Publications

  • * means equal contribution.

  • + means student under my supervision.

  • Manuscripts are usually the technical reports submitted to journals or conference for possible publications.

  • These materials are presented to ensure a timely dissemination of scholarly and technical work. The copyright of these papers is owned by their publishers. Misuse of any of the posted below may result in plagiarism. By downloading any material from this site, you are assumed to agree with these terms.

Manuscripts

  1. M. Wu\(^+\), K. Li, S. Kwong, Q. Zhang, “Evolutionary Many-Objective Optimization Based on Adversarial Decomposition”, Technical Report, April, 2017. [arXiv]

  2. K. Li, K. Deb, X. Yao, “Integration of Preferences in Decomposition-Based Evolutionary Multi-Objective Optimization”, Technical Report, January, 2017. [arXiv]

  3. T. Chen, K. Li, R. Bahsoon, X. Yao, “FEMOSAA: Feature Guided and Knee Driven Multi-Objective Optimization for Self-Adaptive Software at Runtime”, Technical Report, University of Birmingham, August, 2016, [arXiv]

Journal Papers

  1. R. Cheng, M. Li, K. Li, X. Yao, “Evolutionary Multiobjective Optimization Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection”, IEEE Transactions on Evolutionary Computation (TEVC), accepted for publication. [preprint] [source code] [bibtex]

  2. K. Li, K. Deb, X. Yao, “R-Metric: Evaluating the Performance of Preference-Based Evolutionary Multi-Objective Optimization Using Reference Points”, IEEE Transactions on Evolutionary Computation (TEVC), accepted for publication. [preprint] [Supplementary][source code] [bibtex]

  3. K. Li*, R. Chen*\(^+\), X. Yao, “Dynamic Multi-Objectives Optimization with a Changing Number of Objectives”, IEEE Transactions on Evolutionary Computation (TEVC), accepted for publication. © IEEE [preprint] [Supplementary] [source code] [bibtex]

  4. K. Li, K. Deb, Q. Zhang, Q. Zhang, “Efficient Non-domination Level Update Method for Steady-State Evolutionary Multiobjective Optimization”, IEEE Transactions on Cybernetics (TCYB), 47(9): 2838–2849, 2017. © IEEE [PDF] [Supplementary] [source code] [bibtex]

  5. M. Wu\(^+\), K. Li, S. Kwong, Y. Zhou, Q. Zhang, “Matching-Based Selection with Incomplete Lists for Decomposition Multi-Objective Optimization”, IEEE Transactions on Evolutionary Computation (TEVC), 21(4): 554–568, 2017. © IEEE [PDF] [Supplementary] [source code] [bibtex]

  6. H. Xie, X. Li, T. Wang, L. Chen, K. Li, F.-L. Wang, Y. Cai, Q. Li, H. Min, “Personalized Search for Social Media via Dominating Verbal Context”, Neurocomputing (NEUCOM). 172: 27–37, 2016. © Elsevier [PDF][bibtex]

  7. K. Li, K. Deb, Q. Zhang, S. Kwong, “An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition”, IEEE Transactions on Evolutionary Computation (TEVC). 19(5): 694–716, 2015. © IEEE [PDF] [source code] [PF Sampling Script] [bibtex] (Top 10 popular article in IEEE Transctions of Evolutionary Computation)

  8. K. Li, S. Kwong, Q. Zhang, K. Deb, “Interrelationship-based Selection for Decomposition Multiobjective Optimization”, IEEE Transactions on Cybernetics (TCYB). 45(10): 2076–2088, 2015. © IEEE [PDF] [supplementary] [source code] [bibtex] (Top 5 popular article in IEEE Transctions of Cybernetics)

  9. K. Li, S. Kwong, K. Deb, “A Dual Population Paradigm for Evolutionary Multiobjective Optimization”, Information Sciences (INS). 309: 50–72, 2015. [PDF] [source code] [bibtex]

  10. J. Cao, S. Kwong, R. Wang, X. Li, K. Li, X. Kong, “Class-Specific Soft Voting based Multiple Extreme Learning Machines Ensemble”, Neurocomputing (NEUCOM). 149: 275–284, 2015. © Elsevier [PDF] [bibtex]

