周爱民

4. 2004.10-2009.06：英国Essex大学计算与电子工程学院，获博士学位

3. 2003.09-2004.09：武汉大学计算机学院，博士在读

2. 2001.09-2003.06：武汉大学计算机学院，获硕士学位（提前毕业）

1. 1997.09-2001.06：武汉大学计算机学院，获学士学位

3. 2016.12-：华东师范大学，研究员

2. 2012.12-2016.12：华东师范大学，副教授

1. 2009.06-2012.12：华东师范大学，讲师

1. IEEE高级会员

2. 中国计算机学会(CCF)会员

3. Swarm and Evolutionary Computation副编

4. Complex & Intelligent Systems编委

5. IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, IEEE Computational Intelligence Magazine, Pattern Recognition, Information Sciences, 软件学报，计算机学报，CEC, GECCO, EMO, IJCAI, AAAI, NeurIPS等期刊和会议审稿人

6. 国家自然科学基金通讯评审专家（2011-2020）

1. 演化搜索、优化与建模(Evolutionary Search, Optimization and Modeling)

2. 智能教育(AI for Education)

3. 工业应用(Industry Applications)

8. 人工智能，本科必修，2010-2021

7. 人工智能前沿专题，博士生必修，2021

6. AIoT智能系统，研究生选修，2021

5. 人工智能前沿，研究生必修，2018-2020

4. 计算智能，研究生必修，2012-2016

3. 最优化方法，研究生选修，2016-2017

2. Windows程序设计，本科选修，2012

1. 编程实践，本科必修，2010-2012

Google Citation:http://scholar.google.com/citations?user=E4GQv5cAAAAJ&hl=en

DBLP:https://dblp.uni-trier.de/pers/hd/z/Zhou:Aimin

主要论文：

[33]F. Wang, H. Zhang, and A. Zhou, A particle swarm optimization algorithm for mixed-variable optimization problems, Swarm and Evolutionary Computation, 60:100808, 2021. (accepted)

[32]C. Liu, T. Bian, and A. Zhou, Multiobjective multiple features fusion: A case study in image segmentation, Swarm and Evolutionary Computation, 60:100792, 2021. (accepted)

[31]M. Yang, A. Zhou, X. Yao, and C. Li, An efficient recursive differential grouping for large-scale continuous problems, IEEE Transactions on Evolutionary Computation, 25(1):159-171, 2021.

[30]H. Hao, J. Zhang, X. Lu, and A. Zhou, Binary relation learning and classifying for preselection in evolutionary algorithms, IEEE Transactions on Evolutionary Computation, 24(6):1125-1139, 2020.

[29]F. Wang, Y. Li, A. Zhou, and K. Tang, An estimation of distribution algorithm for mixed-variable Newsvendor problems, IEEE Transactions on Evolutionary Computation, 24(3):479-493, 2020.

[28]A. Zhou, Y. Wang, and J. Zhang, Objective extraction via Fuzzy clustering in evolutionary many-objective optimization, Information Sciences, 509:343-355, 2020.

[27]J. Zhang, A. Zhou, and G. Zhang, A pre-selection based on one-class classification in evolutionary algorithms, Chinese Journal of Computers,43(2):233-249, 2020. (in Chinese)

[26]M. Yang, A. Zhou, C. Li, J. Guan, and X. Yan, CCFR2: A more efficient cooperative co-evolutionary framework for large-scale global optimization, Information Sciences, 512:64-79, 2020. 

[25]H. Zhang, A. Zhou, and X. Lin. Interpretable policy derivation for reinforcement learning based on evolutionary feature synthesis, Complex & Intelligent Systems, 6 (3):741-753, 2020.

[24]X. Chen, C. Shi, A. Zhou, and B. Wu, A multiobjective evolutionary algorithm based on hybridindividual selection mechanism, Journal of Software, 30(12):3651-3664, 2019. (in Chinese)

[23]A. Zhou, J. Zhang, J. Sun, and G. Zhang, Fuzzy-classification assisted solution preselectionin evolutionary optimization, in AAAI, pp. 2403-2410, 2019. 

[22]W. Hong, K.Tang, A. Zhou, H. Ishibuchi, and X. Yao, A scalable indicator-based evolutionary algorithm for large-scale multi-objective optimization, IEEE Transactions on Evolutionary Computation, 23(3):525-537, 2019.

[21]J. Sun, H. Zhang, A. Zhou, Q. Zhang, and K. Zhang, A new learning-based adaptive multi-objective evolutionary algorithm, Swarm and Evolutionary Computation, 44:304-319, 2019. 

[20]H.Zhang, and A. Zhou, Tree-structured decomposition and adaptation in MOEA/D, in Parallel Problem Solving From Nature (PPSN XV), pp.359-371, 2018.

