Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in …
J Gijsbrechts, RN Boute, JA Van Mieghem… - … & Service Operations …, 2022 - ideas.repec.org
Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in …
J Gijsbrechts, RN Boute, JA Van Mieghem… - Manufacturing & Service …, 2022 - dl.acm.org
Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in …
Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in …
J Gijsbrechts, RN Boute, JA Mieghem… - … and Service Operations …, 2022 - repositorio.ucp.pt
Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in …
J Gijsbrechts, RN Boute, JA Van Mieghem… - … & Service Operations …, 2022 - merit.url.edu
Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in …
J Gijsbrechts, RN Boute, JA Van Mieghem… - … & Service Operations …, 2021 - papers.ssrn.com
Results: We demonstrate that the A3C algorithm can match performance of state-of-the-art heuristics and other approximate dynamic programming methods. While the initial tuning …