An improved deep Q-learning algorithm for a trade-off between energy consumption and productivity in batch scheduling-Reference-Cited by-同舟云学术

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An improved deep Q-learning algorithm for a trade-off between energy consumption and productivity in batch scheduling

Published:2024-02 Issue: Volume:188 Page:109925
ISSN:0360-8352
Container-title:Computers & Industrial Engineering
language:en
Short-container-title:Computers & Industrial Engineering

Author:

Zheng Xu^ORCID,Chen Zhen

Funder

Scientific Research Foundation of Hunan Provincial Education Department

Publisher

Elsevier BV

Reference49 articles.

1. Discrete-time strategic job arrivals to a single machine with waiting and lateness penalties;Alon;European Journal of Operational Research,2022

2. Non-identical parallel machines batch processing problem with release dates, due dates and variable maintenance activity to minimize total tardiness;Beldar;Computers & Industrial Engineering,2022

3. The n-dimensional hypervolume;Blonder;Global Ecology and Biogeography,2014

4. Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning;Brammer;European Journal of Operational Research,2022

5. Energy-efficient scheduling for an energy-intensive industry under punitive electricity price;Chen;Journal of Cleaner Production,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Q-Learning Energy Management System (Q-EMS) in Wireless Sensor Network;2024 International Conference on Smart Computing, IoT and Machine Learning (SIML);2024-06-06

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