Jing Liang
Impact in
- Computational Theory and Mathematics top 0.01%
- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 0.02%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Solar Radiation and Photovoltaics
Papers in
-
- Metaheuristic Optimization Algorithms Research 137
- Evolutionary Algorithms and Applications 89
-
- Advanced Multi-Objective Optimization Algorithms 115
- Co-authors
- Ponnuthurai Nagaratnam Suganthan (41 shared papers)Boyang Qu (90 shared papers)A. K. Qin (6 shared papers)S. Baskar (4 shared papers)Caitong Yue (84 shared papers)Kunjie Yu (86 shared papers)Kalyanmoy Deb (3 shared papers)Santosh Kumar Tiwari (1 shared paper)
- Journals
- IEEE Transactions on Evolutionary Computation (25 papers)Swarm and Evolutionary Computation (20 papers)Applied Soft Computing (12 papers)Information Sciences (8 papers)IEEE Transactions on Systems Man and Cybernetics Systems (7 papers)
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Jing Liang
371 papers receiving 16.6k citations
Jing Liang's Hit Papers
Peers
Comparison fields: 5 of 192
- Computational Theory and Mathematics 7.5k
- Artificial Intelligence 11.5k
- Industrial and Manufacturing Engineering 1.1k
- Control and Systems Engineering 2.2k
- Renewable Energy, Sustainability and the Environment 1.5k
Countries citing papers authored by Jing Liang
This map shows the geographic impact of Jing Liang'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 Jing Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Liang more than expected).
Fields of papers citing papers by Jing Liang
This network shows the impact of papers produced by Jing Liang. 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 Jing Liang. The network helps show where Jing Liang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jing Liang, 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 413 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Comprehensive learning particle swarm optimizer for global optimization of multimodal functions Hit paper breakdown → | 2006 | 2918 |
| 2 | Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization Hit paper breakdown → | 2005 | 2014 |
| 3 | Problem Definitions and Evaluation Criteria for the CEC 2013 Special Session on Real-Parameter Optimization Hit paper breakdown → | 2013 | 540 |
| 4 | Parameters identification of photovoltaic models using an improved JAYA optimization algorithm Hit paper breakdown → | 2017 | 467 |
| 5 | A Multiobjective Particle Swarm Optimizer Using Ring Topology for Solving Multimodal Multiobjective Problems Hit paper breakdown → | 2017 | 415 |
| 6 | 2005 | 383 | |
| 7 | A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module Hit paper breakdown → | 2019 | 377 |
| 8 | 2005 | 349 | |
| 9 | Differential Evolution With Neighborhood Mutation for Multimodal Optimization Hit paper breakdown → | 2012 | 340 |
| 10 | 2018 | 327 | |
| 11 | Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization | 2006 | 321 |
| 12 | 2010 | 300 | |
| 13 | A Survey on Evolutionary Constrained Multiobjective Optimization Hit paper breakdown → | 2022 | 242 |
| 14 | 2019 | 228 | |
| 15 | 2005 | 226 | |
| 16 | 2019 | 185 | |
| 17 | 2008 | 183 | |
| 18 | An Evolutionary Multitasking Optimization Framework for Constrained Multiobjective Optimization Problems Hit paper breakdown → | 2022 | 177 |
| 19 | 2017 | 168 | |
| 20 | 2016 | 167 |
About Jing Liang
Jing Liang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Electrical and Electronic Engineering, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 413 papers that have together received 17.1k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (137 papers), Advanced Multi-Objective Optimization Algorithms (115 papers), Evolutionary Algorithms and Applications (89 papers), Advanced Manufacturing and Logistics Optimization (12 papers), Scheduling and Optimization Algorithms (12 papers), Face and Expression Recognition (11 papers), Photovoltaic System Optimization Techniques (11 papers) and Advanced Algorithms and Applications (11 papers). The work is most often cited by research in Computational Theory and Mathematics (7.5k citations), Artificial Intelligence (11.5k citations), Industrial and Manufacturing Engineering (1.1k citations), Control and Systems Engineering (2.2k citations) and Renewable Energy, Sustainability and the Environment (1.5k citations). Jing Liang has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Ponnuthurai Nagaratnam Suganthan, Boyang Qu, A. K. Qin, S. Baskar, Caitong Yue, Kunjie Yu, Kalyanmoy Deb, Santosh Kumar Tiwari, Nikolaus Hansen and Anne Auger. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, Swarm and Evolutionary Computation, Applied Soft Computing, Information Sciences and IEEE Transactions on Systems Man and Cybernetics Systems.
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.