Technical Reports

  1. None!

Submitted to Journals

  1. None!

Thesis

Ph.D. Thesis

  1. W. Gong, Differential evolution algorithm and its application in clustering analysis, China University of Geosciences, 2010.5. (in Chinese with English abstract)

Master Thesis

  1. W. Gong, Research on Evolutionary Kalman Filter and Its Application, China University of Geosciences, 2007.5. (in Chinese with English abstract)

Journal Publications

  1. Y. Li, X. Wu, W. Gong (corresponding author), M. Xu, Y. Wang, and Q. Gu, Evolutionary competitive multiobjective multitasking: One-Pass optimization of heterogeneous Pareto solutions, IEEE Transactions on Evolutionary Computation. Dec. 2024, Accepted. [source code]
  2. Y. Wang, C. Hu, X. Wu, Z. Zhou, X. Yan, and W. Gong, Utilizing feasible non-dominated solution information for constrained multi-objective optimization, Information Sciences. Dec. 2024, Accepted. [source code]
  3. Y. Li, D. Li, W. Gong (corresponding author), and Q. Gu, Multiobjective multitask optimization via diversity and convergence oriented knowledge transfer, IEEE Transactions on Systems, Man, and Cybernetics: Systems. Dec. 2024, Accepted. [source code]
  4. C. Luo, X. Li, W. Gong, and L. Gao, Affinity propagation hierarchical memetic algorithm for multimodal multi-objective flexible job shop scheduling with variable speed, IEEE Transactions on Evolutionary Computation. Dec. 2024, Accepted. [source code]
  5. Y. Li, W. Gong (corresponding author), and Q. Gu, Transfer task-averaged natural gradient for efficient many-task optimization, IEEE Transactions on Evolutionary Computation. Sept. 2024, Accepted. [source code]
  6. Y. Wang, C. Hu, F. Ming, Y. Li, W. Gong, and L. Gao, A diversity-enhanced tri-stage framework for constrained multi-objective optimization, IEEE Transactions on Evolutionary Computation. Sept. 2024, Accepted. [source code]
  7. F. Ming, B. Xue, M. Zhang, W. Gong (corresponding author), and H. Zhen, Constrained multi-objective optimization via relaxations on both constraints and objectives, IEEE Transactions on Artificial Intelligence. Aug. 2024, Accepted. [source code]
  8. T. Zhang, W. Gong (corresponding author), and Y. Li, Multitask differential evolution with adaptive dual knowledge transfer, Applied Soft Computing. July 2024, Accepted. [source code]
  9. F. Ming, W. Gong (corresponding author), H. Zhen, L. Wang, L. Gao, Constrained multi-objective optimization evolutionary algorithm for real-world continuous mechanical design problems, Engineering Applications of Artificial Intelligence. May 2024, Accepted. [source code]
  10. R. Li, L. Wang, W. Gong (corresponding author), and F. Ming, An evolutionary multitasking memetic algorithm for multi-objective distributed heterogeneous welding flow shop scheduling, IEEE Transactions on Evolutionary Computation. April 2024, Accepted. [source code]
  11. T. Zhang, D. Li, Y. Li, and W. Gong (corresponding author), Constrained multitasking optimization via co-evolution and domain adaptation, Swarm and Evolutionary Computation. April 2024, Accepted. [source code]
  12. F. Ming, W. Gong (corresponding author), and Y. Jin, Growing neural gas network-based surrogate-assisted Pareto set learning for multimodal multi-objective optimization, Swarm and Evolutionary Computation. March 2024, Accepted. [source code]
  13. X. Chu, F. Ming, and W. Gong (corresponding author), Competitive multitasking for computational resource allocation in evolutionary constrained multi-objective optimization, IEEE Transactions on Evolutionary Computation. March 2024, Accepted. [source code]
  14. S. Li, W. Gong (corresponding author), R. Lim, Z. Liao, and Q. Gu, Evolutionary multitasking for solving nonlinear equation systems, Information Sciences. Jan. 2024, Accepted. [source code]
  15. Y. Li and W. Gong (corresponding author), Multiobjective multitask optimization with multiple knowledge types and transfer adaptation, IEEE Transactions on Evolutionary Computation. Jan. 2024, Accepted. [source code]
  16. Y. Li, W. Gong (corresponding author), Z. Hu, and S. Li, A competitive and cooperative evolutionary framework for ensemble of constraint handling techniques, IEEE Transactions on Systems, Man, and Cybernetics: Systems. Dec 2023, Accepted. [source code]
