Mingfeng Fan

705 total citations
20 papers, 465 citations indexed

About

Mingfeng Fan is a scholar working on Computer Networks and Communications, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, Mingfeng Fan has authored 20 papers receiving a total of 465 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Networks and Communications, 6 papers in Aerospace Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Mingfeng Fan's work include Optimization and Search Problems (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Vehicle Routing Optimization Methods (4 papers). Mingfeng Fan is often cited by papers focused on Optimization and Search Problems (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Vehicle Routing Optimization Methods (4 papers). Mingfeng Fan collaborates with scholars based in China, Singapore and Canada. Mingfeng Fan's co-authors include Guohua Wu, Witold Pedrycz, Ponnuthurai Nagaratnam Suganthan, Huan Liu, Xiamiao Li, Jianghan Zhu, Yong‐Ming He, Jianmai Shi, Yanghe Feng and Zhiguang Cao and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Vehicular Technology and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Mingfeng Fan

18 papers receiving 443 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mingfeng Fan China 10 192 129 128 124 112 20 465
Xiangmin Guan China 14 388 2.0× 249 1.9× 60 0.5× 92 0.7× 66 0.6× 42 569
Xichao Su China 13 205 1.1× 171 1.3× 186 1.5× 72 0.6× 62 0.6× 44 545
Cristian Ramirez‐Atencia Spain 9 188 1.0× 191 1.5× 69 0.5× 103 0.8× 87 0.8× 18 365
Murat Ermiş Türkiye 9 139 0.7× 98 0.8× 127 1.0× 113 0.9× 27 0.2× 26 363
Antonio Díaz-Calderón United States 10 150 0.8× 159 1.2× 55 0.4× 35 0.3× 68 0.6× 22 447
Yuning Chen China 18 418 2.2× 40 0.3× 333 2.6× 399 3.2× 120 1.1× 47 842
Márcio da Silva Arantes Brazil 11 146 0.8× 174 1.3× 167 1.3× 49 0.4× 57 0.5× 25 422
Aydın Sipahioğlu Türkiye 10 82 0.4× 127 1.0× 109 0.9× 73 0.6× 38 0.3× 20 286

Countries citing papers authored by Mingfeng Fan

Since Specialization
Citations

This map shows the geographic impact of Mingfeng Fan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mingfeng Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingfeng Fan more than expected).

Fields of papers citing papers by Mingfeng Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mingfeng Fan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mingfeng Fan. The network helps show where Mingfeng Fan may publish in the future.

Co-authorship network of co-authors of Mingfeng Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Mingfeng Fan. A scholar is included among the top collaborators of Mingfeng Fan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mingfeng Fan. Mingfeng Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Fan, Mingfeng, et al.. (2026). Unicorn: A Universal and Collaborative Reinforcement Learning Approach Toward Generalizable Network-Wide Traffic Signal Control. IEEE Transactions on Intelligent Transportation Systems. 1–17.
2.
Li, Jiayi, Guohua Wu, Mingfeng Fan, Zhiguang Cao, & Yalin Wang. (2025). Heterogeneous Attention-Based Graph Convolutional Network for Solving Asymmetric Pickup and Delivery Problem. IEEE Transactions on Automation Science and Engineering. 22. 13000–13014. 1 indexed citations
3.
Fan, Mingfeng, Hao Yu, Juan Xu, et al.. (2025). Exploring Psychological Factors and Brain Alterations in Functional Anorectal Pain Patients: Insights From Multimodal Magnetic Resonance Imaging Investigations. Neurogastroenterology & Motility. 37(5). e15017–e15017.
4.
Fan, Mingfeng, Huan Liu, Guohua Wu, Aldy Gunawan, & Guillaume Sartoretti. (2025). Multi-UAV reconnaissance mission planning via deep reinforcement learning with simulated annealing. Swarm and Evolutionary Computation. 93. 101858–101858. 4 indexed citations
5.
Wang, Shuai, et al.. (2025). Gut microbiota and relevant metabolites analysis in perianal abscess of infants. BMC Microbiology. 25(1). 333–333. 1 indexed citations
6.
Fan, Mingfeng, Yaoxin Wu, Zhiguang Cao, et al.. (2024). Conditional Neural Heuristic for Multiobjective Vehicle Routing Problems. IEEE Transactions on Neural Networks and Learning Systems. 36(3). 4677–4689. 4 indexed citations
7.
Wu, Guohua, et al.. (2024). DL-DRL: A Double-Level Deep Reinforcement Learning Approach for Large-Scale Task Scheduling of Multi-UAV. IEEE Transactions on Automation Science and Engineering. 22. 1028–1044. 31 indexed citations
8.
Wu, Guohua, et al.. (2024). Joint Task Offloading and Resource Allocation in Multi-UAV Multi-Server Systems: An Attention-Based Deep Reinforcement Learning Approach. IEEE Transactions on Vehicular Technology. 73(8). 11964–11978. 18 indexed citations
9.
Zhang, Yifeng, et al.. (2024). HeteroLight: A General and Efficient Learning Approach for Heterogeneous Traffic Signal Control. 1010–1017. 2 indexed citations
11.
Li, Yansen, Jingfeng Zhang, Yang Jiao, et al.. (2023). Natural course of perianal abscess in infants: a real-world study. Scientific Reports. 13(1). 18416–18416. 5 indexed citations
12.
Li, Jiaxing, et al.. (2023). Task Scheduling Under a Novel Framework for Data Relay Satellite Network via Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology. 72(5). 6654–6668. 32 indexed citations
13.
Fan, Mingfeng, Yaoxin Wu, Tianjun Liao, et al.. (2022). Deep Reinforcement Learning for UAV Routing in the Presence of Multiple Charging Stations. IEEE Transactions on Vehicular Technology. 72(5). 5732–5746. 28 indexed citations
14.
Wu, Guohua, et al.. (2022). An Overview and Experimental Study of Learning-Based Optimization Algorithms for the Vehicle Routing Problem. IEEE/CAA Journal of Automatica Sinica. 9(7). 1115–1138. 74 indexed citations
15.
Zhu, Jianghan, et al.. (2021). An Adaptive Reference Vector Adjustment Strategy and Improved Angle‐Penalized Value Method for RVEA. Complexity. 2021(1). 3 indexed citations
16.
Wu, Guohua, Mingfeng Fan, Jianmai Shi, & Yanghe Feng. (2021). Reinforcement Learning Based Truck-and-Drone Coordinated Delivery. IEEE Transactions on Artificial Intelligence. 4(4). 754–763. 55 indexed citations
17.
Zhu, Jianghan, et al.. (2020). Evolutionary many-Objective algorithm based on fractional dominance relation and improved objective space decomposition strategy. Swarm and Evolutionary Computation. 60. 100776–100776. 81 indexed citations
18.
Liu, Huan, Xiamiao Li, Mingfeng Fan, et al.. (2020). An Autonomous Path Planning Method for Unmanned Aerial Vehicle Based on a Tangent Intersection and Target Guidance Strategy. IEEE Transactions on Intelligent Transportation Systems. 23(4). 3061–3073. 66 indexed citations
19.
Liu, Huan, Xiamiao Li, Guohua Wu, et al.. (2020). An Iterative Two-Phase Optimization Method Based on Divide and Conquer Framework for Integrated Scheduling of Multiple UAVs. IEEE Transactions on Intelligent Transportation Systems. 22(9). 5926–5938. 50 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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