| Evolutionary many-objective optimization: A short review H Ishibuchi, N Tsukamoto, Y Nojima 2008 IEEE congress on evolutionary computation (IEEE world congress on …, 2008 | 1307 | 2008 |
| Modified distance calculation in generational distance and inverted generational distance H Ishibuchi, H Masuda, Y Tanigaki, Y Nojima Evolutionary Multi-Criterion Optimization: 8th International Conference, EMO …, 2015 | 642 | 2015 |
| Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes H Ishibuchi, Y Setoguchi, H Masuda, Y Nojima IEEE Transactions on Evolutionary Computation 21 (2), 169-190, 2016 | 583 | 2016 |
| Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning H Ishibuchi, Y Nojima International Journal of Approximate Reasoning 44 (1), 4-31, 2007 | 495 | 2007 |
| A review of the application of multiobjective evolutionary fuzzy systems: Current status and further directions M Fazzolari, R Alcala, Y Nojima, H Ishibuchi, F Herrera IEEE Transactions on Fuzzy systems 21 (1), 45-65, 2012 | 374 | 2012 |
| Behavior of multiobjective evolutionary algorithms on many-objective knapsack problems H Ishibuchi, N Akedo, Y Nojima IEEE Transactions on Evolutionary Computation 19 (2), 264-283, 2014 | 329 | 2014 |
| A framework for large-scale multiobjective optimization based on problem transformation H Zille, H Ishibuchi, S Mostaghim, Y Nojima IEEE Transactions on Evolutionary Computation 22 (2), 260-275, 2017 | 307 | 2017 |
| How to specify a reference point in hypervolume calculation for fair performance comparison H Ishibuchi, R Imada, Y Setoguchi, Y Nojima Evolutionary computation 26 (3), 411-440, 2018 | 236 | 2018 |
| Evolutionary many-objective optimization by NSGA-II and MOEA/D with large populations H Ishibuchi, Y Sakane, N Tsukamoto, Y Nojima 2009 IEEE International Conference on Systems, Man and Cybernetics, 1758-1763, 2009 | 210 | 2009 |
| Performance comparison of NSGA-II and NSGA-III on various many-objective test problems H Ishibuchi, R Imada, Y Setoguchi, Y Nojima 2016 IEEE Congress on Evolutionary Computation (CEC), 3045-3052, 2016 | 203 | 2016 |
| Simultaneous use of different scalarizing functions in MOEA/D H Ishibuchi, Y Sakane, N Tsukamoto, Y Nojima Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 167 | 2010 |
| Adaptation of scalarizing functions in MOEA/D: An adaptive scalarizing function-based multiobjective evolutionary algorithm H Ishibuchi, Y Sakane, N Tsukamoto, Y Nojima Evolutionary Multi-Criterion Optimization, 438-452, 2009 | 158 | 2009 |
| Many-objective test problems to visually examine the behavior of multiobjective evolution in a decision space H Ishibuchi, Y Hitotsuyanagi, N Tsukamoto, Y Nojima Parallel Problem Solving from Nature–PPSN XI, 91-100, 2011 | 148 | 2011 |
| 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 | 147 | 2019 |
| Reference point specification in inverted generational distance for triangular linear Pareto front H Ishibuchi, R Imada, Y Setoguchi, Y Nojima IEEE Transactions on Evolutionary Computation 22 (6), 961-975, 2018 | 141 | 2018 |
| Handling imbalance between convergence and diversity in the decision space in evolutionary multimodal multiobjective optimization Y Liu, H Ishibuchi, GG Yen, Y Nojima, N Masuyama IEEE Transactions on Evolutionary Computation 24 (3), 551-565, 2019 | 140 | 2019 |
| 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 | 122 | 2018 |
| 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 | 121 | 2021 |
| Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions R Alcalá, Y Nojima, F Herrera, H Ishibuchi Soft Computing-A Fusion of Foundations, Methodologies and Applications 15 …, 2011 | 121 | 2011 |
| A study on performance evaluation ability of a modified inverted generational distance indicator H Ishibuchi, H Masuda, Y Nojima Proceedings of the 2015 annual conference on genetic and evolutionary …, 2015 | 117 | 2015 |
Hisao IshibuchiSouthern University of Science and TechnologyVerified email at sustech.edu.cn