  17. Y. Wang, K. Huang, W. Gong (corresponding author), and F. Ming, Bi-directional search based on constraint relaxation for constrained multi-objective optimization problems with large infeasible regions, Expert Systems With Applications. Nov. 2023, Accepted. [source code]
  18. Y. Li, W. Gong (corresponding author), and S. Li, Multitask evolution strategy with knowledge-guided external sampling, IEEE Transactions on Evolutionary Computation. Nov. 2023, Accepted. [source code]
  19. R. Li, W. Gong (corresponding author), L. Wang, C. Lu, Z. Pan, and X. Zhuang, Double DQN-based coevolution for green distributed heterogeneous hybrid flowshop scheduling with multiple priorities of jobs, IEEE Transactions on Automation Science and Engineering. Oct. 2023, Accepted. [source code]
  20. S. Cao, R. Li, W. Gong (corresponding author), and C. Lu, Inverse model and adaptive neighborhood search based cooperative optimizer for energy-efficient distributed flexible job shop scheduling, Swarm and Evolutionary Computation. Oct. 2023, Accepted. [source code]
  21. X. Cheng, W. Gong (corresponding author), F. Ming, and X. Zhu, Multimodal multi-objective optimization via determinantal point processes assisted evolutionary algorithm, Neural Computing and Applications. Oct. 2023, Accepted. [source code]
  22. Z. Hu, W. Gong (corresponding author), W. Pderycz, and Y. Li, Deep reinforcement learning assisted co-evolutionary differential evolution for constrained optimization, Swarm and Evolutionary Computation. August 2023, Accepted. [source code]
  23. R. Li, W. Gong (corresponding author), L. Wang, C. Lu, and C. Dong, Co-evolution with deep reinforcement learning for energy-aware distributed heterogeneous flexible job shop scheduling, IEEE Transactions on Systems, Man, and Cybernetics: Systems. August 2023, Accepted. [source code]
  24. C. Luo, W. Gong (corresponding author), and C. Lu, Knowledge-driven two-stage memetic algorithm for energy-efficient flexible job shop scheduling with machine breakdowns, Expert Systems With Applications. August 2023, Accepted. [source code]
  25. F. Ming, W. Gong (corresponding author), and Y. Jin, Even search in a promising region for constrained multi-objective optimization, IEEE/CAA Journal of Automatica Sinica. July 2023, Accepted. [source code]
  26. F. Ming, W. Gong (corresponding author), L. Wang, and L.Gao, A constraint-handling technique for decomposition-based constrained many-objective evolutionary algorithms, IEEE Transactions on Systems, Man, and Cybernetics: Systems. July 2023, Accepted. [source code]
  27. F. Ming, W. Gong (corresponding author), S. Li, L. Wang, and Z. Liao, Handling constrained many-objective optimization problems via determinantal point processes, Information Sciences. May 2023, Accepted. [source code]
  28. R. Li, W. Gong (corresponding author), L. Wang, C. Lu, and X. Zhuang, Surprisingly popular-based adaptive memetic algorithm for energy-efficient distributed flexible job shop scheduling, IEEE Transactions on Cybernetics. May 2023, Accepted. [source code]
  29. F. Ming, W. Gong (corresponding author), L. Wang, and Y. Jin, Constrained multi-objective optimization with deep reinforcement learning assisted operator selection, IEEE/CAA Journal of Automatica Sinica. May 2023, Accepted. [source code]
  30. C. Luo, W. Gong (corresponding author), R. Li, and C. Lu, Problem-specific knowledge MOEA/D for energy-efficient scheduling of distributed permutation flow shop in heterogeneous factories, Engineering Applications of Artificial Intelligence. May 2023, Accepted. [source code]
  31. S. Li, W. Gong (corresponding author), L. Wang, and Q. Gu, Evolutionary multitasking via reinforcement learning, IEEE Transactions on Emerging Topics in Computational Intelligence. May 2023, Accepted. [source code]
  32. C. Xing, W. Gong (corresponding author), and S. Li, Adaptive archive-based multifactorial evolutionary algorithm for constrained multitasking optimization, Applied Soft Computing. May 2023, Accepted. [source code]
  33. H. Zhen, S. Xiong, W. Gong (corresponding author), and L. Wang, Neighborhood evolutionary sampling with dynamic repulsion for expensive multimodal optimization, Information Sciences. Feb. 2023, Accepted. [source code]
  34. Z. Liao W. Gong (corresponding author), and S. Li, Two-stage reinforcement learning-based differential evolution for solving nonlinear equations, IEEE Transactions on Systems, Man, and Cybernetics: Systems. Feb. 2023, Accepted.
