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伍国华
个人简介

伍国华,博士,中南大学交通运输工程学院教授,博士生导师,物流工程系书记,智慧城市研究中心主任,湖南省杰出青年基金获得者,中国仿真学会智能仿真优化与调度专委会副秘书长,湖南省系统工程学会常务理事,IEEE计算智能协会调度前沿委员会副主席,中国仿真学会优秀科技工作者。国防科技大学本科、硕士和博士,国防科技大学优秀博士毕业生,加拿大阿尔伯塔大学访问学者。获吴文俊人工智能自然科学二等奖,湖南省自然科学三等奖,国防科技大学教学成果一等奖,荣立三等功一次。研究方向为智能优化与决策、机器学习、调度理论及应用、智能交通。已发表高水平SCI/EI论文50余篇,以第一作者和通讯作者在IEEE Transaction on Cybernetics (SCI,IF: 10.13), Information Sciences(SCI, IF: 5.50)、IEEE Transaction on System Man Cybernetics: System (SCI, IF: 7.35)、 Computer & Operations Research(SCI, IF: 3.03)等权威期刊发表SCI论文25篇,其中ESI前0.1%热点论文1篇,ESI前1%高被引论文3篇。主持国家高分重大专项、国防科技创新特区(重点)、装备预研研究项目、国家自科基金、国防科技委基金、湖南省自科基金等9项课题,参与国家、军队和省部级课题12项。


目前担任期刊Information Sciences(SCI, IF:5.51)的客座主编;期刊Swarm and Evolutionary Computation ( SCI, IF:6.33)的副主编、期刊International Journal of Bio-Inspired Computation ( SCI, IF:3.33)的编委和客座主编、期刊Memetic Computing ( SCI, IF: 1.96)的客座主编,期刊郑州大学学报(工学版)客座主编,在国际进化计算大会CEC 2017、CEC2018和CEC 2019连续组织单目标优化竞赛,撰写了相关技术报告。在智能优化主流会议WCCI、CEC、SSCI等多次组织专题会议,担任会议Chair。目前是IEEE TEVC、 IEEE TCYB、Information Sciences、Applied Soft Computing等20多个国际著名期刊的审稿人。


【招生信息】

每年招收多名硕士生和2~3名博士生(欢迎有意愿直博的同学提前联系)

硕士研究生招生方向:交通运输规划与管理,物流工程

博士研究生招生方向:交通运输工程


欢迎对研究感兴趣,以学习知识、锻炼能力为目的的本科生提前进入课题组学习交流



【联系方式】

办公室:中南大学铁道校区交通楼508

手机:13548596533

邮箱:guohuawu@csu.edu.cn



教育经历
2004.09.01—2008.06.30 于国防科技大学信息系统工程专业攻读并取得学士学位

2008.09.01—2009.12.30 于国防科技大学运筹学专业攻读硕士学位,并保送提前攻读博士学位

2010.03.01—2014.06.30 于国防科技大学运筹学专业攻读并取得博士学位,导师为邱涤珊教授

2012.10.01—2014.03.30 国家公派留学加拿大阿尔伯塔大学,导师为Witold Pedrycz 教授(加拿大皇家学院院士,IEEE Fellow)

工作经历
2014.06.30—2018.08.30 国防科技大学 系统工程学院 讲师

2018.09.01—至今 中南大学 交通运输工程学院 教授
社会兼职
国际期刊《Information Sciences》(SCI, IF:5.53,中科院一区)客座主编;

国际期刊《Swarm and Evolutionary Computation》(SCI, IF:6.31)副主编;

国际期刊《International Journal of Bio-Inspired Computation》(SCI, IF:3.40)编委;

国际期刊《International Journal of Bio-Inspired Computation》(SCI, IF:3.40)客座主编

国际期刊《Memetic Computing》(SCI, IF:2.67)客座主编

中国仿真学会智能仿真优化与调度专委会副秘书长

湖南省系统工程学会 常务理事

IEEE计算智能协会调度前沿委员会 副主席

第一届智能仿真优化与调度大会 程序主席

国际进化计算大会CEC 2017和CEC 2018单目标进化优化竞赛Chair;

在智能优化主流会议WCCI、CEC、SSCI等多次组织专题会议,担任会议Chair;

目前是IEEE TEVC、 IEEE TCYB、IEEE System Journal、Information Sciences、Applied Soft Computing等20多个国际著名期刊的审稿人。
科研方向
智能优化方法、人工智能、调度理论及应用、智能交通。

【近期研究兴趣】

(1)集群机器人/无人机系统;

(2)自适应/集成进化算法设计;

(3)变量约简理论及应用;

(4)进化多目标优化理论;

(5)基于深度/强化学习的自动优化算法设计;

(6)文献与交通大数据挖掘

(7)对地观测网络资源协同调度;

(8)基于车机(汽车与无人机)协同的物流配送与巡线调度;

(9)电动汽车路径优化方法;

(10)航天资源(卫星)优化调度理论方法;

(11)军事装备、人员与后勤物资的联合投送方法;


