Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 DRL-Based Reactive Scheduling Policy for Flexible Job Shops With Random Job Arrivals
Linlin Zhao, Jiaxin Fan, Chunjiang Zhang, et al.
IEEE Transactions on Automation Science and Engineering (2023) Vol. 21, Iss. 3, pp. 2912-2923
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

HGNP: A PCA-based heterogeneous graph neural network for a family distributed flexible job shop
Jiake Li, Junqing Li, Ying Xu
Computers & Industrial Engineering (2025), pp. 110855-110855
Closed Access | Times Cited: 2
Manufacturing resource-based self-organizing scheduling using multi-agent system and deep reinforcement learning
Yuxin Li, Qihao Liu, Xinyu Li, et al.
Journal of Manufacturing Systems (2025) Vol. 79, pp. 179-198
Closed Access | Times Cited: 2
An end-to-end deep reinforcement learning method based on graph neural network for distributed job-shop scheduling problem
Jiang‐Ping Huang, Liang Gao, Xinyu Li
Expert Systems with Applications (2023) Vol. 238, pp. 121756-121756
Closed Access | Times Cited: 24
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
An efficient and adaptive design of reinforcement learning environment to solve job shop scheduling problem with soft actor-critic algorithm
Jinghua Si, Xinyu Li, Liang Gao, et al.
International Journal of Production Research (2024), pp. 1-16
Closed Access | Times Cited: 7
Multi-agent deep reinforcement learning for dynamic reconfigurable shop scheduling considering batch processing and worker cooperation
Yuxin Li, Xinyu Li, Liang Gao, et al.
Robotics and Computer-Integrated Manufacturing (2024) Vol. 91, pp. 102834-102834
Closed Access | Times Cited: 5
Automating Pipe Spool Fabrication Shop Scheduling for Modularized Industrial Construction Projects Using Reinforcement Learning
Mohamed ElMenshawy, Lingzi Wu, Brian Gue, et al.
Journal of Computing in Civil Engineering (2025) Vol. 39, Iss. 3
Closed Access
A three-stage adaptive memetic algorithm for multi-objective optimization of flexible assembly job-shop scheduling problem
Chenlu Zhang, Jiamei Feng, Mingchuan Zhang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 144, pp. 110098-110098
Closed Access
Solving Dynamic Multi-Objective Flexible Job Shop Scheduling Problems Using a Dual-Level Integrated Deep Q-Network Approach
Hua Xu, Jing-Hua Zheng, Lan Huang, et al.
Processes (2025) Vol. 13, Iss. 2, pp. 386-386
Open Access
A random flight–follow leader and reinforcement learning approach for flexible job shop scheduling problem
Changshun Shao, Zhenglin Yu, Hongchang Ding, et al.
The Journal of Supercomputing (2025) Vol. 81, Iss. 3
Closed Access
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
Research on dynamic job shop scheduling problem with AGV based on DQN
Zhengfeng Li, Wengpeng Gu, Huichao Shang, et al.
Cluster Computing (2025) Vol. 28, Iss. 4
Closed Access
TDCR: Transformer based decision conflict resolution model for collaborative scheduling
Xian‐Zhang Hu, Jian An, Xiaolin Gui, et al.
Neurocomputing (2025), pp. 129760-129760
Closed Access
A heuristic-assisted deep reinforcement learning algorithm for flexible job shop scheduling with transport constraints
Xiaoting Dong, Guangxi Wan, Peng Zeng
Complex & Intelligent Systems (2025) Vol. 11, Iss. 5
Open Access
Deep reinforcement learning for solving efficient and energy-saving flexible job shop scheduling problem with multi-AGV
Weiyao Cheng, Chaoyong Zhang, Leilei Meng, et al.
Computers & Operations Research (2025), pp. 107087-107087
Closed Access
Real-time scheduling for two-stage assembly flowshop with dynamic job arrivals by deep reinforcement learning
Jian Chen, Hanlei Zhang, Wenjing Ma, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102632-102632
Closed Access | Times Cited: 4
An incremental learning approach to dynamic parallel machine scheduling with sequence-dependent setups and machine eligibility restrictions
Donghun Lee, In-Beom Park, Kwanho Kim
Applied Soft Computing (2024) Vol. 164, pp. 112002-112002
Closed Access | Times Cited: 3
Learning to schedule dynamic distributed reconfigurable workshops using expected deep Q-network
Shengluo Yang, Junyi Wang, Zhigang Xu
Advanced Engineering Informatics (2023) Vol. 59, pp. 102307-102307
Closed Access | Times Cited: 8
Deep reinforcement learning-based dynamic scheduling for resilient and sustainable manufacturing: A systematic review
Chao Zhang, Max Juraschek, Christoph Herrmann
Journal of Manufacturing Systems (2024) Vol. 77, pp. 962-989
Open Access | Times Cited: 2
A literature review of reinforcement learning methods applied to job-shop scheduling problems
Xiehui Zhang, Guangyu Zhu
Computers & Operations Research (2024), pp. 106929-106929
Closed Access | Times Cited: 2
Deep Reinforcement Learning Based on Graph Neural Network for Flexible Job Shop Scheduling Problem with Lot Streaming
Junchao He, Junqing Li
Lecture notes in computer science (2024), pp. 85-95
Closed Access | Times Cited: 1
Optimizing Robotic Task Sequencing and Trajectory Planning on the Basis of Deep Reinforcement Learning
Xiaoting Dong, Guangxi Wan, Peng Zeng, et al.
Biomimetics (2023) Vol. 9, Iss. 1, pp. 10-10
Open Access | Times Cited: 2
An effective multi-agent-based graph reinforcement learning method for solving flexible job shop scheduling problem
Lanjun Wan, Long Fu, Changyun Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 139, pp. 109557-109557
Closed Access
A dynamic flexible job shop scheduling method based on collaborative agent reinforcement learning
Changshun Shao, Zhenglin Yu, Hongchang Ding, et al.
Flexible Services and Manufacturing Journal (2024)
Closed Access
Knowledge-Driven Scheduling of Digital Twin-Based Flexible Ship Pipe Manufacturing Workshop
Hongmei Zhang, Sisi Tian, Ruifang Li, et al.
Lecture notes in mechanical engineering (2024), pp. 293-306
Closed Access
Page 1 - Next Page

Scroll to top