  35. F. Ming, W. Gong (corresponding author), and L. Gao, Adaptive auxiliary task selection for multitasking-assisted constrained multi-objective optimization, IEEE Computational Intelligence Magazine. Jan. 2023, Accepted. [source code]
  36. S. Li, W. Gong (corresponding author), Q. Gu, and Z. Liao, Adaptive dual niching-based differential evolution with resource reallocation for nonlinear equation systems, Neural Computing and Applications. Jan. 2023, Accepted. [source code]
  37. Y. Li, W. Gong (corresponding author), S. Li, Evolutionary competitive multitasking optimization via improved adaptive differential evolution, Expert Systems With Applications. 217 (2023) 119550. [source code]
  38. F. Ming, W. Gong (corresponding author), L. Wang, and L. Gao, Constrained multi-objective optimization via multitasking and knowledge transfer, IEEE Transactions on Evolutionary Computation. Dec., 2022. Accepted. [source code]
  39. F. Ming, W. Gong (corresponding author), L. Wang, and L. Gao, Balancing convergence and diversity in objective and decision spaces for multimodal multi-objective optimization, IEEE Transactions on Emerging Topics in Computational Intelligence. Nov., 2022. Accepted. [source code]
  40. F. Ming, W. Gong (corresponding author), Y. Yang, and Z. Liao, Constrained multimodal multi-objective optimization: Test problem construction and algorithm design, Swarm and Evolutionary Computation. Nov., 2022. Accepted. [source code]
  41. Z. Zhang, Y. Cai, and W. Gong (corresponding author), Semi-supervised learning with graph convolutional extreme learning machines, Expert Systems With Applications. Oct., 2022. Accepted. [source code]
  42. Y. Li, W. Gong (corresponding author), and S. Li, Multi-task optimization via an adaptive solver multitasking evolutionary framework, Information Sciences. Oct., 2022. Accepted. [source code]
  43. C. Qin, F. Ming, W. Gong (corresponding author), and Q. Gu, Constrained multi-objective optimization via two archives assisted push-pull evolutionary algorithm, Swarm and Evolutionary Computation. Sept., 2022. Accepted. [source code]
  44. F. Ming, W. Gong (corresponding author), D. Li, L. Wang, and L. Gao, A competitive and cooperative swarm optimizer for constrained multi-objective optimization problems, IEEE Transactions on Evolutionary Computation. Aug., 2022. Accepted. [source code]
  45. S. Xiong, W. Gong (corresponding author), and K. Wang, An adaptive neighborhood-based speciation differential evolution for multimodal optimization, Expert Systems With Applications. Aug., 2022. Accepted. [source code]
  46. R. Li, W. Gong (corresponding author), L. Wang, C. Lu, and S. Jiang, Two-stage knowledge-driven evolutionary algorithm for distributed green flexible job shop scheduling with type-2 fuzzy processing time, Swarm and Evolutionary Computation. July, 2022. Accepted. [source code]
  47. J. Dong, W. Gong (corresponding author), and F. Ming, A tri-stage competitive swarm optimizer for constrained multi-objective optimization, Applied Intelligence. June, 2022. Accepted. [source code]
  48. H. Zhen, W. Gong (corresponding author), and L. Wang, Evolutionary sampling agent for expensive problems, IEEE Transactions on Evolutionary Computation. May, 2022. Accepted. [source code]
  49. R. Li, W. Gong (corresponding author), C. Lu, and L. Wang, A learning-based memetic algorithm for energy-efficient flexible job shop scheduling with type-2 fuzzy processing time, IEEE Transactions on Evolutionary Computation. May, 2022. Accepted. [source code]
  50. R. Li, W. Gong (corresponding author), and C. Lu, A reinforcement learning based RMOEA/D for bi-objective fuzzy flexible job shop scheduling, Expert Systems With Applications. April, 2022. Accepted. [source code]
  51. W. Li, W. Gong (corresponding author), F. Ming, and L. Wang, Constrained multi-objective evolutionary algorithm with an improved two-archive strategy, Knowledge-Based Systems. April, 2022. Accepted. [source code]
  52. H. Zhen, W. Gong (corresponding author), and L. Wang, Offline data-driven evolutionary optimization based on model selection, Swarm and Evolutionary Computation. April, 2022. Accepted. [source code]
