| An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition K Li, K Deb, Q Zhang, S Kwong IEEE Transactions on Evolutionary Computation 19 (5), 694-716, 2015 | 1086 | 2015 |
| Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition K Li, A Fialho, S Kwong, Q Zhang IEEE Transactions on Evolutionary Computation 18 (1), 114-130, 2014 | 399 | 2014 |
| Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization K Li, R Chen, G Fu, X Yao IEEE Transactions on Evolutionary Computation 23 (2), 303-315, 2019 | 349 | 2019 |
| Stable Matching Based Selection in Evolutionary Multiobjective Optimization K Li, Q Zhang, S Kwong, M Li, R Wang IEEE Transactions on Evolutionary Computation 18 (6), 909-923, 2014 | 343 | 2014 |
| Interrelationship-Based Selection for Decomposition Multiobjective Optimization K Li, S Kwong, Q Zhang, K Deb IEEE Transactions on Cybernetics 45 (10), 2076-2088, 2015 | 172 | 2015 |
| Dynamic Multi-Objectives Optimization with a Changing Number of Objectives R Chen, K Li, X Yao IEEE Transactions on Evolutionary Computation 22 (1), 157-171, 2018 | 155 | 2018 |
| Achieving balance between proximity and diversity in multi-objective evolutionary algorithm K Li, S Kwong, J Cao, M Li, J Zheng, R Shen Information Sciences 182 (1), 220-242, 2012 | 138 | 2012 |
| R-Metric: Evaluating the Performance of Preference-Based Evolutionary Multi-Objective Optimization Using Reference Points K Li, K Deb, X Yao IEEE Transactions on Evolutionary Computation 22 (6), 821 - 835, 2018 | 125* | 2018 |
| Efficient Non-domination Level Update Method for Steady-State Evolutionary Multiobjective Optimization K Li, K Deb, Q Zhang, Q Zhang IEEE Transactions on Cybernetics 47 (9), 2838-2849, 2017 | 120* | 2017 |
| Learning to Decompose: a Paradigm for Decomposition-based Multiobjective Optimization M Wu, K Li, S Kwong, Q Zhang, J Zhang IEEE Transactions on Evolutionary Computation 23 (3), 376-390, 2019 | 109 | 2019 |
| Evolutionary many-objective optimization based on adversarial decomposition M Wu, K Li, S Kwong, Q Zhang IEEE transactions on cybernetics 50 (2), 753-764, 2018 | 106 | 2018 |
| Evolutionary multiobjective optimization-based multimodal optimization: Fitness landscape approximation and peak detection R Cheng, M Li, K Li, X Yao IEEE Transactions on Evolutionary Computation 22 (5), 692-706, 2017 | 98 | 2017 |
| A Dual-Population Paradigm for Evolutionary Multiobjective Optimization K Li, S Kwong, K Deb Information Sciences 309, 50-72, 2015 | 85 | 2015 |
| FEMOSAA: Feature-guided and knee-driven multi-objective optimization for self-adaptive software T Chen, K Li, R Bahsoon, X Yao ACM Transactions on Software Engineering and Methodology (TOSEM) 27 (2), 1-50, 2018 | 78 | 2018 |
| Matching-Based Selection with Incomplete Lists for Decomposition Multi-Objective Optimization M Wu, K Li, S Kwong, Y Zhou, Q Zhang IEEE Transactions on Evolutionary Computation 21 (4), 554-568, 2017 | 78 | 2017 |
| Class-specific soft voting based multiple extreme learning machines ensemble J Cao, S Kwong, R Wang, X Li, K Li, X Kong Neurocomputing 149, 275-284, 2015 | 74 | 2015 |
| Integration of preferences in decomposition multiobjective optimization K Li, R Chen, G Min, X Yao IEEE transactions on cybernetics 48 (12), 3359-3370, 2018 | 73 | 2018 |
| A general framework for evolutionary multiobjective optimization via manifold learning K Li, S Kwong Neurocomputing 146, 65-74, 2014 | 67 | 2014 |
| Learning paradigm based on jumping genes: A general framework for enhancing exploration in evolutionary multiobjective optimization K Li, S Kwong, R Wang, KS Tang, KF Man Information Sciences 226, 1-22, 2013 | 66 | 2013 |
| Does preference always help? A holistic study on preference-based evolutionary multiobjective optimization using reference points K Li, M Liao, K Deb, G Min, X Yao IEEE Transactions on Evolutionary Computation 24 (6), 1078-1096, 2020 | 58 | 2020 |
Sam KwongLingnan Univerity, Hong KongVerified email at ln.edu.hk
