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龚文引 中文主页 中国地质大学(武汉)教师个人

发表于:2022-06-27 12:31:20

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):


[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)