  53. R. Li, W. Gong (corresponding author), and C. Lu, Self-adaptive multi-objective evolutionary algorithm for flexible job shop scheduling with fuzzy processing time, Computers & Industrial Engineering. March, 2022. Accepted. [source code]
  54. Z. Zhang, Y. Cai, and W. Gong (corresponding author), Evolution-driven randomized graph convolutional networks, IEEE Transactions on Systems, Man, and Cybernetics: Systems. March, 2022. Accepted. [source code]
  55. K. Wang, W. Gong (corresponding author), Z. Liao, and L. Wang, Hybrid niching-based differential evolution with two archives for nonlinear equations system, IEEE Transactions on Systems, Man, and Cybernetics: Systems. March, 2022. Accepted. [source code]
  56. F. Ming, W. Gong (corresponding author), L. Wang, and C. Lu, A tri-population based co-evolutionary framework for constrained multi-objective optimization problems, Swarm and Evolutionary Computation. Feb, 2022. Accepted. [source code]
  57. F. Ming, W. Gong (corresponding author), L. Wang, and L. Gao, A constrained many-objective optimization evolutionary algorithm with enhanced mating and environmental selections, IEEE Transactions on Cybernetics. Feb, 2022. Accepted. [source code] [supplementary file]
  58. F. Yu, W. Gong (corresponding author), and H. Zhen, A data-driven evolutionary algorithm with muti-evolutionary sampling strategy for expensive optimization, Knowledge-Based Systems. Feb, 2022. Accepted. [source code]
  59. F. Ming, W. Gong (corresponding author), and L. Wang, A two-stage evolutionary algorithm with balanced convergence and diversity for many-objective optimization, IEEE Transactions on Systems, Man, and Cybernetics: Systems. Jan, 2022. Accepted. [source code]
  60. J. Dong, W. Gong (corresponding author), F. Ming, and L. Wang, A two-stage evolutionary algorithm based on three indicators for constrained multi-objective optimization, Expert Systems With Applications. Jan, 2022. Accepted. [source code]
  61. Z. Zhang, Y. Cai, W. Gong (corresponding author), P. Ghamisi, X. Liu, and R. Gloaguen, Hypergraph convolutional subspace clustering with multi-hop aggregation for hyperspectral image, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. Dec, 2021. Accepted. [source code]
  62. K. Wang, W. Gong (corresponding author), L. Deng, and L. Wang Multimodal optimization via dynamically hybrid niching-based differential evolution, Knowledge-Based Systems. Dec, 2021. Accepted. [source code]
  63. Z. Hu and W. Gong (corresponding author), Constrained evolutionary optimization based on reinforcement learning using the objective function and constraints, Knowledge-Based Systems. Nov, 2021. Accepted. [source code]
  64. S. Li, W. Gong (corresponding author), L. Wang, and Q. Gu, Multi-objective optimal power flow with stochastic wind and solar power, Applied Soft Computing. Nov, 2021. Accepted. [source code]
  65. H. Zhen, W. Gong (corresponding author), L. Wang, F. Ming, and Z. Liao, Two-stage data-driven evolutionary optimization for high-dimensional expensive problems, IEEE Transactions on Cybernetics. Oct, 2021. Accepted. [source code]
  66. F. Ming, W. Gong (corresponding author), H. Zhen, S. Li, L. Wang, Z. Liao, A simple two-stage evolutionary algorithm for constrained multi-objective optimization, Knowledge-Based Systems. June, 2021. Accepted. [source code]
  67. S. Li, W. Gong (corresponding author), C. Hu, X. Yan, L. Wang, and Q. Gu, Adaptive constraint differential evolution for optimal power flow, Energy. June, 2021. Accepted. [source code]
  68. X. Dai, W. Gong (corresponding author), and Q. Gu, Automated test case generation based on differential evolution with node branch archive, Computers & Industrial Engineering. Vol. 156, June 2021, Article 107290. [source code]
  69. H. Zhen, W. Gong (corresponding author), and L. Wang, A data-driven evolutionary sampling optimization for expensive problems, Journal of Systems Engineering and Electronics. March 2021, Accepted. [source code]
  70. W. Gong, Z. Liao, X. Mi, L. Wang, and Y. Guo, Nonlinear Equations Solving with Intelligent Optimization Algorithms: A Survey, Complex System Modeling and Simulation. Vol. 1, No. 1, pp. 15-32, Mar. 2021.
