Genghui Li

2.5k citations
62 papers · 2.0k · h-index 26

Impact in

Papers in

Genghui Li

59 papers receiving 2.0k citations

Peers

Genghui Li
Comparison fields: 5 of 110
  • Computational Theory and Mathematics 885
  • Artificial Intelligence 1.2k
  • Industrial and Manufacturing Engineering 193
  • Control and Systems Engineering 186
  • Computer Vision and Pattern Recognition 171
Replace E. Damangir with:
E. Damangir Iran
Hoda Zamani Iran
Jian-Yu Li China
Heqi Wang China
Ryoji Tanabe Japan
Zhenyu Meng China
Shimpi Singh Jadon India
Tong Han China
Abhishek Kumar India
Bing-Chuan Wang China
Genghui Li relative to E. Damangir Iran E. Damangir's profile →
Citations per field
00.5×2×4×6×8.3×
E. Damangir · 1×
Citations per year

Countries citing papers authored by Genghui Li

Since Specialization
Citations

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

Fields of papers citing papers by Genghui Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Genghui Li. 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 Genghui Li. The network helps show where Genghui Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Genghui Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Genghui Li Line = papers co-authored together Genghui Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015186
2 2016119
3 2015113
4 2018110
5 201795
6 201794
7 201982
8 201781
9 201681
10 202178
11 202368
12 201662
13 202256
14 201754
15 202154
16 201847
17 202143
18 201940
19 202339
20 201838

About Genghui Li

Genghui Li is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Industrial and Manufacturing Engineering, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 62 papers that have together received 2.0k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (42 papers), Metaheuristic Optimization Algorithms Research (39 papers), Evolutionary Algorithms and Applications (27 papers), Vehicle Routing Optimization Methods (4 papers), Robotic Path Planning Algorithms (3 papers), Optimal Experimental Design Methods (3 papers), Scheduling and Optimization Algorithms (3 papers) and Topology Optimization in Engineering (2 papers). The work is most often cited by research in Computational Theory and Mathematics (885 citations), Artificial Intelligence (1.2k citations), Industrial and Manufacturing Engineering (193 citations), Control and Systems Engineering (186 citations) and Computer Vision and Pattern Recognition (171 citations). Genghui Li has collaborated with scholars based in China, Hong Kong and Spain. Frequent co-authors include Laizhong Cui, Qiuzhen Lin, Nan Lu, Qingfu Zhang, Zhenkun Wang, Jianyong Chen, Weifeng Gao, Jian Lü, Zhong Ming and Zexuan Zhu. Their work appears in journals such as Information Sciences, IEEE Transactions on Evolutionary Computation, Swarm and Evolutionary Computation, IEEE Transactions on Systems Man and Cybernetics Systems and Applied Soft Computing.

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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