Algorithm selection for black-box continuous optimization problems: A survey on methods and challenges MA Muñoz, Y Sun, M Kirley, SK Halgamuge Information Sciences 317, 224-245, 2015 | 233 | 2015 |
A recursive decomposition method for large scale continuous optimization Y Sun, M Kirley, SK Halgamuge IEEE Transactions on Evolutionary Computation 22 (5), 647-661, 2017 | 193 | 2017 |
Extended differential grouping for large scale global optimization with direct and indirect variable interactions Y Sun, M Kirley, SK Halgamuge Proceedings of the 2015 annual conference on genetic and evolutionary …, 2015 | 150 | 2015 |
Decomposition for large-scale optimization problems with overlapping components Y Sun, X Li, A Ernst, MN Omidvar 2019 IEEE congress on evolutionary computation (CEC), 326-333, 2019 | 90 | 2019 |
Improving mmd-gan training with repulsive loss function W Wang, Y Sun, S Halgamuge Seventh International Conference on Learning Representations (ICLR) 2019, 2019 | 83 | 2019 |
Adaptive threshold parameter estimation with recursive differential grouping for problem decomposition Y Sun, MN Omidvar, M Kirley, X Li Proceedings of the genetic and evolutionary computation conference, 889-896, 2018 | 68 | 2018 |
Quantifying variable interactions in continuous optimization problems Y Sun, M Kirley, SK Halgamuge IEEE Transactions on Evolutionary Computation 21 (2), 249-264, 2016 | 49 | 2016 |
Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation J Bi, Y Ma, J Wang, Z Cao, J Chen, Y Sun, YM Chee Advances in Neural Information Processing Systems, 2022 | 46 | 2022 |
Generalization of machine learning for problem reduction: a case study on travelling salesman problems Y Sun, A Ernst, X Li, J Weiner OR Spectrum 43, 607–633, 2021 | 33 | 2021 |
On the selection of fitness landscape analysis metrics for continuous optimization problems Y Sun, SK Halgamuge, M Kirley, MA Munoz 7th International Conference on Information and Automation for …, 2014 | 33 | 2014 |
Using statistical measures and machine learning for graph reduction to solve maximum weight clique problems Y Sun, X Li, A Ernst IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (5), 1746 …, 2021 | 32 | 2021 |
Learning primal heuristics for mixed integer programs Y Shen, Y Sun, A Eberhard, X Li 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 26 | 2021 |
Boosting Ant Colony Optimization via Solution Prediction and Machine Learning Y Sun, S Wang, Y Shen, X Li, AT Ernst, M Kirley Computers & Operations Research, 2022 | 25 | 2022 |
Enhancing Column Generation by a Machine-Learning-Based Pricing Heuristic for Graph Coloring Y Shen, Y Sun, X Li, A Eberhard, A Ernst The Thirty-Six AAAI Conference on Artificial Intelligence (AAAI-22), 2022 | 22 | 2022 |
On the Efficiency of K-Means Clustering: Evaluation, Optimization, and Algorithm Selection S Wang, Y Sun, Z Bao Proceedings of the VLDB Endowment, 2020 | 19 | 2020 |
Public transport planning: When transit network connectivity meets commuting demand S Wang, Y Sun, C Musco, Z Bao Proceedings of the 2021 International Conference on Management of Data, 1906 …, 2021 | 17 | 2021 |
Cooperative co-evolution with online optimizer selection for large-scale optimization Y Sun, M Kirley, X Li Proceedings of the Genetic and Evolutionary Computation Conference, 1079-1086, 2018 | 14 | 2018 |
Solving the Maximum Edge Disjoint Path Problem Using a Modified Lagrangian Particle Swarm Optimisation Hybrid J Weiner, AT Ernst, X Li, Y Sun, K Deb European Journal of Operational Research 293 (3), 847-862, 2021 | 12 | 2021 |
An improved merge search algorithm for the constrained pit problem in open-pit mining A Kenny, X Li, AT Ernst, Y Sun Proceedings of the Genetic and Evolutionary Computation Conference, 294-302, 2019 | 8 | 2019 |
Adaptive solution prediction for combinatorial optimization Y Shen, Y Sun, X Li, A Eberhard, A Ernst European Journal of Operational Research 309 (3), 1392-1408, 2023 | 7 | 2023 |