Author:
Nahhas Abdulrahman,Kharitonov Andrey,Turowski Klaus
Reference30 articles.
1. Alves, J.C., Mateus, G.R., 2020. Deep reinforcement learning and optimization approach for multi-echelon supply chain with uncertain demands, in: Lalla-Ruiz, E., Mes, M., Voss, S. (Eds.), Computational Logistics. Springer, Cham, volume 12433 of Lecture Notes in Computer Science, pp. 584-599.
2. Deep reinforcement learning approach towards a smart parking architecture;Awaisi,2022
3. Deep reinforcement learning for inventory control: A roadmap;Boute;European Journal of Operational Research,2022
4. Solving the online batching problem using deep reinforcement learning;Cals;Computers & Industrial Engineering,2021
5. Deep reinforcement learning of map-based obstacle avoidance for mobile robot navigation;Chen;SN Computer Science,2021