IDEAS home Printed from https://ideas.repec.org/r/eee/proeco/v78y2002i2p153-161.html

Inventory management in supply chains: a reinforcement learning approach

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Jung, Seung Hwan & Yang, Yunsi, 2023. "On the value of operational flexibility in the trailer shipment and assignment problem: Data-driven approaches and reinforcement learning," International Journal of Production Economics, Elsevier, vol. 264(C).
  2. Saxena, Neha & Sarkar, Biswajit, 2023. "How does the retailing industry decide the best replenishment strategy by utilizing technological support through blockchain?," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
  3. Joren Gijsbrechts & Robert N. Boute & Jan A. Van Mieghem & Dennis J. Zhang, 2022. "Can Deep Reinforcement Learning Improve Inventory Management? Performance on Lost Sales, Dual-Sourcing, and Multi-Echelon Problems," Manufacturing & Service Operations Management, INFORMS, vol. 24(3), pages 1349-1368, May.
  4. 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.
  5. Deniz Preil & Michael Krapp, 2022. "Artificial intelligence-based inventory management: a Monte Carlo tree search approach," Annals of Operations Research, Springer, vol. 308(1), pages 415-439, January.
  6. Fotuhi, Fateme & Huynh, Nathan & Vidal, Jose M. & Xie, Yuanchang, 2013. "Modeling yard crane operators as reinforcement learning agents," Research in Transportation Economics, Elsevier, vol. 42(1), pages 3-12.
  7. Kevin Geevers & Lotte Hezewijk & Martijn R. K. Mes, 2024. "Multi-echelon inventory optimization using deep reinforcement learning," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(3), pages 653-683, September.
  8. Park, Hyungjun & Choi, Dong Gu & Min, Daiki, 2023. "Adaptive inventory replenishment using structured reinforcement learning by exploiting a policy structure," International Journal of Production Economics, Elsevier, vol. 266(C).
  9. Bergsma, Ritsaart & de Ruijt, Corné & Bhulai, Sandjai, 2025. "A systematic review of machine learning approaches in inventory control optimization," Operations Research Perspectives, Elsevier, vol. 15(C).
  10. Alexander Kastius & Rainer Schlosser, 2022. "Dynamic pricing under competition using reinforcement learning," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 50-63, February.
  11. Jibang Wu & Zixuan Zhang & Zhe Feng & Zhaoran Wang & Zhuoran Yang & Michael I. Jordan & Haifeng Xu, 2022. "Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning," Papers 2202.10678, arXiv.org.
  12. Albino, Vito & Carbonara, Nunzia & Giannoccaro, Ilaria, 2007. "Supply chain cooperation in industrial districts: A simulation analysis," European Journal of Operational Research, Elsevier, vol. 177(1), pages 261-280, February.
  13. Schett, Georg & Ehrig, Claudia & Schwendinger, Benjamin & Neumann, Ursula & Beck, Nico & Stadler, Florian & Ansari, Fazel, 2026. "Integrated demand forecasting and reinforcement learning for order point optimization in inventory planning," International Journal of Production Economics, Elsevier, vol. 299(C).
  14. Abhijit Gosavi & Vy K. Le, 2024. "Maintenance optimization in a digital twin for Industry 4.0," Annals of Operations Research, Springer, vol. 340(1), pages 245-269, September.
  15. Michele Compare & Luca Bellani & Enrico Cobelli & Enrico Zio & Francesco Annunziata & Fausto Carlevaro & Marzia Sepe, 2020. "A reinforcement learning approach to optimal part flow management for gas turbine maintenance," Journal of Risk and Reliability, , vol. 234(1), pages 52-62, February.
  16. Bellantuono, Nicola & Giannoccaro, Ilaria & Pontrandolfo, Pierpaolo & Tang, Christopher S., 2009. "The implications of joint adoption of revenue sharing and advance booking discount programs," International Journal of Production Economics, Elsevier, vol. 121(2), pages 383-394, October.
  17. Carlos Cuartas & Jose Aguilar, 2023. "Hybrid algorithm based on reinforcement learning for smart inventory management," Journal of Intelligent Manufacturing, Springer, vol. 34(1), pages 123-149, January.
  18. de Vries, Jan, 2013. "The influence of power and interest on designing inventory management systems," International Journal of Production Economics, Elsevier, vol. 143(2), pages 233-241.
  19. Afshin Oroojlooyjadid & MohammadReza Nazari & Lawrence V. Snyder & Martin Takáč, 2022. "A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization," Manufacturing & Service Operations Management, INFORMS, vol. 24(1), pages 285-304, January.
  20. Yan, Yimo & Chow, Andy H.F. & Ho, Chin Pang & Kuo, Yong-Hong & Wu, Qihao & Ying, Chengshuo, 2022. "Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 162(C).
  21. Rebecca S. Widrick & Sarah G. Nurre & Matthew J. Robbins, 2018. "Optimal Policies for the Management of an Electric Vehicle Battery Swap Station," Transportation Science, INFORMS, vol. 52(1), pages 59-79, January.
  22. Rachman, Rifny & Tingey, Josh & Allmendinger, Richard & Shukla, Pradyumn & Pan, Wei, 2026. "Reinforcement learning for multi-objective multi-echelon supply chain optimisation," European Journal of Operational Research, Elsevier, vol. 334(3), pages 942-962.
  23. Lange, Fabian & Schlosser, Rainer, 2025. "Dynamic pricing with waiting and price-anticipating customers," Operations Research Perspectives, Elsevier, vol. 14(C).
  24. Monthatipkul, Chumpol & Yenradee, Pisal, 2008. "Inventory/distribution control system in a one-warehouse/multi-retailer supply chain," International Journal of Production Economics, Elsevier, vol. 114(1), pages 119-133, July.
  25. Wael Alasfar, 2022. "The Impact of Strategic supplier partnership on Low-cost advantage in the Syrian Food Products Sector," Eximia Journal, Plus Communication Consulting SRL, vol. 5(1), pages 1-13, July.
  26. Tilahun Nigatu Habtemariyam & Chalchissa Amentie Kero, 2022. "The Effect of Supply Chain Management on Competitive Advantage: Mediating Role of Supply Chain Responsiveness in Ethiopian Food Processing Industry," International Journal of Business and Management (IJBM), International Emerging Scholars Society (IESS), New Zealand, vol. 1(1), pages 1-33, July.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.