Zhang-Hua Fu

1.2k total citations
45 papers, 749 citations indexed

About

Zhang-Hua Fu is a scholar working on Industrial and Manufacturing Engineering, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Zhang-Hua Fu has authored 45 papers receiving a total of 749 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Industrial and Manufacturing Engineering, 25 papers in Artificial Intelligence and 11 papers in Computational Theory and Mathematics. Recurrent topics in Zhang-Hua Fu's work include Vehicle Routing Optimization Methods (19 papers), Metaheuristic Optimization Algorithms Research (19 papers) and Optimization and Packing Problems (10 papers). Zhang-Hua Fu is often cited by papers focused on Vehicle Routing Optimization Methods (19 papers), Metaheuristic Optimization Algorithms Research (19 papers) and Optimization and Packing Problems (10 papers). Zhang-Hua Fu collaborates with scholars based in China, France and United States. Zhang-Hua Fu's co-authors include Jin‐Kao Hao, Xiangjing Lai, Ying Huang, Yangming Zhou, Xiang Meng, Wei Li, Hongyuan Zha, Dong Yue, MengChu Zhou and Zhangming Niu and has published in prestigious journals such as European Journal of Operational Research, Expert Systems with Applications and IEEE Access.

In The Last Decade

Zhang-Hua Fu

42 papers receiving 732 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhang-Hua Fu China	16	299	261	198	130	90	45	749
T.H. Lee Singapore	15	108 0.4×	295 1.1×	170 0.9×	123 0.9×	31 0.3×	47	747
P. Merz Germany	8	314 1.1×	490 1.9×	238 1.2×	69 0.5×	105 1.2×	12	746
Qingzheng Xu China	13	52 0.2×	337 1.3×	185 0.9×	53 0.4×	81 0.9×	64	669
Ali Maroosi Iran	12	68 0.2×	380 1.5×	64 0.3×	52 0.4×	115 1.3×	34	779
Domagoj Jakobović Croatia	22	747 2.5×	928 3.6×	195 1.0×	150 1.2×	188 2.1×	105	1.6k
David J. Smith New Zealand	7	322 1.1×	322 1.2×	177 0.9×	45 0.3×	72 0.8×	16	726
Masaharu Munetomo Japan	15	66 0.2×	467 1.8×	212 1.1×	58 0.4×	191 2.1×	103	802
Peter Merz Germany	13	275 0.9×	506 1.9×	262 1.3×	55 0.4×	205 2.3×	32	882
Ahmed F. Ali Egypt	13	53 0.2×	341 1.3×	179 0.9×	74 0.6×	87 1.0×	48	579

Countries citing papers authored by Zhang-Hua Fu

Since Specialization

Citations

This map shows the geographic impact of Zhang-Hua Fu'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 Zhang-Hua Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhang-Hua Fu more than expected).

Fields of papers citing papers by Zhang-Hua Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhang-Hua Fu. 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 Zhang-Hua Fu. The network helps show where Zhang-Hua Fu may publish in the future.

Co-authorship network of co-authors of Zhang-Hua Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhang-Hua Fu. A scholar is included among the top collaborators of Zhang-Hua Fu 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 Zhang-Hua Fu. Zhang-Hua Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Wu, Xinyu, et al.. (2025). Efficient Backbone Network Construction in Wireless Artificial Intelligent Computing Systems. Tsinghua Science & Technology. 30(5). 2300–2319. 1 indexed citations

Gao, Zheng, Fuqin Deng, Zhang-Hua Fu, Xiangjing Lai, & Qinghua Wu. (2025). A problem reduction based memetic algorithm for the vehicle routing problem with discrete split deliveries and pickups. Computers & Operations Research. 182. 107106–107106.