讲授课程
2018年秋季学期,国际班本科生和研究生《运筹学》
学术成果
【主持项目】

1.国防装备预研项目,弱标注XXX深度学习技术,主持,2019-2020

2.国防科技创新特区项目(重点),不完全信息集群博弈XXX智能优化方法,主持,2019-2019,

3.湖南省自然科学杰出青年基金, 2019JJ20026, 主持,2019-2022

4.中南大学特聘教授启动基金,主持, 2018-2022

5.高分辨率对地观测系统重大专项, 异构XXX任务规划方法研究, GFZX04060103, 主持, 2015-2016

6.国家自然科学基金青年基金, 进化优化中的变量约简策略研究, 61603404, 主持, 2017-2019

7.国防科技委基金,XXX协同规划调度框架、模型和算法研究,201724015,主持, 2017-2019

8.军内横向, xx卫星运行仿真平台, 主持, 2017-2018

9.省自然科学基金青年基金, 空天一体化对地观测系统协同任务规划方法研究, 2017JJ3369,主持,2017-2019

10.横向课题,无人集群群体智能与任务规划方法研究,主持,2019-2020.

11.横向课题,超机动敏捷卫星成像调度方法研究,主持,2019-2019.

12.横向课题,高超声速飞行器健康评估方法研究,主持,2019-2019.

13.武器装备预研项目, 面向快速响应XXX设计与评估技术, 51322010102, 参与, 2011-2015

14.装备预研重点基金, 面向XXX卫星综合应用模式与运行机制研究, 0201051115114KY, 参与, 2015-2017

15.武器装备预研项目, XXX支援任务需求生成与表达, 0201051117047KY, 参与, 2016-2019

16.高分辨率对地观测系统重大专项, “XXX快速协同规划与调度技术”,参与, 2011-2014


【发表论文】


【2019年】

[1] Huangke Chen, Ye Tian, Witold Pedrycz, Guohua Wu*(通讯),, et.al., Hyperplane Assisted Evolutionary Algorithm for Many-Objective Optimization Problems, IEEE Transactions on Cybernetics, 2019, DOI: 10.1109/TCYB.2019.2899225 (IF: 10.1, SCI, JCR一区, 中科院一区)

[2] Huangke Chen, Guohua Wu*(通讯), Witold Pedrycz, et.al., An Adaptive Resource Allocation Strategy for Objective Space Partition based Multiobjective Optimization, IEEE Transactions on System Man Cybernetics: System, DOI: 10.1109/TSMC.2019.2898456 (IF: 7.35, SCI, JCR一区)

[3] Guohua Wu, Rammohan Mallipeddi, P. N. Suganthan. Ensemble Strategies for Population-based Optimization Algorithms-A Survey. Swarm and Evolutionary Computation, 2018, 2019, 44: 695-711. (IF: 6.33, JCR一区)

[4] Haifeng Li, Li Chen, Hailun Ding, Qi Li, Bingyu Sun, Guohua Wu*(通讯), Procedural Learning with Robust Visual Features via Low Rank Prior, IEEE ACCESS, 2019, 7:18884-18893 (SCI, IF: 4.10, JCR 一区)

[5] Yongming He, Yingwu Chen, Jimin Lu, Cheng Chen, Guohua Wu*(通讯), Scheduling multiple agile earth observation satellites with an edge computing framework and a constructive heuristic algorithm, Journal of Systems Architecture, 2019, DOI: 10.1016/j.sysarc.2019.03.005 (SCI, CCF B类)

[6] Partha P. Biswas, P. N. Suganthan, Guohua Wu*(通讯), G. J. Amaratunga, Parameter estimation of solar cells using datasheet information with an adaptive differential evolution algorithm, Renewable Energy, 132(2019): 425-438 (SCI, IF:5.44, JCR 一区)

[7] Anping Lin, Wei Sun* , Hongshan Yu, Guohua Wu*(通讯), Hongwei Tang, Adaptive comprehensive learning particle swarm optimization with cooperative archive,Applied soft computing, 2019, doi.org/10.1016/j.asoc.2019.01.047 (IF: 4.87, SCI, JCR一区)

[8] 李夏苗,陈新江,伍国华*(通讯),,等.考虑断点续传的中继卫星调度模型及启发式算法[J].航空学报, 2019, 40(11): 323233 (一级学报, EI检索)

[9] Yao Liu, Zhong Liu, Jianmai Shi, Guohua Wu, Chao Chen, Optimization of Base Location and Patrol Routes for Unmanned Aerial Vehicles in Border Intelligence, Surveillance, and Reconnaissance. Journal of Advanced Transportation, 2019, doi.org/10.1155/2019/9063232 (IF:1.98,SCI,JCR二区)

【2018年】

[10] Guohua Wu, X. Shen, H. Li, P.N. Suganthan, Ensemble of differential evolution variants, Information Sciences, 423 (2018): 172-186. (SCI, IF:5.53,ESI 前1%高引, 中科院一区, TOP期刊)