  71. X. Yang and W. Gong (corresponding author), Opposition-based JAYA with population reduction for parameter estimation of photovoltaic solar cells and modules, Applied Soft Computing. Vol. 104, Feb. 2021, Article 107218. [source code]
  72. S. Li, W. Gong (corresponding author), and Q. Gu, A comprehensive survey on meta-heuristic algorithms for parameter extraction of photovoltaic models, Renewable and Sustainable Energy Reviews. Vol. 141, Feb. 2021, Article 110828.
  73. Z. Hu, W. Gong (corresponding author), and S. Li, Reinforcement learning-based differential evolution for parameters extraction of photovoltaic models, Energy Reports. Vol. 7, Feb. 2021, 916-928. [source code]
  74. J. Wu, W. Gong (corresponding author), and L. Wang, A clustering-based differential evolution with different crowding factors for nonlinear equations system, Applied Soft Computing. Vol. 98, Jan. 2021, Article 106733. [source code]
  75. S. Li, W. Gong (corresponding author), L. Wang, X. Yan, and C. Hu A hybrid adaptive teaching-learning-based optimization and differential evolution for parameter identification of photovoltaic models, Energy Conversion and Management. Vol. 225, 1 Dec. 2020, Article 113474. [source code]
  76. S. Li, W. Gong (corresponding author), L. Wang, X. Yan, and C. Hu, Optimal power flow by means of constrained adaptive differential evolution, Energy. Volume 198, 1 May 2020, Article 117314.
  77. Z. Liao, W. Gong (corresponding author), and L. Wang, Memetic niching-based evolutionary algorithms for solving nonlinear equation system, Expert Systems With Applications. Volume 149, 1 July 2020, Article 113261.
  78. S. Li, Q. Gu, W. Gong (corresponding author), and B. Ning, An enhanced adaptive differential evolution for parameter extraction of photovoltaic models, Energy Conversion and Management, Volume 205, 1 February 2020, Article 112443.
  79. Z. Liao, W. Gong (corresponding author), L. Wang, X. Yan, and C. Hu, A decomposition-based differential evolution with reinitialization for nonlinear equations systems, Knowledge-Based Systems. Volume 191, 5 March 2020, Article 105312.
  80. Z. Liao, W. Gong (corresponding author), X. Yan, L. Wang, and C. Hu, Solving nonlinear equations system with dynamic repulsion-based evolutionary algorithms, IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2020, 50(4): 1590-1601.
  81. W. Gong, Y. Wang, Z. Cai, and L. Wang, Finding multiple roots of nonlinear equation systems via a repulsion-based adaptive differential evolution, IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2020, 50(4): 1499-1513.
  82. X. Yang, W. Gong (corresponding author), and L. Wang, Comparative study on parameter extraction of photovoltaic models via differential evolution, Energy Conversion and Management, Volume 201, 1 December 2019, Article 112113.
