| Faster exact algorithms for computing expected hypervolume improvement I Hupkens, A Deutz, K Yang, M Emmerich international conference on evolutionary multi-criterion optimization, 65-79, 2015 | 42 | 2015 |
| A multicriteria generalization of bayesian global optimization M Emmerich, K Yang, A Deutz, H Wang, CM Fonseca Advances in Stochastic and Deterministic Global Optimization, 229-242, 2016 | 37 | 2016 |
| Multi-objective Bayesian global optimization using expected hypervolume improvement gradient K Yang, M Emmerich, A Deutz, T Bäck Swarm and evolutionary computation 44, 945-956, 2019 | 32 | 2019 |
| Computing 3-D expected hypervolume improvement and related integrals in asymptotically optimal time K Yang, M Emmerich, A Deutz, CM Fonseca International Conference on Evolutionary Multi-Criterion Optimization, 685-700, 2017 | 25 | 2017 |
| Preference-based multiobjective optimization using truncated expected hypervolume improvement K Yang, L Li, A Deutz, T Back, M Emmerich 2016 12th International Conference on Natural Computation, Fuzzy Systems and …, 2016 | 24 | 2016 |
| Efficient computation of expected hypervolume improvement using box decomposition algorithms K Yang, M Emmerich, A Deutz, T Bäck Journal of Global Optimization 75 (1), 3-34, 2019 | 22 | 2019 |
| 2015 IEEE Congress on Evolutionary Computation (CEC) H Li, ML Wong IEEE, 2015 | 20 | 2015 |
| Truncated expected hypervolume improvement: Exact computation and application K Yang, A Deutz, Z Yang, T Back, M Emmerich 2016 IEEE Congress on Evolutionary Computation (CEC), 4350-4357, 2016 | 18 | 2016 |
| A review: Prognostics and health management in automotive and aerospace DV Nguyen, M Kefalas, K Yang, A Apostolidis, M Olhofer, S Limmer, ... International Journal of Prognostics and Health Management 10 (2), 35, 2019 | 15 | 2019 |
| Expected Hypervolume Improvement Algorithm for PID Controller Tuning and the Multiobjective Dynamical Control of a Biogas Plant K Yang, D Gaida, T Bäck, M Emmerich Evolutionary Computation (CEC), 2015 IEEE Congress on, 1934 - 1942, 2015 | 13 | 2015 |
| A new approach to target region based multiobjective evolutionary algorithms Y Wang, L Li, K Yang, MTM Emmerich 2017 IEEE Congress on Evolutionary Computation (CEC), 1757-1764, 2017 | 12 | 2017 |
| Power distribution network reconfiguration by evolutionary integer programming K Yang, MTM Emmerich, R Li, J Wang, T Bäck International conference on parallel problem solving from nature, 11-23, 2014 | 9 | 2014 |
| SMS-EMOA with multiple dynamic reference points Z Yang, H Wang, K Yang, T Back, M Emmerich Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), 2016 …, 2016 | 6 | 2016 |
| Modeling and Prediction of Remaining Useful Lifetime for Maintenance Scheduling Optimization of a Car Fleet D Van Nguyen, S Limmer, K Yang, M Olhofer, T Bäck International Journal of Performability Engineering 15 (9), 2318, 2019 | 5 | 2019 |
| Towards single-and multiobjective bayesian global optimization for mixed integer problems K Yang, K van der Blom, T Bäck, M Emmerich AIP Conference Proceedings 2070 (1), 020044, 2019 | 5 | 2019 |
| Infill criteria for multiobjective Bayesian optimization MTM Emmerich, K Yang, AH Deutz High-Performance Simulation-Based Optimization, 3-16, 2020 | 4 | 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 | 4 | 2019 |
| Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvement PS Palar, K Yang, K Shimoyama, M Emmerich, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference, 1333-1340, 2018 | 3 | 2018 |
| Towards multi-objective mixed integer evolution strategies K van der Blom, K Yang, T Bäck, M Emmerich AIP Conference Proceedings 2070 (1), 020046, 2019 | 2 | 2019 |
| Multi-objective Bayesian global optimization for continuous problems and applications K Yang Leiden University, 2017 | 2 | 2017 |
Michael EmmerichAssociate Professor, LIACS, Leiden University & Lead AI Scientist at SILO.AIVerified email at liacs.nl
