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 multi-objective migrating birds optimization algorithm based on game theory for dynamic flexible job shop scheduling problem
Lixin Wei, Jinxian He, Zeyin Guo, et al.
Expert Systems with Applications (2023) Vol. 227, pp. 120268-120268
Closed Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

A DQL-NSGA-III algorithm for solving the flexible job shop dynamic scheduling problem
Hongtao Tang, Xiao Yu, Wei Zhang, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121723-121723
Closed Access | Times Cited: 46

A Double Deep Q-Network framework for a flexible job shop scheduling problem with dynamic job arrivals and urgent job insertions
Shaojun Lu, Yongqi Wang, Min Kong, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108487-108487
Closed Access | Times Cited: 8

Joint scheduling optimisation method for the machining and heat-treatment of hydraulic cylinders based on improved multi-objective migrating birds optimisation
Xixing Li, Qingqing Zhao, Hongtao Tang, et al.
Journal of Manufacturing Systems (2024) Vol. 73, pp. 170-191
Closed Access | Times Cited: 6

Flexible job shop scheduling via deep reinforcement learning with meta-path-based heterogeneous graph neural network
Lanjun Wan, Long Fu, Changyun Li, et al.
Knowledge-Based Systems (2024) Vol. 296, pp. 111940-111940
Closed Access | Times Cited: 6

A Pareto-optimality based black widow spider algorithm for energy efficient flexible job shop scheduling problem considering new job insertion
Kashif Akram, M. Usman Maqbool Bhutta, Shahid Ikramullah Butt, et al.
Applied Soft Computing (2024) Vol. 164, pp. 111937-111937
Closed Access | Times Cited: 6

An energy-saving real-time scheduling method based on bi-level multi-agent architecture with bargaining game for flexible job shops
Mingzhu Hu, Shengfeng Qin, Shuying Wang, et al.
Expert Systems with Applications (2025), pp. 126527-126527
Closed Access

A novel hybrid intelligent scheduling: integrating human feedback into reinforcement learning for adaptive preference objectives
Chen Ding, Fei Qiao, Dongyuan Wang, et al.
International Journal of Production Research (2025), pp. 1-19
Closed Access

A Review on Intelligent Scheduling and Optimization for Flexible Job Shop
Bin Jiang, Yajie Ma, Lijun Chen, et al.
International Journal of Control Automation and Systems (2023) Vol. 21, Iss. 10, pp. 3127-3150
Closed Access | Times Cited: 14

A dynamic multi-objective evolutionary algorithm based on genetic engineering and improved particle swarm prediction strategy
Yue Yang, Yongjie Ma, Yan Zhao, et al.
Information Sciences (2024) Vol. 660, pp. 120125-120125
Closed Access | Times Cited: 4

Synergistic two-stage optimization for multi-objective energy management strategy of integrated photovoltaic-storage charging stations
Chenghao Lyu, Shuhe Zhan, Yuchen Zhang, et al.
Journal of Energy Storage (2024) Vol. 89, pp. 111665-111665
Closed Access | Times Cited: 4

Dynamic scheduling for multi-objective flexible job shop via deep reinforcement learning
Erdong Yuan, Liejun Wang, Shiji Song, et al.
Applied Soft Computing (2025) Vol. 171, pp. 112787-112787
Closed Access

A data-driven approach to pricing models for balanced public–private healthcare systems
Aydin Teymourifar, Onur Kaya, Gürkan Öztürk
Healthcare Analytics (2025) Vol. 7, pp. 100385-100385
Closed Access

An IoT-Enabled Real-Time Dynamic Scheduler for Flexible Job Shop Scheduling (FJSS) in an Industry 4.0-Based Manufacturing Execution System (MES 4.0)
Anum Tariq, Shoab Ahmed Khan, Wasi Haider But, et al.
IEEE Access (2024) Vol. 12, pp. 49653-49666
Open Access | Times Cited: 3

A discrete event simulator to implement deep reinforcement learning for the dynamic flexible job shop scheduling problem
Lorenzo Tiacci, Andrea Rossi
Simulation Modelling Practice and Theory (2024) Vol. 134, pp. 102948-102948
Open Access | Times Cited: 3

Integrating stop planning, timetabling and rolling stock planning on high-speed railway lines: A multi-objective optimization approach
Lin Yang, Dewei Li, Hui Wang, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121515-121515
Closed Access | Times Cited: 8

Genetic Programming for Dynamic Flexible Job Shop Scheduling: Evolution With Single Individuals and Ensembles
Meng Xu, Yi Mei, Fangfang Zhang, et al.
IEEE Transactions on Evolutionary Computation (2023) Vol. 28, Iss. 6, pp. 1761-1775
Closed Access | Times Cited: 8

Grid-based artificial bee colony algorithm for multi-objective job shop scheduling with manual loading and unloading tasks
Bohan Zhang, Ada Che, Yusheng Wang
Expert Systems with Applications (2023) Vol. 245, pp. 123011-123011
Closed Access | Times Cited: 8

Multi-objective fuzzy surgical scheduling during post-disaster with Nash equilibrium
Zhi Li, Jiaqi Yan, Jun Xue
Expert Systems with Applications (2023) Vol. 238, pp. 121945-121945
Open Access | Times Cited: 4

Cooperative coati optimization algorithm with transfer functions for feature selection and knapsack problems
Rui Zhong, Chao Zhang, Jun Yu
Knowledge and Information Systems (2024) Vol. 66, Iss. 11, pp. 6933-6974
Closed Access | Times Cited: 1

Multi-guided population co-evolutionary algorithm based on multiple similarity decomposition for large-scale flexible job shop scheduling problem
Cong Wang, Lixin Wei, Hao Sun, et al.
Applied Soft Computing (2024) Vol. 166, pp. 112157-112157
Closed Access | Times Cited: 1

A novel method for solving dynamic flexible job-shop scheduling problem via DIFFormer and deep reinforcement learning
Lanjun Wan, Xueyan Cui, Haoxin Zhao, et al.
Computers & Industrial Engineering (2024) Vol. 198, pp. 110688-110688
Closed Access | Times Cited: 1

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