Drift analysis and average time complexity of evolutionary algorithms J He, X Yao Artificial Intelligence 127 (1), 57-85, 2001 | 486 | 2001 |
A study of drift analysis for estimating computation time of evolutionary algorithms J He, X Yao Natural Computing 3 (1), 21-35, 2004 | 283 | 2004 |
Time complexity of evolutionary algorithms for combinatorial optimization: A decade of results PS Oliveto, J He, X Yao International Journal of Automation and Computing 4 (3), 281-293, 2007 | 279 | 2007 |
From an individual to a population: An analysis of the first hitting time of population-based evolutionary algorithms J He, X Yao Evolutionary Computation, IEEE Transactions on 6 (5), 495-511, 2002 | 227 | 2002 |
Towards an analytic framework for analysing the computation time of evolutionary algorithms J He, X Yao Artificial Intelligence 145 (1-2), 59-97, 2003 | 221 | 2003 |
Approximating covering problems by randomized search heuristics using multi-objective models* T Friedrich, J He, N Hebbinghaus, F Neumann, C Witt Evolutionary Computation 18 (4), 617-633, 2010 | 178 | 2010 |
A hybrid artificial immune system and Self Organising Map for network intrusion detection ST Powers, J He Information Sciences 178 (15), 3024-3042, 2008 | 178 | 2008 |
Evolutionary programming using a mixed mutation strategy H Dong, J He, H Huang, W Hou Information Sciences 177 (1), 312-327, 2007 | 137 | 2007 |
On the convergence rates of genetic algorithms J He, L Kang Theoretical Computer Science 229 (1-2), 23-39, 1999 | 130 | 1999 |
Analysis of the -EA for Finding Approximate Solutions to Vertex Cover Problems PS Oliveto, J He, X Yao Evolutionary Computation, IEEE Transactions on 13 (5), 1006-1029, 2009 | 111 | 2009 |
Conditions for the convergence of evolutionary algorithms J He, X Yu Journal of systems architecture 47 (7), 601-612, 2001 | 91 | 2001 |
A new approach for analyzing average time complexity of population-based evolutionary algorithms on unimodal problems T Chen, J He, G Sun, G Chen, X Yao Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 39 …, 2009 | 90 | 2009 |
A note on problem difficulty measures in black-box optimization: Classification, realizations and predictability J He, C Reeves, C Witt, X Yao Evolutionary computation 15 (4), 435-443, 2007 | 82 | 2007 |
Average convergence rate of evolutionary algorithms J He, G Lin IEEE Transactions on Evolutionary Computation 20 (2), 316-321, 2016 | 80 | 2016 |
A scalar projection and angle-based evolutionary algorithm for many-objective optimization problems Y Zhou, Y Xiang, Z Chen, J He, J Wang IEEE transactions on cybernetics 49 (6), 2073-2084, 2018 | 67 | 2018 |
Multi-objective and MGG evolutionary algorithm for constrained optimization Y Zhou, Y Li, J He, L Kang The 2003 Congress on Evolutionary Computation, 2003. CEC'03. 1, 1-5, 2003 | 63 | 2003 |
Analysis of population-based evolutionary algorithms for the vertex cover problem PS Oliveto, J He, X Yao 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on …, 2008 | 59 | 2008 |
Solving equations by hybrid evolutionary computation techniques J He, J Xu, X Yao Evolutionary Computation, IEEE Transactions on 4 (3), 295-304, 2000 | 59 | 2000 |
On the easiest and hardest fitness functions J He, T Chen, X Yao IEEE Transactions on Evolutionary Computation 19 (2), 295-305, 2015 | 58 | 2015 |
A runtime analysis of evolutionary algorithms for constrained optimization problems Y Zhou, J He Evolutionary Computation, IEEE Transactions on 11 (5), 608-619, 2007 | 55 | 2007 |