姓 名 杨鸣 性 别 男
出生年月 1982年7月 籍贯
民 族 汉族 政治面貌 中共党员
最后学历 博士研究生毕业 最后学位 工学博士
技术职称 副教授 导师类别 硕导
行政职务 Email ymzhongzhong@qq.com
工作单位 邮政编码
通讯地址
单位电话
个人主页 http://cs.cug.edu.cn/myang


个人简介
杨鸣，博士，副教授，主要讲授程序设计相关的课程和从事演化计算方面的研究工作；2009年获湖北省优秀硕士学位论文奖励；2014.12至2015.12，在英国伯明翰大学计算机学院从事博士后研究（国家留学基金委全额资助）；2017年入选学校“地大****”青年优秀人才和摇篮计划；主持国家自然科学基金青年基金项目1项、民用航天预研项目1项，作为核心成员参与国家级项目5项；至今以第一作者、通讯作者发表SCI、EI检索论文近20篇，其中包括演化计算领域的国际权威期刊《IEEE Transactions on Evolutionary Computation》、《IEEE Transactions on Cybernetics》、《Evolutionary Computation》、演化计算领域的著名国际会议GECCO和CEC论文。

工作经历
1. 2008.07至今，中国地质大学（武汉）计算机学院，教师
2. 2014.12-2015.12，英国伯明翰大学（University of Birmingham）计算机学院，博士后（中国国家留学基金委资助）

教育经历
1. 2001.09-2005.06，中国地质大学（武汉）计算机学院，计算机科学与技术专业，本科
2. 2005.09-2008.06，中国地质大学（武汉）计算机学院，计算机软件与理论专业，硕士
3. 2009.09-2012.06，中国地质大学（武汉）计算机学院，地学信息工程，博士