  83. S. Li, W. Gong (corresponding author), X. Yan, C. Hu, D. Bai, and L. Wang, Parameter estimation of photovoltaic models with memetic adaptive differential evolution, Solar Energy, 2019, 190, 465-474.
  84. W. He, W. Gong (corresponding author), L. Wang, X. Yan, and C. Hu, Fuzzy neighborhood-based differential evolution with orientation for nonlinear equations system, Knowledge-Based Systems. 2019, 182: Article 104796.
  85. S. Li, W. Gong (corresponding author), X. Yan, C. Hu, D. Bai, L. Wang, and L. Gao, Parameter extraction of photovoltaic models using an improved teaching-learning-based optimization, Energy Conversion and Management. 2019, 186, 293-305.
  86. W. Gong, X. Yan, C. Hu, L. Wang, and L. Gao, Fast and accurate parameter extraction for different types of fuel cells with decomposition and nature-inspired optimization method. Energy Conversion and Management. 2018, 174: 913-921.
  87. W. Gong, Y. Wang, Z. Cai and S. Yang, A Weighted Biobjective Transformation Technique for Locating Multiple Optimal Solutions of Nonlinear Equation Systems. IEEE Transactions on Evolutionary Computation. vol. 21, no. 5, pp. 697-713, Oct. 2017.
  88. W. Gong, A. Zhou, and Z. Cai, A multioperator search strategy based on cheap surrogate models for evolutionary optimization. IEEE Transactions on Evolutionary Computation. 2015, 19(5), 746 - 758. [C++ source code]
  89. W. Gong, X. Yan, X. Liu, and Z. Cai, Parameter extraction of different fuel cell models with transferred adaptive differential evolution. Energy. 2015, 86: 139 - 151. [C++ source code]
  90. W. Gong, Z. Cai, and D. Liang, Adaptive ranking mutation operator based differential evolution for constrained optimization. IEEE Transactions on Cybernetics. 2015, 45(4): 716 - 727. [C++ source code] [Supplement file]
  91. W. Gong, Z. Cai, J. Yang, X. Li, and J. Li, Parameter identification of an SOFC model with an efficient, adaptive differential evolution algorithm. International Journal of Hydrogen Energy. 2014, 39(10): 5083 - 5096. [C++ source code]
  92. W. Gong, Z. Cai, and Y. Wang, Repairing the crossover rate in adaptive differential evolution. Applied Soft Computing. 2014, 15: 149 - 168. [C++ and Matlab source codes]
  93. W. Gong, Z. Cai, and D. Liang, Engineering optimization by means of an improved constrained differential evolution. Computer Methods in Applied Mechanics and Engineering. 2014, 268: 884 - 904. [C++ source code]
  94. W. Gong and Z. Cai, Parameter optimization of PEMFC model with improved multi-strategy adaptive differential evolution. Engineering Applications of Artificial Intelligence. 2014, 27: 28 - 40. [C++ source code]
  95. W. Gong and Z. Cai, Differential Evolution with Ranking-based Mutation Operators. IEEE Transactions on Cybernetics. 2013, 43(6): 2066 - 2081. [C++ source code]
  96. W. Gong and Z. Cai, Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution. Energy. 2013, 59: 356 - 364.
  97. W. Gong and Z. Cai, Parameter extraction of solar cell models using repaired adaptive differential evolution. Solor Energy. 2013, 94: 209 - 220. [C++ source code]
  98. Z. Hu, W. Gong, and Z. Cai, Multi-resolution Remote Sensing Image Registration Using Differential Evolution with Adaptive Strategy Selection, Optical Engineering. 2012, 51 (10), 101707.
  99. W. Gong, A. Fialho, Z. Cai, and H. Li, Adaptive Strategy Selection in Differential Evolution for Numerical Optimization: An Empirical Study, Information Sciences. Dec. 2011, 181(24): 5364 - 5386. [C++ source code]
  100. Z. Cai, and W. Gong*, A Point Symmetry-based Clustering Approach Using Differential Evolution, Journal of Information & Computational Science. Sep. 2011, 8(9): 1593 - 1608.
  101. W. Gong, Z. Cai, L. Jia, and H. Li, A Generalized Hybrid Generation Scheme of Differential Evolution for Global Numerical Optimization, International Journal of Computational Intelligence and Applications (IJCIA). 2011, 10(1): 35 - 65.