Zhou, Yangming, et al.. (2024). Learning to Detect Critical Nodes in Sparse Graphs via Feature Importance Awareness. IEEE Transactions on Automation Science and Engineering. 22. 3772–3782. 3 indexed citations

Lai, Xiangjing, et al.. (2023). Global optimization and structural analysis of Coulomb and logarithmic potentials on the unit sphere using a population-based heuristic approach. Expert Systems with Applications. 238. 121704–121704.

Hao, Jin‐Kao, et al.. (2022). An effective hybrid search algorithm for the multiple traveling repairman problem with profits. European Journal of Operational Research. 304(2). 381–394. 9 indexed citations

Hu, Shan, Yi Zhou, Mingyu Xiao, Zhang-Hua Fu, & Zhipeng Lü. (2022). Listing maximal k-relaxed-vertex connected components from large graphs. Information Sciences. 620. 67–83. 2 indexed citations

Li, Jian, et al.. (2022). Cooperatively Scheduling Hundreds of Fetch and Freight Robots in an Autonomous Warehouse. 219. 469–474. 3 indexed citations

Zhou, Yangming, Wenqiang Xu, Zhang-Hua Fu, & MengChu Zhou. (2021). Solving Colored Traveling Salesman Problem via Multi-neighborhood Simulated Annealing Search. 1–6. 1 indexed citations

Liu, Yuanyuan, et al.. (2021). TSingNet: Scale-aware and context-rich feature learning for traffic sign detection and recognition in the wild. Neurocomputing. 447. 10–22. 48 indexed citations

10.

Lai, Xiangjing, Jin‐Kao Hao, Dong Yue, Zhipeng Lü, & Zhang-Hua Fu. (2021). Iterated dynamic thresholding search for packing equal circles into a circular container. European Journal of Operational Research. 299(1). 137–153. 21 indexed citations

11.

Zhang, Lianxin, Zhang-Hua Fu, Hengli Liu, et al.. (2021). An Efficient Parallel Self-assembly Planning Algorithm for Modular Robots in Environments with Obstacles. 10038–10044. 3 indexed citations

12.

Li, Wei, Xiang Meng, Ying Huang, & Zhang-Hua Fu. (2020). Multipopulation cooperative particle swarm optimization with a mixed mutation strategy. Information Sciences. 529. 179–196. 104 indexed citations

13.

Li, Hong, et al.. (2019). An Efficient 2-opt Operator for the Robotic Task Sequencing Problem. 124–129. 3 indexed citations

14.

Fu, Zhang-Hua, et al.. (2019). Dynamically Reconstructing Minimum Spanning Trees After Swapping Pairwise Vertices. IEEE Access. 7. 16351–16363. 3 indexed citations

15.

Lai, Xiangjing & Zhang-Hua Fu. (2019). A Tabu Search Approach With Dynamical Neighborhood Size for Solving the Maximum Min-Sum Dispersion Problem. IEEE Access. 7. 181357–181368. 8 indexed citations

16.

Fu, Zhang-Hua, et al.. (2018). Dynamic Task Sequencing of Manipulator by Monte Carlo Tree Search. 569–574. 2 indexed citations

17.

Fu, Zhang-Hua & Jin‐Kao Hao. (2017). Knowledge-guided local search for the prize-collecting Steiner tree problem in graphs. Knowledge-Based Systems. 128. 78–92. 10 indexed citations

18.

Fu, Zhang-Hua, Wenqi Huang, & Zhipeng Lü. (2012). Iterated tabu search for the circular open dimension problem. European Journal of Operational Research. 225(2). 236–243. 25 indexed citations

19.

Huang, Wenqi, et al.. (2011). Tabu search algorithm combined with global perturbation for packing arbitrary sized circles into a circular container. Science China Information Sciences. 56(9). 1–14. 12 indexed citations

20.

Fu, Zhang-Hua. (1999). Dimensionality optimization by heuristic greedy learning vs. genetic algorithms in knowledge discovery and data mining. Intelligent Data Analysis. 3(3). 211–225. 3 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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