| A many-objective evolutionary algorithm using a one-by-one selection strategy Y Liu, D Gong, J Sun, Y Jin IEEE Transactions on Cybernetics 47 (9), 2689-2702, 2017 | 238 | 2017 |
| A multimodal multiobjective evolutionary algorithm using two-archive and recombination strategies Y Liu, GG Yen, D Gong IEEE Transactions on Evolutionary Computation 23 (4), 660-674, 2018 | 200 | 2018 |
| Many-objective evolutionary optimization based on reference points Y Liu, D Gong, X Sun, Y Zhang Applied Soft Computing 50, 344-355, 2017 | 125 | 2017 |
| A double-niched evolutionary algorithm and its behavior on polygon-based problems Y Liu, H Ishibuchi, Y Nojima, N Masuyama, K Shang Parallel Problem Solving from Nature–PPSN XV: 15th International Conference …, 2018 | 104 | 2018 |
| Adapting reference vectors and scalarizing functions by growing neural gas to handle irregular Pareto fronts Y Liu, H Ishibuchi, N Masuyama, Y Nojima IEEE Transactions on Evolutionary Computation 24 (3), 439-453, 2019 | 103 | 2019 |
| Discrete evolutionary multi-objective optimization for energy-efficient blocking flow shop scheduling with setup time Y Han, J Li, H Sang, Y Liu, K Gao, Q Pan Applied Soft Computing 93, 106343, 2020 | 102 | 2020 |
| Handling Imbalance Between Convergence and Diversity in the Decision Space in Evolutionary Multi-Modal Multi-Objective Optimization Y Liu, H Ishibuchi, GG Yen, Y Nojima, N Masuyama IEEE Transactions on Evolutionary Computation, 2019 | 100 | 2019 |
| Distributed flow shop scheduling with sequence-dependent setup times using an improved iterated greedy algorithm X Han, Y Han, Q Chen, J Li, H Sang, Y Liu, Q Pan, Y Nojima Complex System Modeling and Simulation 1 (3), 198-217, 2021 | 96 | 2021 |
| An improved iterated greedy algorithm for the energy-efficient blocking hybrid flow shop scheduling problem HX Qin, YY Han, B Zhang, LL Meng, YP Liu, QK Pan, DW Gong Swarm and Evolutionary Computation 69, 100992, 2022 | 68 | 2022 |
| Meta-heuristic algorithm for solving vehicle routing problems with time windows and synchronized visit constraints in prefabricated systems J Li, Y Han, P Duan, Y Han, B Niu, C Li, Z Zheng, Y Liu Journal of Cleaner Production 250, 119464, 2020 | 67 | 2020 |
| A collaborative iterative greedy algorithm for the scheduling of distributed heterogeneous hybrid flow shop with blocking constraints HX Qin, YY Han, YP Liu, JQ Li, QK Pan Expert Systems with Applications 201, 117256, 2022 | 41 | 2022 |
| A new R2 indicator for better hypervolume approximation K Shang, H Ishibuchi, ML Zhang, Y Liu Proceedings of the Genetic and Evolutionary Computation Conference, 745-752, 2018 | 37 | 2018 |
| An effective iterative greedy algorithm for distributed blocking flowshop scheduling problem with balanced energy costs criterion X Han, Y Han, B Zhang, H Qin, J Li, Y Liu, D Gong Applied Soft Computing 129, 109502, 2022 | 36 | 2022 |
| A meta-objective approach for many-objective evolutionary optimization D Gong, Y Liu, GG Yen Evolutionary computation 28 (1), 1-25, 2020 | 33 | 2020 |
| Searching for local pareto optimal solutions: A case study on polygon-based problems Y Liu, H Ishibuchi, Y Nojima, N Masuyama, Y Han 2019 IEEE Congress on Evolutionary Computation (CEC), 896-903, 2019 | 28 | 2019 |
| Intelligent optimization under blocking constraints: A novel iterated greedy algorithm for the hybrid flow shop group scheduling problem H Qin, Y Han, Y Wang, Y Liu, J Li, Q Pan Knowledge-Based Systems 258, 109962, 2022 | 24 | 2022 |
| Topological clustering via adaptive resonance theory with information theoretic learning N Masuyama, CK Loo, H Ishibuchi, N Kubota, Y Nojima, Y Liu IEEE Access 7, 76920-76936, 2019 | 24 | 2019 |
| Parallel many-objective evolutionary optimization using objectives decomposition DW Gong, YP Liu, XY Sun, Y Han Acta Automatica Sinica 41 (8), 1438-1451, 2015 | 21 | 2015 |
| Indicator-based set evolution particle swarm optimization for many-objective problems X Sun, Y Chen, Y Liu, D Gong Soft Computing 20, 2219-2232, 2016 | 18 | 2016 |
| On the normalization in evolutionary multi-modal multi-objective optimization Y Liu, H Ishibuchi, GG Yen, Y Nojima, N Masuyama, Y Han 2020 IEEE congress on evolutionary computation (CEC), 1-8, 2020 | 17 | 2020 |
Yu-Yan HanSchool of Information and Electrical Engineering, China University of Mining and TechnologyVerified email at cumt.edu.cn
