| Development and investigation of efficient GA/PSO-hybrid algorithm applicable to real-world design optimization S Jeong, S Hasegawa, K Shimoyama, S Obayashi IEEE Computational Intelligence Magazine 4 (3), 36-44, 2009 | 117 | 2009 |
| Global sensitivity analysis via multi-fidelity polynomial chaos expansion PS Palar, LR Zuhal, K Shimoyama, T Tsuchiya Reliability Engineering & System Safety 170, 175-190, 2018 | 79 | 2018 |
| New constraint-handling method for multi-objective and multi-constraint evolutionary optimization A Oyama, K Shimoyama, K Fujii Transactions of the Japan Society for Aeronautical and Space Sciences 50 …, 2007 | 71 | 2007 |
| Expected improvement of penalty-based boundary intersection for expensive multiobjective optimization N Namura, K Shimoyama, S Obayashi IEEE Transactions on Evolutionary Computation 21 (6), 898-913, 2017 | 70 | 2017 |
| Updating kriging surrogate models based on the hypervolume indicator in multi-objective optimization K Shimoyama, K Sato, S Jeong, S Obayashi Journal of Mechanical Design 135 (9), 094503, 2013 | 56 | 2013 |
| On efficient global optimization via universal Kriging surrogate models PS Palar, K Shimoyama Structural and Multidisciplinary Optimization 57, 2377-2397, 2018 | 54 | 2018 |
| A new efficient and useful robust optimization approach-design for multi-objective six sigma K Shimoyama, A Oyama, K Fujii 2005 IEEE Congress on Evolutionary Computation 1, 950-957, 2005 | 54 | 2005 |
| A comparative study of multi-objective expected improvement for aerodynamic design LR Zuhal, PS Palar, K Shimoyama Aerospace Science and Technology 91, 548-560, 2019 | 50 | 2019 |
| Kriging-surrogate-based optimization considering expected hypervolume improvement in non-constrained many-objective test problems K Shimoyama, S Jeong, S Obayashi 2013 IEEE Congress on Evolutionary Computation, 658-665, 2013 | 50 | 2013 |
| Topology optimization of fluid problems using genetic algorithm assisted by the Kriging model M Yoshimura, K Shimoyama, T Misaka, S Obayashi International Journal for Numerical Methods in Engineering 109 (4), 514-532, 2017 | 49 | 2017 |
| Aerodynamic multiobjective design exploration of a flapping airfoil using a navier-stokes solver A Oyama, Y Okabe, K Shimoyama, K Fujii Journal of Aerospace Computing, Information, and Communication 6 (3), 256-270, 2009 | 47 | 2009 |
| Development of multi-objective six sigma approach for robust design optimization K Shimoyama, A Oyama, K Fujii Journal of aerospace computing, information, and communication 5 (8), 215-233, 2008 | 46 | 2008 |
| On the use of surrogate models in engineering design optimization and exploration: The key issues PS Palar, RP Liem, LR Zuhal, K Shimoyama Proceedings of the genetic and evolutionary computation conference companion …, 2019 | 44 | 2019 |
| Kriging-model-based uncertainty quantification in computational fluid dynamics S Kawai, K Shimoyama 32nd AIAA Applied Aerodynamics Conference, 2737, 2014 | 42 | 2014 |
| New constraint-handling method for multi-objective multi-constraint evolutionary optimization and its application to space plane design A Oyama Evolutionary and deterministic methods for design, optimization and control …, 2005 | 42 | 2005 |
| Multi-objective design exploration and its applications S Obayashi, SK Jeong, K Shimoyama, K Chiba, H Morino International Journal of Aeronautical and Space Sciences 11 (4), 247-265, 2010 | 38 | 2010 |
| Review of data mining for multi-disciplinary design optimization S Jeong, K Shimoyama Proceedings of the Institution of Mechanical Engineers, Part G: Journal of …, 2011 | 37 | 2011 |
| Practical implementation of robust design assisted by response surface approximation and visual data-mining K Shimoyama, JN Lim, S Jeong, S Obayashi, M Koishi | 37 | 2009 |
| Gaussian process surrogate model with composite kernel learning for engineering design P Satria Palar, L Rizki Zuhal, K Shimoyama AIAA journal 58 (4), 1864-1880, 2020 | 36 | 2020 |
| A multi-point mechanism of expected hypervolume improvement for parallel multi-objective bayesian global optimization K Yang, PS Palar, M Emmerich, K Shimoyama, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference, 656-663, 2019 | 32 | 2019 |
