马晓亮


马晓亮博士,助理教授,2014年获得西安电子科技大学计算机应用技术博士学位,2018年3月至今在深圳大学从事科研和教学工作。研究领域包括进化计算、多目标优化、基于分解的多目标优化算法、车辆路径规划、智能计算、生物信息学、博弈论等。在IEEE Transactions on Evolutionary Computation, Evolutionary Computation, Information Sciences, Neurocomputing等国际期刊发表学术成果多篇,目前担任IEEE-TEVC、IEEE- CYB、IEEE-TETCI等期刊的审稿人。主持国家自然青年基金项目与博士后基金项目各1项,近年来发表SCI检索的相关论文10多篇。
联系方式:maxiaoliang@yeah.net

 

主持的基金项目

[1] 国家自然科学基金 青年基金 (No. 61603259) 面向配送路径优化问题的传输学习和多目标自适应模因计算方法研究. 2017.1-2019.12, 项目经费19万元,排名1/7

[2] 中国博士后科学基金 (No. 2016M592536) 基于多目标自适应Memetic算法的大规模车辆调度研究. 2016.1-2017.12, 项目经费5万元,排名1/1

 

参于的基金项目:

[1] 博士点新教师基金(20090203120016).高性能并行人工免疫算法研究, 2010 年1月至2012年12月, 项目经费3.6万元, 排名: 5/8

[2] 陕西省自然科学基础研究计划项目(2011JQ8010) 基于进化多目标优化的物流配送管理方法 2011.01-2012.12, 项目经费4万元, 排名:2/6

[3] 国家自然科学基金 青年基金 (No. 61303119). 基于搜索过程知识表示与推理的进化多目标优化算法研究. 2014.01-2016.12, 项目经费25万元, 排名:2/8

 

职业活动:

程序委员会委员:the 11th International Conference on Simulated Evolution and Learning (SEAL2017), Shenzhen, China, November 10-13, 2017; the 2017 Fifth China Computer Federation Conference on Big Data (CCFBigData2017), Shenzhen, China, October 14-16, 2017.

审稿人:IEEE Transactions on Evolutionary Computation, IEEE Computational Intelligence Magazine, IEEE Transactions on Cybernetics, Engineering Applications of Artificial Intelligence, Engineering Applications of Artificial Intelligence, Neurocomputing, International Journal of Bio-Inspired Computation, International Journal of Production Research, and so on.

 

 

已出版/录用的文章:

[1] Xiaoliang Ma, Qingfu Zhang, Guangdong Tian, Junshan Yang, and Zexuan Zhu. On Tchebycheff decomposition approaches for multiobjective evolutionary optimization. IEEE Transactions on Evolutionary Computation, accepted, 2017, doi: 10.1109/TEVC.2017.2704118. (JCR 1, Top, IF: 10.629) [The 43th most frequently downloaded documents for IEEE Transactions on Evolutionary Computation according to the usage statistics in 2017年6月]

[2] Xiaoliang Ma, Fang Liu, Yutao Qi. etal. A multiobjective evolutionary algorithm based on decision variable analyses for multiobjective optimization problems with large-scale variables. IEEE Transactions on Evolutionary Computation, 2016, 20(2): 275-298. (SCI: 000374028000008, JCR 1, Top, IF: 10.629, 2016.4)

[3] Xiaoliang Ma, Fang Liu, Yutao Qi. etal. MOEA/D with Baldwinian learning inspired by the regularity property of continuous multiobjective problem. Neurocomputing. 2014, 145: 336–352. (SCI: 000342248100036, JCR 2 , IF: 3.317, 2014.12)

[4] Xiaoliang Ma, Fang Liu, Yutao Qi. etal. MOEA/D with opposition-based learning for multiobjective optimization problem. Neurocomputing. 2014, (146):48-64. (SCI:000342529500005, JCR 2 , IF: 3.317, 2014.12)

[5] Xiaoliang Ma, Yutao Qi, Lingling Li. etal. MOEA/D with uniform decomposition measurements for many-objective problems. Soft Computing. 2014.12, 18(12): 2541–2564. (SCI: 000345097100016, JCR 3, IF: 2.472, 2014.12)

[6] Xiaoliang Ma, Fang Liu, Yutao Qi. etal. MOEA/D with biased weight adjustment inspired by user-preference and its application on multi-objective reservoir flood control problem. Soft Computing, 20(12): 4999-5023, 2016. (SCI: 000386611200028, JCR 3, IF: 2.472, 2016.12)

[7] Yutao Qi, Xiaoliang Ma, Fang Liu. etal. MOEA/D with adaptive weight adjustment. Evolutionary Computation. 2014, 22(2): 231-264. (SCI: 000335565200002, JCR 2 , IF: 3.826, 2014.12)

[8] Yutao Qi, Liang Bao, Xiaoliang Ma, Qiguang Miao, Xiaodong Li. Self-adaptive multi-objective evolutionary algorithm based on decomposition for large-scale problems: A case study on reservoir flood control operation. Information Sciences. 367-368(1): 529-549, 2016. (SCI: 000382794400033, JCR 2 , IF: 4.832, 2016.10)

[9] Yang Junshan, Zhou Jiarui, Zexuan Zhu, Xiaoliang Ma, Zhen Ji. Iterative Ensemble Feature Selection for Multiclass Classification of Imbalanced Microarray Data. Journal of Biological Research, 2016, 23(13):1-9. (SCI: 000383686200004, JCR 4 , IF: 1.2, 2016.7)

[10] Yutao Qi, Fang Liu, Weiyuan Chang, Xiaoliang Ma, Licheng Jiao. Memetic immune algorithm for multiobjective optimization. Journal of Software. 2013, 24(7):1529-1544. (EI: 20133416646677)

[11] Xiaoliang Ma, Zexuan Zhu, Zhen Ji, Junshan Yang and Nuosi Wu, A comparative study on decomposition-based multi-objective evolutionary algorithms for many-objective optimization, 2016 IEEE Congress on Evolutionary Computation (CEC2016), 2016. (EI: 20165203176593)

[12] Yutao Qi, Xiaoliang Ma, Minglei Yin. etal. MOEA/D with a delaunay triangulation based weight Adjustment. In Genetic and Evolutionary Computation Conference 2014, Canada. 2014.7.12-16, 93-94. (EI: 20143318061998)

[13] Jun Xiao, Yanming Yang, Xiaoliang Ma, Jiarui Zhou, and Zexuan Zhu, Multi-objective memetic algorithm for solving pickup and delivery problem with dynamic customer requests and traffic information, 2016 IEEE Congress on Evolutionary Computation (CEC2016), 2016. (EI: 20165203176875)

[14] Qunjian Chen, Xiaoliang Ma, Yiwen Sun, Zexuan Zhu. Adaptive memetic algorithm based evolutionary multi-tasking single-objective optimization. The 11th International Conference on Simulated Evolution and Learning, 2017, 462-472.

[15] Yanming Yang, Xiaoliang Ma, Yiwen Sun, Zexuan Zhu. Multi-objective memetic algorithm based on three-dimensional request prediction for dynamic pickup-and-delivery problem with time windows. The 11th International Conference on Simulated Evolution and Learning, 2017, 810-820.

作者:管理员 时间:2018-5-23