Liangjun Ke
Impact in
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- Vehicle Routing Optimization Methods
- Optimization and Packing Problems
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Metaheuristic Optimization Algorithms Research 10
- Reinforcement Learning in Robotics 6
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- Vehicle Routing Optimization Methods 15
- Optimization and Packing Problems 5
- Co-authors
- Zuren Feng (17 shared papers)Qingfu Zhang (3 shared papers)Roberto Battiti (2 shared papers)Zhigang Ren (3 shared papers)Claudia Archetti (1 shared paper)Xueming Qian (2 shared papers)Xian‐Sheng Hua (1 shared paper)Ping Chen (1 shared paper)
In The Last Decade
Liangjun Ke
49 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 91
- Industrial and Manufacturing Engineering 536
- Computational Theory and Mathematics 355
- Artificial Intelligence 551
- Transportation 95
- Automotive Engineering 171
Countries citing papers authored by Liangjun Ke
This map shows the geographic impact of Liangjun Ke'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 Liangjun Ke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liangjun Ke more than expected).
Fields of papers citing papers by Liangjun Ke
This network shows the impact of papers produced by Liangjun Ke. 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 Liangjun Ke. The network helps show where Liangjun Ke may publish in the future.
Co-authors
The 25 scholars most cited alongside Liangjun Ke, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 237 | |
| 2 | 2011 | 168 | |
| 3 | 2007 | 137 | |
| 4 | 2008 | 123 | |
| 5 | 2020 | 122 | |
| 6 | 2014 | 87 | |
| 7 | 2010 | 70 | |
| 8 | 2012 | 65 | |
| 9 | 2015 | 53 | |
| 10 | 2008 | 43 | |
| 11 | 2018 | 29 | |
| 12 | 2020 | 26 | |
| 13 | 2021 | 24 | |
| 14 | 2015 | 22 | |
| 15 | 2010 | 20 | |
| 16 | 2014 | 20 | |
| 17 | 2010 | 19 | |
| 18 | 2011 | 14 | |
| 19 | 2017 | 14 | |
| 20 | 2010 | 13 |
About Liangjun Ke
Liangjun Ke is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering, Computational Theory and Mathematics, Computer Networks and Communications and Aerospace Engineering, having authored 54 papers that have together received 1.5k indexed citations. Recurring topics across this work include Vehicle Routing Optimization Methods (15 papers), Metaheuristic Optimization Algorithms Research (10 papers), Satellite Communication Systems (8 papers), Mobile Agent-Based Network Management (7 papers), Advanced Multi-Objective Optimization Algorithms (7 papers), Optimization and Search Problems (6 papers), Reinforcement Learning in Robotics (6 papers) and Optimization and Packing Problems (5 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (536 citations), Computational Theory and Mathematics (355 citations), Artificial Intelligence (551 citations), Transportation (95 citations) and Automotive Engineering (171 citations). Liangjun Ke has collaborated with scholars based in China, Hong Kong and Japan. Frequent co-authors include Zuren Feng, Qingfu Zhang, Roberto Battiti, Zhigang Ren, Claudia Archetti, Xueming Qian, Xian‐Sheng Hua, Ping Chen, Zhaojun Zhang and Zhigang Ren. Their work appears in journals such as Applied Intelligence, IEEE Transactions on Cybernetics, Computers & Industrial Engineering, Annals of Operations Research and International Journal of Bio-Inspired Computation.
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.