MOEA/D: A multiobjective evolutionary algorithm based on decomposition Q Zhang, H Li IEEE Transactions on evolutionary computation 11 (6), 712-731, 2007 | 7327 | 2007 |
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II H Li, Q Zhang IEEE transactions on evolutionary computation 13 (2), 284-302, 2008 | 2388 | 2008 |
Multiobjective evolutionary algorithms: A survey of the state of the art A Zhou, BY Qu, H Li, SZ Zhao, PN Suganthan, Q Zhang Swarm and Evolutionary Computation 1 (1), 32-49, 2011 | 2143 | 2011 |
The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances Q Zhang, W Liu, H Li 2009 IEEE congress on evolutionary computation, 203-208, 2009 | 705 | 2009 |
Opposition-based particle swarm algorithm with Cauchy mutation H Wang, H Li, Y Liu, C Li, S Zeng 2007 IEEE congress on evolutionary computation, 4750-4756, 2007 | 344 | 2007 |
Robust multi-exposure image fusion: a structural patch decomposition approach K Ma, H Li, H Yong, Z Wang, D Meng, L Zhang IEEE Transactions on Image Processing 26 (5), 2519-2532, 2017 | 267 | 2017 |
Enhanced differential evolution with adaptive strategies for numerical optimization W Gong, Z Cai, CX Ling, H Li IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41 …, 2010 | 247 | 2010 |
Push and pull search for solving constrained multi-objective optimization problems Z Fan, W Li, X Cai, H Li, C Wei, Q Zhang, K Deb, E Goodman Swarm and evolutionary computation 44, 665-679, 2019 | 192 | 2019 |
A real-coded biogeography-based optimization with mutation W Gong, Z Cai, CX Ling, H Li Applied Mathematics and Computation 216 (9), 2749-2758, 2010 | 180 | 2010 |
An Adaptive Evolutionary Multi-Objective Approach Based on Simulated Annealing HLD Landa-silva Evolutionary Computation 19 (4), 561-595, 2011 | 178 | 2011 |
Adaptive strategy selection in differential evolution for numerical optimization: an empirical study W Gong, Á Fialho, Z Cai, H Li Information Sciences 181 (24), 5364-5386, 2011 | 163 | 2011 |
Biased multiobjective optimization and decomposition algorithm H Li, Q Zhang, J Deng IEEE transactions on cybernetics 47 (1), 52-66, 2016 | 140 | 2016 |
Comparison between MOEA/D and NSGA-III on a set of novel many and multi-objective benchmark problems with challenging difficulties H Li, K Deb, Q Zhang, PN Suganthan, L Chen Swarm and Evolutionary Computation 46, 104-117, 2019 | 136 | 2019 |
MOEA/D with NBI-style Tchebycheff approach for portfolio management Q Zhang, H Li, D Maringer, E Tsang IEEE congress on evolutionary computation, 1-8, 2010 | 111 | 2010 |
Difficulty adjustable and scalable constrained multiobjective test problem toolkit Z Fan, W Li, X Cai, H Li, C Wei, Q Zhang, K Deb, E Goodman Evolutionary computation 28 (3), 339-378, 2020 | 101 | 2020 |
Comparison between MOEA/D and NSGA-II on the multi-objective travelling salesman problem W Peng, Q Zhang, H Li Multi-objective memetic algorithms, 309-324, 2009 | 90 | 2009 |
Hybrid estimation of distribution algorithm for multiobjective knapsack problem H Li, Q Zhang, E Tsang, JA Ford EvoCOP 3004, 145-154, 2004 | 82 | 2004 |
On the use of two reference points in decomposition based multiobjective evolutionary algorithms Z Wang, Q Zhang, H Li, H Ishibuchi, L Jiao Swarm and evolutionary computation 34, 89-102, 2017 | 75 | 2017 |
A multiobjective differential evolution based on decomposition for multiobjective optimization with variable linkages H Li, Q Zhang Parallel Problem Solving from Nature-PPSN IX: 9th International Conference …, 2006 | 75 | 2006 |
Evolutionary multi-objective simulated annealing with adaptive and competitive search direction H Li, D Landa-Silva 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on …, 2008 | 69 | 2008 |