Can Deep Reinforcement Learning Improve Inventory Management? Performance on Lost Sales, Dual-Sourcing, and Multi-Echelon Problems | Zendy

Joren Gijsbrechts | Zendy; Robert Boute | Zendy; Jan A. Van Mieghem | Zendy; Dennis Zhang | Zendy

Open Access

Can Deep Reinforcement Learning Improve Inventory Management? Performance on Lost Sales, Dual-Sourcing, and Multi-Echelon Problems

Author(s) -

Joren Gijsbrechts,

Robert Boute,

Jan A. Van Mieghem,

Dennis Zhang

Publication year - 2022

Publication title -

manufacturing and service operations management

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.372

H-Index - 83

eISSN - 1526-5498

pISSN - 1523-4614

DOI - 10.1287/msom.2021.1064

Subject(s) - reinforcement learning , computer science , markov decision process , heuristics , lost sales , dual (grammatical number) , operations research , supply chain , mathematical optimization , inventory management , artificial intelligence , inventory theory , variety (cybernetics) , supply chain management , inventory control , operations management , markov process , economics , marketing , mathematics , business , art , statistics , literature , operating system

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