| Surrogate-assisted cooperative swarm optimization of high-dimensional expensive problems C Sun, Y Jin, R Cheng, J Ding, J Zeng IEEE Transactions on Evolutionary Computation 21 (4), 644-660, 2017 | 393 | 2017 |
| Surrogate-assisted hierarchical particle swarm optimization H Yu, Y Tan, J Zeng, C Sun, Y Jin Information Sciences 454, 59-72, 2018 | 276 | 2018 |
| Bio-inspired self-organising multi-robot pattern formation: A review H Oh, AR Shirazi, C Sun, Y Jin Robotics and Autonomous Systems 91, 83-100, 2017 | 227 | 2017 |
| Offline data-driven evolutionary optimization using selective surrogate ensembles H Wang, Y Jin, C Sun, J Doherty IEEE Transactions on Evolutionary Computation 23 (2), 203-216, 2018 | 211 | 2018 |
| A two-layer surrogate-assisted particle swarm optimization algorithm C Sun, Y Jin, J Zeng, Y Yu Soft computing 19, 1461-1475, 2015 | 194 | 2015 |
| Multiobjective infill criterion driven Gaussian process-assisted particle swarm optimization of high-dimensional expensive problems J Tian, Y Tan, J Zeng, C Sun, Y Jin IEEE Transactions on Evolutionary Computation 23 (3), 459-472, 2018 | 172 | 2018 |
| A new fitness estimation strategy for particle swarm optimization C Sun, J Zeng, J Pan, S Xue, Y Jin Information sciences 221, 355-370, 2013 | 138 | 2013 |
| An improved vector particle swarm optimization for constrained optimization problems C Sun, J Zeng, J Pan Information Sciences 181 (6), 1153-1163, 2011 | 125 | 2011 |
| Large-scale evolutionary multiobjective optimization assisted by directed sampling S Qin, C Sun, Y Jin, Y Tan, J Fieldsend IEEE transactions on evolutionary computation 25 (4), 724-738, 2021 | 122 | 2021 |
| A generation-based optimal restart strategy for surrogate-assisted social learning particle swarm optimization H Yu, Y Tan, C Sun, J Zeng Knowledge-Based Systems 163, 14-25, 2019 | 85 | 2019 |
| Data-driven evolutionary optimization Y Jin, H Wang, C Sun Springer International Publishing, 2021 | 79 | 2021 |
| Multi-surrogate assisted binary particle swarm optimization algorithm and its application for feature selection P Hu, JS Pan, SC Chu, C Sun Applied soft computing 121, 108736, 2022 | 74 | 2022 |
| An efficient surrogate-assisted quasi-affine transformation evolutionary algorithm for expensive optimization problems N Liu, JS Pan, C Sun, SC Chu Knowledge-Based Systems 209, 106418, 2020 | 66 | 2020 |
| Multiple-strategy learning particle swarm optimization for large-scale optimization problems H Wang, M Liang, C Sun, G Zhang, L Xie Complex & Intelligent Systems 7, 1-16, 2021 | 62 | 2021 |
| A fitness approximation assisted competitive swarm optimizer for large scale expensive optimization problems C Sun, J Ding, J Zeng, Y Jin Memetic Computing 10 (2), 123-134, 2018 | 61 | 2018 |
| Multi-surrogate multi-tasking optimization of expensive problems P Liao, C Sun, G Zhang, Y Jin Knowledge-Based Systems 205, 106262, 2020 | 60 | 2020 |
| A modified particle swarm optimization based on decomposition with different ideal points for many-objective optimization problems S Qin, C Sun, G Zhang, X He, Y Tan Complex & Intelligent Systems 6, 263-274, 2020 | 58 | 2020 |
| Granularity-based surrogate-assisted particle swarm optimization for high-dimensional expensive optimization J Tian, C Sun, Y Tan, J Zeng Knowledge-Based Systems 187, 104815, 2020 | 48 | 2020 |
| A modified particle swarm optimization with feasibility-based rules for mixed-variable optimization problems C Sun, J Zeng, JS Pan International Journal of Innovative Computing, Information and Control 7 (6 …, 2011 | 44 | 2011 |
| A multi-swarm evolutionary framework based on a feedback mechanism R Cheng, C Sun, Y Jin 2013 IEEE Congress on Evolutionary Computation, 718-724, 2013 | 43 | 2013 |
Yaochu JinChair Professor for AI, MAE FIEEE, Westlake University, ChinaVerified email at westlake.edu.cn