  11. K. Li, Q. Zhang, S. Kwong, M. Li, R. Wang, “Stable Matching Based Selection in Evolutionary Multiobjective Optimization”, IEEE Transactions on Evolutionary Computation (TEVC). 18(6): 909–923, 2014. © IEEE [PDF] [JAVA code] [MATLAB code] [bibtex] (Top 10 popular article in IEEE Transctions of Evolutionary Computation)

  12. K. Li, S. Kwong, “A General Framework for Evolutionary Multiobjective Optimization via Manifold Learning”, Neurocomputing (NEUCOM). 146: 65–74, 2014. © Elsevier [PDF] [source code] [bibtex]

  13. M. Li, S. Yang, K. Li, X. Liu, “Evolutionary Algorithms with Segment-based Search for Multiobjective Optimization Problems”, IEEE Transactions on Cybernetics (TCYB). 44(8): 1295–1313, 2014. © IEEE [PDF] [bibtex]

  14. K. Li, Á. Fialho, S. Kwong, Q. Zhang, “Adaptive Operator Selection with Bandits for Multiobjective Evolutionary Algorithm Based on Decomposition”, IEEE Transactions on Evolutionary Computation (TEVC). 18(1): 114–130, 2014. © IEEE [PDF] [supplementary] [source code] [bibtex] (Top 20 popular article in IEEE Transctions of Evolutionary Computation)

  15. K. Li, R. Wang, S. Kwong, J. Cao, “Evolving Extreme Learning Machine Paradigm with Adaptive Operator Selection and Parameter Control”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS). 21(supp02): 143–154, 2013. © World Scientific [PDF] [source code] [bibtex]

  16. K. Li, S. Kwong, R. Wang, K.-S. Tang, K.-F. Man, “Learning Paradigm Based on Jumping Genes: A General Framework for Enhancing Exploration in Evolutionary Multiobjective Optimization”, Information Sciences (INS), 226: 1–22, 2013. © Elsevier [PDF] [source code] [bibtex]

  17. K. Li, S. Kwong, J. Cao, M. Li, J. Zheng, R. Shen, “Achieving Balance Between Proximity and Diversity in Multi-objective Evolutionary Algorithm”, Information Sciences (INS), 182(1): 220–242, 2012. © Elsevier [PDF] [source code] [bibtex]

  18. K. Li, J. Zheng, M. Li, C. Zhou, H. Lv, “A Novel Slicing Based Algorithm to Calculate Hypervolume for Multi-Objective Optimization Problems”, ICIC Express Letters: An International Journal of Research and Surveys, 4(4): 1113–1120, 2010. [PDF] [source code] [bibtex]

Conference Papers

  1. M. Wu, S. Kwong, Y. Jia, K. Li and Q. Zhang, “Adaptive Weights Generation for Decomposition-Based Multi-Objective Optimization Using Gaussian Process Regression”, Proc. of the 18th Annual Conference on Genetic and Evolutionary Computation (GECCO’17), ACM Press: p. 641–648, July 2017. © ACM [PDF] [bibtex]

  2. K. Li, K. Deb, T. Altinoz and X. Yao, “Empirical Investigations of Reference Point Based Methods When Facing a Massively Large Number of Objectives: First Results”, Proc. of the 9th International Conference on Evolutionary Multi-Criterion Optimization (EMO’17), Springer, LNCS, Volume 10173: p. 390-405, March 2017. © Springer [PDF] [bibtex]

  3. K. Li, M. Omidvar, K. Deb, X. Yao, “Variable Interactions in Multi-Objective Optimization Problems”, Proc. of the 14th International Conference on Parallel Problem Solving from Nature (PPSN’16), Springer, LNCS, Volume 9921: p. 399-409, September 2016. © Springer [PDF] [bibtex]

  4. M. Wu\(^+\), S. Kwong, Q. Zhang, K. Li, R. Wang, B. Liu, “Two-Level Stable Matching-Based Selection in MOEA/D”, Proc. of 2015 IEEE Conference on Systems, Mans and Cybernetics (SMC’15), IEEE Press: p. 1720–1725, October 2015. © IEEE [PDF] [bibtex]

  5. K. Li, K. Deb, Q. Zhang, “Evolutionary Multiobjective Optimization With Hybrid Selection Principles”, Proc. of 2015 IEEE Congress on Evolutionary Computation (CEC’15), IEEE Press: p. 900–907, May 2015. © IEEE [PDF] [source code] [bibtex]

