Optimal Order Acceptance and Scheduling via Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Optimal Order Acceptance and Scheduling via Deep Reinforcement Learning

Published:2022-11 Issue: Volume: Page:
ISSN:
Container-title:2022 6th International Symposium on Computer Science and Intelligent Control (ISCSIC)
language:
Short-container-title:

Author:

Qian Jing¹,Chen Chao¹,Wu Keyu²,Yu Li³

Affiliation:

1. National University of Defense Technology,College of Systems Engineering,Changsha,Hunan

2. National University of Defense Technology,College of Systems Engineering and College of Electronic Sciences,Changsha,Hunan

3. Ningbo Lensee Intelligent Technology Co., Ltd,Ningbo,Zhejiang

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10063336/10063352/10063650.pdf?arnumber=10063650

Reference17 articles.

1. Order acceptance policy in Make-to-Order manufacturing based on average-reward reinforcement learning

2. Learning and adaptation of a policy for dynamic order acceptance in make-to-order manufacturing

3. A reinforcement learning approach for scheduling problems;reyna;Investigacion Operaciónal,2015

4. Pattern driven dynamic scheduling approach using reinforcement learning

5. Reinforcement learning for joint pricing, lead-time and scheduling decisions in make-to-order systems

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