龚文引

基本信息Personal Information

博士生导师 硕士生导师

曾获荣誉 : 博士,教授,博士生导师,湖北省杰出青年基金获得者,入选”地大学者”学科骨干人才。

性别 : 男

毕业院校 : 中国地质大学(武汉)

学历 : 博士研究生

学位 : 工学博士学位

在职信息 : 在职

所在单位 : 计算机学院

入职时间 : 2010年07月01日

学科 : 计算机科学与技术

办公地点 : 未来城校区计算机学院大楼601

联系方式 : wygong@cug.edu.cn

Email :

教师其他联系方式Other Contact Information

邮箱 :

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个人简介Personal Profile

本人每年可招收博士研究生1名,硕士研究生3名。欢迎对"智能计算及其相关应用"感兴趣的同学发邮件到wygong@cug.edu.cn.谢谢。


龚文引,博士,教授,博士生导师,湖北省杰出青年基金获得者。分别于2004年、2007年和2010年在中国地质大学(武汉)计算机学院获得学士、硕士和博士学位。主要研究方向为智能计算及其应用。现担任湖北省计算机学会副秘书长、中国仿真学会智能仿真优化与调度专委会监事长、ECOLE执委会委员,国际期刊Memetic Computing、IJBIC、CSMS编委。主持国家重点研发计划课题项目一项、国家自然科学基金项目3项、教育部博士学科点新教师基金一项。在SCI期刊发表论文70余篇,其中ESI高被引论文5篇,出版专著2部、译著1部。曾获得湖北省自然科学奖二等奖两项(R1、R2)、湖北省优秀博士学位论文奖、湖北省优秀硕士学位论文奖、湖北省自然科学优秀学术论文一等奖、GECCO-2010最优论文奖提名等奖励。


更多信息请访问:https://wewnyin.github.io/wenyingong


曾获得第六届和第七届中国地质大学(武汉)“研究生良师益友”称号。



指导学生发表的部分代表性论文(第一作者均为本人指导的研究生):


  • [44] R. Li, W. Gong*, 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. (T2)

  • [43] J. Dong, W. Gong*, and F. Ming, A tri-stage competitive swarm optimizer for constrained multi-objective optimization, Applied Intelligence, June, 2022, Accepted. (T3)

  • [42] H. Zhen, W. Gong*, and L. Wang, Evolutionary sampling agent for expensive problems, IEEE Transactions on Evolutionary Computation, May, 2022, Accepted. (T1)

  • [41] R. Li, W. Gong*, 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. (T1)

  • [40] Z. Zhang, Y. Cai, and W. Gong*, Evolution-driven randomized graph convolutional networks, IEEE Transactions on Systems, Man, and Cybernetics: Systems, March 2022, Accepted. (T2)

  • [39] K. Wang, W. Gong*, 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. (T2)

  • [38] F. Ming, W. Gong*, 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. (T1)

  • [37] F. Ming, W. Gong*, 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. (T2)

  • [36] H. Zhen, W. Gong*, 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. (T1)

  • [35] R. Li, W. Gong*, and C. Lu, A reinforcement learning based RMOEA/D for bi-objective fuzzy flexible job shop scheduling, Expert Systems With Applications, Volume 203, 1 October 2022, 117380. (T2)

  • [34] W. Li, W. Gong*, F. Ming, and L. Wang, Constrained multi-objective evolutionary algorithm with an improved two-archive strategy, Knowledge-Based Systems, Volume 246, 21 June 2022, 108732. (T2)

  • [33] H. Zhen, W. Gong*, and L. Wang, Offline data-driven evolutionary optimization based on model selection, Swarm and Evolutionary Computation, Volume 71, June 2022, 101080. (T2)

  • [32] R. Li, W. Gong*, and C. Lu,  Self-adaptive multi-objective evolutionary algorithm for flexible job shop scheduling with fuzzy processing time, Computers & Industrial Engineering, Volume 168, June 2022, 108099. (T3)

  • [31] F. Ming, W. Gong*, L. Wang, and C. Lu, A tri-population based co-evolutionary framework for constrained multi-objective optimization problems, Swarm and Evolutionary Computation, Volume 70, April 2022, 101055. (T2)

  • [30] F. Yu, W. Gong*, and H. Zhen, A data-driven evolutionary algorithm with muti-evolutionary sampling strategy for expensive optimization, Knowledge-Based Systems, Volume 242, 22 April 2022, 108436. (T2)

  • [29] J. Dong, W. Gong*, F. Ming, and L. Wang, A two-stage evolutionary algorithm based on three indicators for constrained multi-objective optimization, Expert Systems With Applications, Volume 195, 1 June 2022, 116499. (T2)

  • [28] Z. Zhang, Y. Cai, W. Gong*, 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, Volume 15, 676-686, Jan. 2022. (T2)