  102. W. Gong, Z. Cai, C.X. Ling, and H. Li, Enhanced Differential Evolution with Adaptive Strategies for Numerical Optimization, IEEE Transactions on Systems, Man, and Cybernetics: Part B -- Cybernetics. Apr. 2011, 41(2): 397-413.
  103. W. Gong, Z. Cai, and C.X. Ling, DE/BBO: A Hybrid Differential Evolution with Biogeography-Based Optimization for Global Numerical Optimization, Soft Computing. Springer-Verlag. Apr. 2011, 15(4): 645-665. [C source code]
  104. Z. Cai, W. Gong, C.X. Ling, and H. Zhang, A Clustering-based Differential Evolution for Global Optimization, Applied Soft Computing. Elsevier Press. Jan. 2011, 11(1): 1363 - 1379.
  105. W. Gong, Z. Cai, C.X. Ling, and H. Li, A Real-Coded Biogeography-Based Optimization with Mutation, Applied Mathematics and Computation. Elsevier Press. Jul. 2010, 216(9): 2749 - 2758. [C++ source code]
  106. Z. Cai, W. Gong, and C.X. Ling, Research on a Novel Biogeography-based Optimization Algorithm based on Evolutionary Programming, Systems Engineering -- Theory & Practice. June, 2010, 30(6): 1106 - 1112. (in Chinese with English abstract)
  107. W. Gong, and Z. Cai, An Improved Multiobjective Differential Evolution based on Pareto-adaptive epsilon-dominance and Orthogonal Design, European Journal of Operational Research. Elsevier Press. Oct. 2009, 198(2): 576 - 601. [C++ source code]
  108. W. Gong, and Z. Cai, Research on epsilon-domination based Orthogonal Differential Evolution Algorithm for Multi-objective Optimization, Journal of Computer Research and Development. Apr. 2009, 46(4): 655 - 666. (in Chinese with English abstract)
  109. W. Gong, Z. Cai, and L. Zhu, An Efficient Multiobjective Differential Evolution Algorithm for Engineering Design, Structural and Multidisciplinary Optimization. Springer-Verlag. Apr. 2009, 38(2): 137 - 157.
  110. W. Gong, Z. Cai, and L.X. Jiang, Enhancing the Performance of Differential Evolution Using Orthogonal Design Method, Applied Mathematics and Computation. Elsevier Press. Dec. 2008, 206(1): 56 - 69.
  111. W. Gong, C. Chen, and Z. Cai, Simple Diversity Rules and Improved Differential Evolution for Constrained Global Optimization, Dynamics of Continuous, Discrete & Impulsive Systems (Series B: Applications & Algorithms), 2007, 14(S3): 91 - 98.

Conference Publications

  1. J. Xu, Z. Cai, and W. Gong, An adaptive strategy to adjust the components of memetic algorithms, The 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014). 2014.11: 55-62. Limassol, Cyprus.
  2. Y. Huo, Z. Cai, W. Gong, and Q. Liu, A new adaptive Kalman filter by combining evolutionary algorithm and fuzzy inference system, proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC 2014). IEEE Press. 2014.7: 2893-2900. Beijing, China.
  3. Y. Huo, Z. Cai, W. Gong, and Q. Liu, The Parameter Optimization of Kalman Filter Based on Multi-Objective Memetic Algorithm, proceedings of Genetic and Evolutionary Computation Conference (GECCO 2014). ACM Press. 2014.7: 613-620. Vancouver, BC, Canada.
  4. W. Gong, and Z. Cai, An Empirical Study on Differential Evolution for Optimal Power Allocation in WSNs, proceedings of the 8th International Conference on Natural Computation (ICNC'12). IEEE Press. 2012.5: 635 - 639. Chongqing, China.
  5. W. Gong, and Z. Cai, Adaptive Parameter Selection for Strategy Adaptation in Differential Evolution, proceedings of Genetic and Evolutionary Computation Conference (GECCO (Companion)). ACM Press. 2011.7: 111-112. Dublin, Ireland.
