OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A Hierarchical Multi-Action Deep Reinforcement Learning Method for Dynamic Distributed Job-Shop Scheduling Problem With Job Arrivals
Jiang‐Ping Huang, Liang Gao, Xinyu Li
IEEE Transactions on Automation Science and Engineering (2024) Vol. 22, pp. 2501-2513
Closed Access | Times Cited: 9

Showing 9 citing articles:

Graph neural networks for job shop scheduling problems: A survey
Igor G. Smit, Jianan Zhou, Robbert Reijnen, et al.
Computers & Operations Research (2024), pp. 106914-106914
Open Access | Times Cited: 5

Real-time scheduling for production-logistics collaborative environment using multi-agent deep reinforcement learning
Yuxin Li, Xinyu Li, Liang Gao
Advanced Engineering Informatics (2025) Vol. 65, pp. 103216-103216
Closed Access

Integrated heterogeneous graph and reinforcement learning enabled efficient scheduling for surface mount technology workshop
Biao Zhang, Hongyan Sang, Chao Lu, et al.
Information Sciences (2025), pp. 122023-122023
Closed Access

Learn to optimise for job shop scheduling: a survey with comparison between genetic programming and reinforcement learning
Meng Xu, Yi Mei, Fangfang Zhang, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 6
Open Access

Comparative Performance Analysis of Meta-Heuristic Algorithms in Distributed Job Shop Scheduling
Mehmet Akif Şahman, Abdullah Oktay DÜNDAR
2022 57th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST) (2024), pp. 1-4
Closed Access

A Multi-Action Deep Reinforcement Learning Based on BiLSTM for Flexible Job Shop Scheduling Problem with Tight Time
Rui Wang, C. Karen Liu, Xinzhuo Wang, et al.
(2024), pp. 318-326
Closed Access

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