  • [27] K. Wang, W. Gong*, L. Deng, and L. Wang, Multimodal optimization via dynamically hybrid niching-based differential evolution, Knowledge-Based Systems, Volume 238, 28 Feb. 2022, 107972. (T2)

  • [26] Z. Hu and W. Gong*, Constrained evolutionary optimization based on reinforcement learning using the objective function and constraints, Knowledge-Based Systems. Volume 237, 15 Feb. 2022, 107731. (T2)

  • [25] S. Li, W. Gong*, L. Wang, and Q. Gu, Multi-objective optimal power flow with stochastic wind and solar power, Applied Soft Computing, Volume 114, Jan. 2022, 108045. (T2)

  • [24] 李瑞, 龚文引*. 改进MOEA/D算法求解双目标模糊柔性作业车间调度问题. 控制理论与应用. 2022, 39(1): 31-40.

  • [23] S. Li, W. Gong*, C. Hu, X. Yan, L. Wang, and Q. Gu, Adaptive constraint differential evolution for optimal power flow, Energy. Volume 235, 15 Nov. 2021, 121362. (T1)

  • [22] F. Ming, W. Gong*, H. Zhen, S. Li, L. Wang, Z. Liao, A simple two-stage evolutionary algorithm for constrained multi-objective optimization, Knowledge-Based Systems. Volume 228, 27 Sep. 2021, 107263. (T2)

  • [21] W. Li and W. Gong*, An Improved Multioperator-Based Constrained Differential Evolution for Optimal Power Allocation in WSNs, Sensors, 21(18), 6271, Sept. 2021. (T2)

  • [20] X. Dai, W. Gong*, and Q. Gu, Automated test case generation based on differential evolution with node branch archive, Computers & Industrial Engineering. Vol. 156, June, 2021, Article 107290.

  • [19] H. Zhen, W. Gong*, and L. Wang, A data-driven evolutionary sampling optimization for expensive problems, Journal of Systems Engineering and Electronics. Vol. 32, No. 2, pp. 318-330, 2021.

  • [18] W. Li and W. Gong*,  Differential evolution with quasi-reflection-based mutation, Math. Biosci. Eng., 18(3): 2425-2441, 2021.

  • [17] X. Yang and W. Gong*, Opposition-based JAYA with population reduction for parameter estimation of photovoltaic solar cells and modules, Applied Soft Computing. Vol. 104, Feb. 2021, Article 107218. (T2) 

  • [16] S. Li, W. Gong*, 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. (T1)

  • [15] Z. Hu, W. Gong*, and S. Li, Reinforcement learning-based differential evolution for parameters extraction of photovoltaic models, Energy Reports. Vol. 7, Feb. 2021, 916-928.

  • [14] J. Wu, W. Gong*, 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. (T2)

  • [13] S. Li, W. Gong*, 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. (T2)

  • [12] 王开,龚文引*.  求解非线性方程组系统的改进差分进化算法. 控制与决策. 2020,35(9): 2121 - 2128.

  • [11] 郑小操,龚文引*. 改进人工蜂群算法求解模糊柔性车间调度问题. 控制理论与应用. 2020, 37(6): 1284 - 1292.

  • [10] S. Li, W. Gong*, 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. (T1)

  • [9] Z. Liao, W. Gong*, and L. Wang, Memetic niching-based evolutionary algorithms for solving nonlinear equation system, Expert Systems With Applications. Volume 149, 1 July 2020, Article 113261. (T2)

  • [8] S. Li, Q. Gu, W. Gong*, and B. Ning, An enhanced adaptive differential evolution for parameter extraction of photovoltaic models, Energy Conversion and Management, Volume 205, 1 Feb. 2020, Article 112443.  (T2)

  • [7] Z. Liao, W. Gong*, 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.  (T2)

  • [6] 廖作文,龚文引*,王凌. 基于改进环拓扑混合群体智能算法的非线性方程组多根联解. 中国科学: 信息科学. 2020, 50(3): 396-407.  (CCF-A类中文期刊)

  • [5] Z. Liao, W. Gong*, 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. (T2)

  • [4] X. Yang, W. Gong*, and L. Wang, Comparative study on parameter extraction of photovoltaic models via differential evolution, Energy Conversion and Management, Volume 201, 1 Dec. 2019, Article 112113.  (T2)

  • [3] S. Li, W. Gong*, 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.  (T2)

  • [2] W. He, W. Gong*, 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.  (T2)

  • [1] S. Li, W. Gong*, 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.  (T2)



  • 教育经历Education Background
  • 工作经历Work Experience
  • 研究方向Research Focus
  • 社会兼职Social Affiliations
  • 智能计算及其应用

团队介绍Research Group

智能优化与学习

本团队致力于与智能优化与机器学习及其应用相关领域的前沿研究