研究领域
演化计算

发表论文
1 期刊论文
[1] Yang, Ming, Mohammad Nabi Omidvar, Li, Changhe, Li, Xiaodong, Cai, Zhihua, Borhan Kazimipour, Yao, Xin, Efficient resource allocation in cooperative co-evolution for large-scale global optimization, IEEE Transactions on Evolutionary Computation, 2017, 21(4): 493-505 (SCI, T1论文, 2016年IF=10.629)
[2] Yang, Ming, Li, Changhe, Cai, Zhihua, Guan, Jing, Differential evolution with auto-enhanced population diversity, IEEE Transactions on Cybernetics, 2015, 45(2): 302-315 (SCI, T1论文, 2016年IF=7.384, 2017年高被引论文)
[3] Yang, Ming, Li, Changhe, Guan, Jing, Yan, Xuesong, A supervised-learning p-norm distance metric for hyperspectral remote sensing image classification, IEEE Geoscience and Remote Sensing Letters, 2018, 15(9): 1432-1436 (SCI, T3论文, 2016年IF=2.761)
[4] Yang, Ming, Guan, Jing, Cai, Zhihua, Li, Changhe, A self-adaptive differential evolutionary algorithm based on population reduction with minimum distance, International Journal of Innovative Computing and Applications, 2014, 6(1): 13-24 (EI, T4论文)
[5] 杨鸣, 康立山, 吴燕来, 动态多目标TSP中动态程度和目标冲突程度的度量, 武汉大学学报信息科学版, 2008, 33(2): 216-219 (EI, T4论文)
[6] Li, Changhe, Trung Thanh Nguyen, Yang, Ming (通讯作者), Mavrovouniotis, Michalis, Yang, Shengxiang, An adaptive multipopulation framework for locating and tracking multiple optima，IEEE Transactions on Evolutionary Computation, 2016, 20(4): 590-605 (SCI, T1论文, 2016年IF=10.629)
[7] Li, Changhe, Trung Thanh Nguyen, Yang, Ming (通讯作者), Ming Shengxiang, Zeng, Sanyou, Multi-population methods in unconstrained continuous dynamic environments: The challenges，Information Sciences, 2015, 296: 95-118 (SCI, T1论文, 2016年IF=4.832)
[8] Li, Changhe, Yang, Shengxiang, Yang, Ming (通讯作者), An adaptive multi-swarm optimizer for dynamic optimization problems, Evolutionary Computation, 2014, 22(4): 559-594 (SCI, T2论文, 2016年IF=3.826)
[9] Omidvar, M. N., Yang, Ming, Mei, Yi, Li Xiaodong, Yao Xin, DG2: A faster and more accurate differential grouping for large-scale black-box optimization, IEEE Transactions on Evolutionary Computation, 2017, 21(6): 929-942 (SCI, T1论文, 2016年IF=10.629)
[10] Li, Changhe, Trung Thanh Nguyen, Zeng, Sanyou, Yang, Ming, Wu, Min, An open framework for constructing continuous optimization problems, IEEE Transactions on Cybernetics, 2018: 1-15, published first online, doi: 10.1109/TCYB.2018.** (SCI, T1论文, 2016年IF=7.384)
2 会议论文
[1] Yang, Ming, Guan, Jing, Li, Changhe, Differential evolution with auto-enhanced population diversity: The experiments on the CEC’2016 competition, IEEE Congress on Evolutionary Computation, CEC 2016, Vancouver, Canada, 2016 (EI)
[2] Yang, Ming, Guan, Jing, Cai, Zhihua, Li, Changhe, A dimensional-level adaptive differential evolutionary algorithm for continuous optimization, Genetic and Evolutionary Computation Conference, GECCO 2014, Vancouver, BC, Canada, 2014 (EI)
[3] Yang, Ming, Cai, Zhihua, Li, Changhe, Guan, Jing, An improved JADE algorithm for global optimization, IEEE Congress on Evolutionary Computation, CEC 2014, Beijing, China, 2014 (EI)
[4] Yang, Ming, Guan, Jing, Cai, Zhihua, Li, Changhe, Differential evolution based on population reduction with minimum distance, International Conference on Advanced Computational Intelligence, ICACI 2013, Hangzhou, China, 2013 (EI)
[5] Yang, Ming, Cai, Zhihua, Li, Changhe, Guan, Jing, An improved adaptive differential evolution algorithm with population adaptation, Genetic and Evolutionary Computation Conference, GECCO 2013, Amsterdam, The Netherlands, 2013 (EI)
[6] Yang, Ming, Cai, Zhihua, Guan, Jing, Gong, Wenyin, Differential evolution with improved population reduction, Genetic and Evolutionary Computation Conference, GECCO 2011, Dublin, Ireland, 2011 (EI)
[7] Yang, Ming, Guan, Jing, Cai, Zhihua, Wang, Lu, Self-adapting differential evolution algorithm with chaos random for global numerical optimization, International Symposium on Intelligence Computation and Applications, ISICA 2010, Wuhan, China, 2010 (EI)
[8] Yang, Ming, Guan, Jing, Dynamic clonal and chaos-mutation evolutionary algorithm for function optimization, International Symposium on Intelligence Computation and Applications, ISICA 2008, Wuhan, China, 2008 (EI)
[9] Yang, Ming, Kang, Lishan, Guan, Jing, Multi-algorithm co-evolution strategy for dynamic multi-objective TSP, IEEE Congress on Evolutionary Computation, CEC 2008, Hong Kong, China, 2008
[10] Yang, Ming, Kang, Lishan, Guan, Jing, An evolutionary algorithm for dynamic multi-objective TSP, International Symposium on Intelligence Computation and Application, ISICA 2007, Wuhan, China, 2007 (EI)
[11] Fang, Zheng (培养的研究生), Yang, Ming, Zhang, Guilin, Guan, Jing, A hybrid differential evolutionary algorithm based on the hierarchical clustering, IEEE Congress on Evolutionary Computation, CEC 2016, Vancouver, Canada, 2016 (EI)
[12] Li, Changhe, Yang, Shengxiang, Yang, Ming, Maintaining diversity by clustering in dynamic environments, IEEE Congress on Evolutionary Computation, CEC 2012, Brisbane, Australia, 2012 (EI)
[13] Li, Changhe, Yang, Ming, Kang, Lishan, A new approach to solving dynamic traveling salesman problems, International Conference on Simulated Evolution and Learning, SEAL 2006, Hefei, China, 2006 (EI)