  6. K. Li, S. Kwong, R. Wang, J. Cao, I. Rudas, “Multi-Objective Differential Evolution with Self-Navigation”, Proc. of 2012 IEEE International Conference on Systems, Mans and Cybernetics (SMC’12), IEEE Press: p. 508–513, October 2012. © IEEE [PDF] [bibtex]

  7. J. Cao, S. Kwong, R. Wang, K. Li, “A Weighted Voting Method Using Minimum Square Error based on Extreme Learning Machine”, Proc. of 2012 International Conference on Machine Learning and Cybernetics (ICMLC’12), IEEE Press: p. 411–414, July 2012. © IEEE [PDF] [bibtex]

  8. J. Cao, H. Wang, S. Kwong, K. Li, “Combining Interpretable Fuzzy Rule-based Classifiers via Multi-Objective Hierarchical Evolutionary Algorithm”, Proc. of 2011 IEEE International Conference on Systems, Mans and Cybernetics (SMC’11), IEEE Press: p. 1771–1776, October 2011. © IEEE [PDF] [bibtex]

  9. K. Li, S. Kwong, K.-F. Man, “JGBL paradigm: A Novel Strategy to Enhance the Exploration Ability of NSGA-II”, Proc. of the 12th Annual Conference on Genetic and Evolutionary Computation (GECCO’11), ACM Press: p. 99–100, July 2011. © ACM [PDF] [bibtex]

  10. K. Li, Á. Fialho, S. Kwong, “Multi-Objective Differential Evolution with Adaptive Control of Parameters and Operators”, Proc. of the 5th International Conference on Learning and Intelligent OptimizatioN (LION’11), Springer Verlag, LNCS, p. 473–487, January 2011. © Springer [PDF] [bibtex]

  11. M. Li, J. Zheng, K. Li, Q. Yuan, R. Shen, “Enhancing Diversity for Average Ranking Method in Evolutionary Many-Objective Optimization”, Proc. of the 11th International Conference on Parallel Problem Solving from Nature (PPSN’10), Springer Verlag, LNCS, Vol. 6238: p. 647–656, September 2010. © Springer [PDF] [bibtex]

  12. M. Li, J. Zheng, R. Zhen, K. Li, Q. Yuan, “A Grid-based Fitness Strategy for Evolutionary Many-Objective Optimization”, Proc. of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO’10), ACM Press: p. 463–470, July 2010. © ACM [PDF] [bibtex] (Nominated as best paper candidate)

  13. K. Li, J. Zheng, M. Li, C. Zhou, H. Lv, “A Novel Algorithm for Non-dominated Hypervolume-based Multiobjective Optimization”, Proc. of 2009 IEEE International Conference on Systems, Mans and Cybernetics (SMC’09), IEEE Press: p. 5220–5226, December 2009. © IEEE [PDF] [bibtex]

  14. M. Li, J. Zheng, K. Li, J. Wu, G. Xiao, “An Spanning Tree Based Method For Pruning Non-Dominated Solutions in Multi-Objective Optimization Problems”, Proc. of 2009 IEEE International Conference on Systems, Mans and Cybernetics (SMC’09), IEEE Press: p. 4882–4887, December 2009. © IEEE [PDF] [bibtex]

  15. C. Zhou, J. Zheng, K. Li, H. Lv, “Objective Reduction based on the Least Square Method for Large-dimensional Multiobjective Optimization Problem”, Proc. of the 5th International Conference on Natural Computation (ICNC’09), IEEE Press: p. 350–354, August 2009. © IEEE [PDF] [bibtex]

  16. H. Lv, J. Zheng, J. Wu, C. Zhou, K. Li, “The Convergence Analysis of Genetic Algorithm based on Space Mating”, Proc. of the 5th International Conference on Natural Computation (ICNC’09), IEEE Press: p. 557–562, August 2009. © IEEE [PDF] [bibtex]

  17. K. Li, J. Zheng, “An Improved Multi-objective Evolutionary Algorithm based on Differential Evolution”, Proc. of 2009 WRI World Congress on Computer Science and Information Engineering (CSIE’09), IEEE Press: p. 825–830, 31 March – 2 April 2009. © IEEE [PDF] [bibtex]