  6. M. Yang, Z. Cai, J. Guan, and W. Gong, Differential Evolution with Improved Population Reduction, proceedings of Genetic and Evolutionary Computation Conference (GECCO (Companion)). ACM Press. 2011.7: 143-144. Dublin, Ireland.
  7. L. Jia, L. Li, W. Gong, and L. Huang, Hybrid Differential Evolution for Global Numerical Optimization, proceedings of The Fifth International Conference on Rough Set and Knowledge Technology (RSKT 2010). Springer-Verlag. 2010.10, LNAI 6401: 560 - 567. Beijing, China.
  8. A. Fialho, W. Gong, and Z. Cai, Probability Matching-based Adaptive Strategy Selection vs. Uniform Strategy Selection within Differential Evolution, In BBOB'10: GECCO Workshop on Black-Box Optimization Benchmarking. ACM Press. 2010.7: 1527 - 1534. Portland, USA.
  9. W. Gong, A. Fialho, and Z. Cai, Adaptive Strategy Selection in Differential Evolution, proceedings of Genetic and Evolutionary Computation Conference (GECCO 2010). ACM Press. 2010.7: 409 - 416. Portland, USA. Best Paper Award Nominee! [C++ source code]
  10. W. Gong, Z. Cai, C.X. Ling, and B. Huang, A Point Symmetry-based Automatic Clustering Approach Using Differential Evolution, proceedings of the 4th International Symposium on Intelligence Computation and Applications (ISICA 2009), LNCS 5821, Springer-Verlag. 2009.10: 151 - 162. Huangshi, China.
  11. L.Y. Jia, W. Gong, and H.B. Wu, An Improved Self-adaptive Control Parameter of Differential Evolution for Global Optimization, proceedings of the 4th International Symposium on Intelligence Computation and Applications (ISICA 2009), CCIS 51, Springer-Verlag. 2009.10: 215 - 224. Huangshi, China.
  12. W. Gong, Z. Cai, C.X. Ling, and J. Du, Hybrid Differential Evolution based on Fuzzy C-means Clustering, proceedings of Genetic and Evolutionary Computation Conference (GECCO 2009). ACM Press. 2009.7: 523 - 530. Montreal, Canada.
  13. X.B. Liu, Z. Cai, and W. Gong, An Improved Gene Expression Programming for Fuzzy Classification, proceedings of the 3rd International Symposium on Intelligence Computation and Applications (ISICA 2008), LNCS 5370, Springer-Verlag. 2008.12: 520 - 529. Wuhan, China.
  14. W. Gong and Z. Cai, A Multiobjective Differential Evolution Algorithm for Constrained Optimization, proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC 2008). 2008.6: 181 - 188. Hong Kong, China.
  15. W. Gong, Z. Cai, and Y.Q. Huang, A Simple and Fast Differential Evolution for Unconstrained Global Optimization, proceedings of the 2nd International Symposium on Intelligence Computation and Applications (ISICA-07). 2007.9: 163 - 167.
  16. Z. Cai, W. Gong, and Y.Q. Huang, A Novel Differential Evolution Algorithm based on epsilon-domination and Orthogonal Design Method for Multiobjective Optimization, proceedings of the 4th International Conference on Evolutionary Multi-Criterion Optimization (EMO-07), LNCS 4403, Springer-Verlag. 2007.3: 286 - 301.
  17. J. Wang, L. Zhu, Z. Cai, W. Gong, et al, Training RBF Networks with an Extended Kalman Filter Optimized Using Fuzzy Logic, proceedings of the 4th International Conference on Intelligence Information Processing (IIP2006). 2006.9: 317 - 326.
  18. W. Gong, Z. Cai, and C. X. Ling, ODE: A Fast and Robust Differential Evolution Based on Orthogonal Design, AI 2006: Advances in Artificial Intelligence - 19th Australian Joint Conference on Artificial Intelligence, LNAI 4304, Springer-Verlag. 2006.12: 709-718.
  19. W. Gong, Z. Cai, X. W. Lu, et al, A New Mutation Operator Based on the T Probability Distribution in Evolutionary Programming, proceedings of the 5th IEEE International Conference on Cognitive Informatics (IEEE ICCI2006). 2006.7: 675-679.