[19]J. Zhang, A. Zhou, K. Tang, and G. Zhang, Preselectionvia classification: A case study on evolutionary multiobjective optimization, Information Sciences, 465:388-403, 2018.

[18]D. Ding, Q. Zhang, L. Yang, A. Zhou, and J. Xia, Wiggly parallel-coupled line design by usingmultiobjective evolutionary algorithm, IEEE Microwave and Wireless Components Letters, 28(8):648-650, 2018.

[17]H. Fang, A. Zhou, and H. Zhang, Information fusion in offspring generation: A case studyin DE and EDA, Swarm and Evolutionary Computation, 42:92-108, 2018.

[16]J. Sun, A. Zhou, S. Keates, and S. Liao, Simultaneous Bayesian clustering and feature selection through student’s t mixtures model, IEEE Transactions on Neural Networks and Learning Systems, 29(4):1187-1199, 2018.

[15]H. Zhang, A. Zhou, S. Song, Q. Zhang, X. Gao, and J. Zhang, A self-organizing multiobjective evolutionary algorithm, IEEE Transactions on Evolutionary Computation, 20(5):792-806, 2016.

[14]L. Wang, Q. Zhang, A. Zhou, M. Gong, and L. Jiao, Constrained subproblems in decomposition based multiobjective evolutionary algorithm, IEEE Transactions on Evolutionary Computation, 20(3):475-480, 2016.

[13]A. Zhou, and Q. Zhang, Are all the subproblems equally important? Resource allocation in decomposition based multiobjective evolutionary algorithms, IEEE Transactions on Evolutionary Computation, 20(1):52-64, 2016.

[12]Z. Wang, Q. Zhang, A. Zhou, M. Gong, and L. Jiao, Adaptive replacement strategies for MOEA/D, IEEE Transactions on Cybernetics, 46 (2):474-486, 2016.

[11]A. Zhou, J. Sun, and Q. Zhang, An estimation of distribution algorithm with cheap and expensive local search, IEEE Transactions on Evolutionary Computation, 19 (6): 807-822, 2015.

[10]W. Gong, A. Zhou, and Z. Cai, A multi-operator search strategy based on cheap surrogate models for evolutionary optimization, IEEE Transactions on Evolutionary Computation, 19 (5): 746-758, 2015.

[9]A. Zhou, Y. Jin, and Q. Zhang, A population prediction strategy for evolutionary dynamic multiobjective optimization, IEEE Transactions on Cybernetics, 44(1):40-53, 2014.

[8]A. Zhou, Q. Zhang, and G. Zhang, A multiobjective evolutionary algorithm based on mixture Gaussian models,Journal of Software, 5:913-928, 2014. (in Chinese)

[7]A. Zhou, F. Gao, and G. Zhang, A decomposition based estimation of distribution algorithm for multiobjective traveling salesman problems, Computers and Mathematics with Applications, 66:1857–1868, 2013.

[6]A. Zhou, B. Qu, H. Li, S. Zhao, P. Suganthan, and Q. Zhang, Multiobjective evolutionary algorithms: A survey of the state of the art, Swarm and Evolutionary Computation, 1(1): 32–49, 2011.

[5]A. Zhou, Q. Zhang and Y. Jin, Approximating the set of Pareto optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm, IEEE Transactions on Evolutionary Computation, 13(5):1167-1189, 2009.

[4]Q. Zhang, A. Zhou, and Y. Jin, RM-MEDA: A regularity model based multiobjective estimation of distribution algorithm, IEEE Transactions on Evolutionary Computation, 12(1):41-63, 2008.

[3]A.Zhou, Q. Zhang, Y. Jin, B. Sendhoff, and E. Tsang, Modelling the populationdistribution in multi-objective optimization by generative topographic mapping, in Parallel Problem Solving From Nature(PPSN IX), pp.443-452, 2006.

[2]A. Zhou, H. Cao, L. Kang, and Y. Huang, The automatic modelling of complex functions based on genetic programming, Journal of System Simulation, 15(6):797–799, 2003.

[1]A. Zhou, L. Kang, Y. Chen, and Y. Huang, A new definition and calculation model for evolutionary multi-objective optimization, Journal of Wuhan University, 8(1B):189–194, 2003.

学位论文：

[2]博士论文: Estimation of distribution algorithms for continuous multiobjective optimization, University of Essex, 2009年, 导师: Qingfu Zhang教授, Edward Tsang教授, Yaochu Jin教授(Honda Research Institute Europe), Bernhard Sendhoff博士(Honda Research Institute Europe).

[1]硕士论文: 演化建模及其应用, 武汉大学, 2003年, 导师: 康立山教授.