Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities

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作者：
Yan, Yimo [1 ]
Chow, Andy H.F. [2 ]
Ho, Chin Pang [3 ]
Kuo, Yong-Hong [1 ,4 ]
Wu, Qihao [1 ]
Ying, Chengshuo [5 ]
机构：
[1] Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong, Hong Kong
[2] Department of Advanced Design and Systems Engineering, City University of Hong Kong, Hong Kong
[3] School of Data Science, City University of Hong Kong, Hong Kong
[4] HKU Musketeers Foundation Institute of Data Science, the University of Hong Kong, Hong Kong
[5] Yangtze Delta Region Academy of Beijing Institute of Technology, China
来源：
Transportation Research Part E: Logistics and Transportation Review | 2022年 / 162卷
关键词：
The authors are grateful to the Co-EIC; Associate Editor; and Reviewers for their comments and suggestions. The work described in this paper was partially supported by grants from Chow Sang Sang Group Research Fund sponsored by Chow Sang Sang Holdings International Limited (Project No. 9229059 and 9229076 ). The research of the third author was partially supported by the National Natural Science Foundation of China (Project No. 72032005 ). The research of the fourth author was partially supported by the Research Grants Council (RGC) (General Research Fund) 17200820 ); the Germany/Hong Kong Joint Research Scheme Germany Academic Exchange Service (DAAD) and RGC of Hong Kong ( G-HKU703/19 ); and the 2019 Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team (China) ( 2019BT02S593 );
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