Benefits, challenges, and limitations of inventory control using machine learning algorithms: literature review
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12597-024-00839-0.pdf
Reference87 articles.
1. Albayrak Ünal, Ö., Erkayman, B., Usanmaz, B.: Applications of artificial intelligence in inventory management: a systematic review of the literature. Arch. Comput. Methods Eng. 30(4), 2605–2625 (2023). https://doi.org/10.1007/s11831-022-09879-5
2. Svoboda, J., Minner, S., Yao, M.: Typology and literature review on multiple supplier inventory control models. Eur. J. Oper. Res. 293(1), 1–23 (2021). https://doi.org/10.1016/j.ejor.2020.11.023
3. Rolf, B., Jackson, I., Müller, M., Lang, S., Reggelin, T., Ivanov, D.: A review on reinforcement learning algorithms and applications in supply chain management. Int. J. Prod. Res. (2022). https://doi.org/10.1080/00207543.2022.2140221
4. Esteso, A., Peidro, D., Mula, J., Díaz-Madroñero, M.: Reinforcement learning applied to production planning and control. Int. J. Prod. Res. 61(16), 5772–5789 (2023). https://doi.org/10.1080/00207543.2022.2104180
5. Jha, K., Doshi, A., Patel, P., Shah, M.: A comprehensive review on automation in agriculture using artificial intelligence. Artif. Intell. Agric. 2, 1–12 (2019). https://doi.org/10.1016/j.aiia.2019.05.004
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