Azzamouri, A., Baptiste, P., Dessevre, G., Pellerin, R., 2021. Demand driven material requirements planning (Ddmrp): A systematic review and classification. Journal of Industrial Engineering and Management, 14(3), 439–456. DOI: 10.3926/jiem.3331
Bahu, B., Bironneau, L., Hovelaque, V., 2019. Compréhension du DDMRP et de son adoption : premiers éléments empiriques. Logistique & Management, 27(1), 20–32. DOI: 10.1080/12507970.2018.1547130
Benavente, D., Peralta, S., Quispe, G., Moguerza, J., Raymundo, C., 2023. The Demand Driven MRP Implementation in Complex Manufacturing Industries: A Systematic Literature Reviews. International Journal of Engineering Trends and Technology, 71(3), 33–45. DOI: 10.14445/22315381/IJETT-V71I3P205
Bennett, N., Lemoine, G. J., 2014. What a difference a word makes: Understanding threats to performance in a VUCA world. Business Horizons, 57(3), 311–317. DOI: 10.1016/j.bushor.2014.01.001
Boute, R. N., Gijsbrechts, J., van Jaarsveld, W., Vanvuchelen, N., 2021. Deep Reinforcement Learning for Inventory Control: A Roadmap. In SSRN Electronic Journal. DOI: 10.2139/ssrn.3861821
Damand, D., Lahrichi, Y., Barth, M., 2022. Parameterisation of demand-driven material requirements planning: a multi-objective genetic algorithm. International Journal of Production Research. DOI: 10.1080/00207543.2022.2098074
Duhem, L., Benali, M., Martin, G., 2023. Parametrization of a demand-driven operating model using reinforcement learning. Computers in Industry, 147(September 2022), 103874. DOI: 10.1016/j.compind.2023.103874
El Marzougui, M., Messaoudi, N., Dachry, W., Bensassi, B., 2022a. Industry 4.0 Technologies on Demand Driven Material Requirement Planning: Theoretical Background and Impacts. 59–69.
El Marzougui, M., Messaoudi, N., Dachry, W., Bensassi, B., 2022b. Integration Model for Demand-Driven Material Requirement Planning and Industry 4.0. SAE International Journal of Materials and Manufacturing, 16(1), 5–16. DOI: 10.4271/05-16-01-0001
El Marzougui, M., Messaoudi, N., Dachry, W., Bensassi, B., 2023. Demand Driven Material Requirement Planning and Industry 4.0 Integration: Conceptual Framework and Hypotheses. International Journal of Engineering Trends and Technology, 71(12), 201–216. DOI: 10.14445/22315381/IJETT-V71I12P220
Esteso, A., Peidro, D., Mula, J., Díaz-Madroñero, M., 2022. Reinforcement learning applied to production planning and control. International Journal of Production Research. DOI: 10.1080/00207543.2022.2104180
Kortabarria, A., Apaolaza, U., Lizarralde, A., Amorrortu, I., 2018. Material Management without Forecasting: From MRP to Demand Driven MRP. Journal of Industrial Engineering and Management, 11(4), 632–650. https://pubmed.ncbi.nlm.nih.gov/34103776/
Lee, C. J., Rim, S. C., 2019. A Mathematical Safety Stock Model for DDMRP Inventory Replenishment. Mathematical Problems in Engineering, 2019. DOI: 10.1155/2019/6496309
Marzougui, M. El, Messaoudi, N., Dachry, W., Sarir, H., Demand, B. B., Mrp, D., 2021. Demand driven mrp : literature review and research issues M El Marzougui, N . Messaoudi, W Dachry, H Sarir, B Bensassi To cite this version : HAL Id : hal-03193163.
Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., Riedmiller, M., 2013. Playing Atari with Deep Reinforcement Learning. 1–9. http://arxiv.org/abs/1312.5602
Mousavi, S. S., Schukat, M., Howley, E., 2018. Deep Reinforcement Learning: An Overview. Lecture Notes in Networks and Systems, 16, 426–440. DOI: 10.1007/978-3-319-56991-8_32
Velasco Acosta, A. P., Mascle, C., Baptiste, P., 2020. Applicability of Demand-Driven MRP in a complex manufacturing environment. International Journal of Production Research, 58(14), 4233–4245. DOI: 10.1080/00207543.2019.1650978