(6). https://doi.org/10.23055/ijietap.2023.30.6.8613

Issue

Vol. 30 No. 6 (2023)

Section

Supply Chain Management

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