Deep reinforcement learning for inventory control: A roadmap

Citations

Cited by:

1. Koen W. de Bock & Kristof Coussement & Arno De Caigny & Roman Slowiński & Bart Baesens & Robert N Boute & Tsan-Ming Choi & Dursun Delen & Mathias Kraus & Stefan Lessmann & Sebastián Maldonado & David , 2023. "Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda," Post-Print hal-04219546, HAL.
2. Pavithra Harsha & Ashish Jagmohan & Jayant Kalagnanam & Brian Quanz & Divya Singhvi, 2025. "Deep Policy Iteration with Integer Programming for Inventory Management," Manufacturing & Service Operations Management, INFORMS, vol. 27(2), pages 369-388, March.
3. Alp Muharremoglu & Nan Yang & Xin Geng, 2024. "Single-Product Assemble-to-Order Systems with Exogenous Lead Times," Operations Research, INFORMS, vol. 72(3), pages 916-939, May.
4. Yen, Benjamin P.-C. & Luo, Yu, 2023. "Navigational guidance – A deep learning approach," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1179-1191.
5. Michal Koren & Or Peretz, 2026. "Dynamic colour dynamics: markov decision processes for fashion inventory management," Annals of Operations Research, Springer, vol. 358(3), pages 1329-1359, March.
6. Dehaybe, Henri & Catanzaro, Daniele & Chevalier, Philippe, 2024. "Deep Reinforcement Learning for inventory optimization with non-stationary uncertain demand," European Journal of Operational Research, Elsevier, vol. 314(2), pages 433-445.
   • Dehaybe, Henri & Catanzaro, Daniele & Chevalier, Philippe, 2023. "Deep Reinforcement Learning for Inventory Optimization with Non-Stationary Uncertain Demand," LIDAM Reprints CORE 3270, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
7. Yu-Xin Tian & Chuan Zhang, 2025. "A multimodal deep reinforcement learning framework for multi-period inventory decision-making under demand uncertainty," Fuzzy Optimization and Decision Making, Springer, vol. 24(4), pages 723-750, December.
8. Ewelina Chołodowicz & Przemysław Orłowski, 2024. "Neural Network Control of Perishable Inventory with Fixed Shelf Life Products and Fuzzy Order Refinement under Time-Varying Uncertain Demand," Energies, MDPI, vol. 17(4), pages 1-22, February.
9. Fleuren, Tijn, 2025. "Stochastic approaches for production-inventory planning : Applications to high-tech supply chains," Other publications TiSEM 1fe1bbe5-fd90-4077-8606-d, Tilburg University, School of Economics and Management.
10. Juan Camilo Gutierrez & Sonia Isabel Polo Triana & Juan Sebastian León Becerra, 2025. "Benefits, challenges, and limitations of inventory control using machine learning algorithms: literature review," OPSEARCH, Springer;Operational Research Society of India, vol. 62(3), pages 1140-1172, September.
11. Lotte Hezewijk & Nico P. Dellaert & Willem L. Jaarsveld, 2025. "On non-negative auto-correlated integer demand processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 101(2), pages 135-161, April.
12. Seyed Ashkan Hosseini Shekarabi & Reza Kiani Mavi & Flavio Romero Macau, 2025. "Supply Chain Resilience: A Critical Review of Risk Mitigation, Robust Optimisation, and Technological Solutions and Future Research Directions," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 26(3), pages 681-735, September.
13. Cui, Geng & Imura, Naoto & Nishinari, Katsuhiro & Ezaki, Takahiro, 2025. "On order smoothing interpolating the order-up-to and constant order policies," Omega, Elsevier, vol. 136(C).
14. Verleijsdonk, Peter & van Jaarsveld, Willem & Kapodistria, Stella, 2024. "Scalable policies for the dynamic traveling multi-maintainer problem with alerts," European Journal of Operational Research, Elsevier, vol. 319(1), pages 121-134.
15. Haotian Zhang & Stuart Dereck Semujju & Zhicheng Wang & Xianwei Lv & Kang Xu & Liang Wu & Ye Jia & Jing Wu & Wensheng Liang & Ruiyan Zhuang & Zhuo Long & Ruijun Ma & Xiaoguang Ma, 2026. "Large scale foundation models for intelligent manufacturing applications: a survey," Journal of Intelligent Manufacturing, Springer, vol. 37(1), pages 119-170, January.
16. De Munck, Thomas & Tancrez, Jean-Sébastien & Chevalier, Philippe, 2025. "Transfer Reinforcement Learning for Pricing, Driver Repositioning and Customer Admission in Ride-Hailing Networks," LIDAM Discussion Papers CORE 2025004, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
17. Goedhart, Joost & Haijema, René & Akkerman, Renzo, 2023. "Modelling the influence of returns for an omni-channel retailer," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1248-1263.
18. Ralfs, Jana & Pham, Dai T. & Kiesmüller, Gudrun P., 2025. "Optimal outbound shipment policy for an inventory system with advance demand information," European Journal of Operational Research, Elsevier, vol. 324(1), pages 92-103.
19. Wang, Zihao & Wang, Wenlong & Liu, Tianjun & Chang, Jasmine & Shi, Jim, 2025. "IoT-driven dynamic replenishment of fresh produce in the presence of seasonal variations: A deep reinforcement learning approach using reward shaping," Omega, Elsevier, vol. 134(C).
20. Hu, Junkai & Xia, Li & Huang, Teng & Wu, Haoran, 2025. "A multi-agent deep reinforcement learning approach for multi-echelon inventory optimization and its application to the beer game," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 203(C).
21. Bootaki, Behrang & Zhang, Guoqing, 2024. "A location-production-routing problem for distributed manufacturing platforms: A neural genetic algorithm solution methodology," International Journal of Production Economics, Elsevier, vol. 275(C).
22. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.
23. Mansur M. Arief, 2026. "Deepbullwhip: An Open-Source Simulation and Benchmarking for Multi-Echelon Bullwhip Analyses," Papers 2604.13478, arXiv.org.
24. Temizöz, Tarkan & Imdahl, Christina & Dijkman, Remco & Lamghari-Idrissi, Douniel & van Jaarsveld, Willem, 2025. "Deep Controlled Learning for Inventory Control," European Journal of Operational Research, Elsevier, vol. 324(1), pages 104-117.
25. Pahr, Alexander & Grunow, Martin & Amorim, Pedro, 2025. "Learning from the aggregated optimum: Managing port wine inventory in the face of climate risks," European Journal of Operational Research, Elsevier, vol. 323(2), pages 671-685.
26. Akkerman, Fabian & Prak, Dennis & Mes, Martijn, 2025. "Dynamic reordering and inspection for the multi-item Inventory Record Inaccuracy problem," European Journal of Operational Research, Elsevier, vol. 321(2), pages 428-444.