[11] R. Wang, S. Lai, Guohua Wu*(通讯), L. Xing, L. Wang, and H. Ishibuchi, "Multi-clustering via evolutionary multi-objective optimization," Information Sciences, vol. 450, pp. 128-140, 2018. (SCI, IF:5.53,中科院一区, TOP 期刊)

[12] 陈黄科, 伍国华*(通讯), 霍离俗, 戚玉涛. 基于目标空间划分的自适应多目标进化算法, 软件学报, 2018,28(9):2649-2663. (一级学报, EI检索)

[13] Huangke Chen, Jinming Wen, Witold Pedrycz, Guohua Wu*(通讯), Big Data Processing Workflows Oriented Real-Time Scheduling Algorithm using Task-Duplication in Clouds, IEEE Transactions on Big Data, 10.1109/TBDATA.2018.2874469

[14] Xin Shen, Guohua Wu*(通讯), Rui Wang, Huangke Chen, Haifeng Li, Janmai Shi. A Self-adapted Across Neighborhood Search Algorithm with Variable Reduction Strategy for Solving Non-Convex Static and Dynamic Economic Dispatch Problems, IEEE ACCESS, 2018, 41314 - 41324. (SCI, IF:4.10,JCR 一区)

[15] Anping Lin, Wei Sun*, Hongshan Yu, Guohua Wu*(通讯), Hongwei Tang, Global genetic learning particle swarm optimization with diversity enhancement by ring topology, Swarm and Evolutionary Computation, 2018, 44: 571-583 (SCI, JCR一区)

[16] Huangke Chen, Jianghan Zhu, Guohua Wu*(通讯), Lisu Huo, Cost-efficient reactive scheduling for real-time workflows in clouds, Journal of Supercomputing, 2018, 11: 6291–6309 (SCI, IF: 2.16, JCR二区)

[17] Guohua Wu, Longfei Zhang, Minfan He, Ying Yu, Huangke Chen, Rui Wang. An Across Neighborhood Search Algorithm with a Solution Difference Perturbation Mechanism for Solving Economic Dispatch Problems. The 10th International Conference on Advanced Computational Intelligence (ICACI 2018), Xiamen, China, 2018, 640-645.

[18] Y. Wang, Z Liu, J Shi, Guohua Wu, R Wang, Joint Optimal Policy for Subsidy on Electric Vehicles and Infrastructure Construction in Highway Network, Energies 11 (9), 2479, 2018

[19] Q. Liu, R. Wang, Y. Zhang, Guohua Wu, and J. Shi, "An Optimal and Distributed Demand Response Strategy for Energy Internet Management," Energies, vol. 11, p. 215, 2018

[20] Huangke Chen, Xiaomin Zhu, Witold Pedrycz, Shu Yin, Guohua Wu and Hui Yan, PEA: Parallel Evolutionary Algorithm by Separating Convergence and Diversity for Large-Scale Multi-Objective Optimization, 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), 2018, 223- 232.

[21] Qingzheng Xu, Heng Yang, Na Wang, Rong Fei, Guohua Wu, A Uniform Approach for the Comparison of Opposition-Based Learning, International Conference on Sensing and Imaging, 2018, 563-574.

【2018年之前】

[22] Guohua Wu, Witold Pedrycz, Haifeng Li, Manhao Ma, and Jin Liu. Coordinated Planning of Heterogeneous Earth Observation Resources. IEEE Transactions on System Man Cybernetics: System, 46( 2016) , 109-125 (IF: 7.35, SCI, JCR一区)

[23] Guohua Wu, Rammohan Mallipeddi, P. N. Suganthan, Rui Wang, Huangke Chen, Differential Evolution with Multi-Population Based Ensemble of Mutation Strategies. Information Sciences, 329 (2016): 329-345. (IF: 5.53, SCI,ESI 前1%高引,中科院一区, TOP 期刊)

[24] Guohua Wu, Across neighborhood search for numerical optimization. Information Sciences, 329 (2016): 597-618. (IF: 5.53, SCI,中科院一区, TOP 期刊)

[25] Guohua Wu, Jin Liu, Manhao Ma, and Dishan Qiu. A two-phase scheduling method with the consideration of task clustering for earth observing satellites. Computers & Operations Research: 40 (2013): 1884–1894 (IF: 3.0, SCI,JCR一区)

[26] Guohua Wu, Huilin Wang, Witold Pedrycz, Haifeng Li, Ling Wang. Satellite observation scheduling with a novel adaptive simulated annealing algorithm and a dynamic task clustering strategy. Computers & Industrial Engineering, 113(2017):576–588. (SCI, IF:3.52,JCR一区)

[27] Guohua Wu, W. Pedrycz, P. N. Suganthan, Haifeng Li. Using Variable Reduction Strategy to Accelerate Evolutionary Optimization, Applied soft computing, 61(2017): 283-293. (SCI, IF: 4.87,JCR一区)

[28] Guohua Wu, Witold Pedrycz, P. N. Suganthan, Rammohan Mallipeddi. A Variable Reduction Strategy for Evolutionary Algorithms Handling Equality Constraints. Applied soft computing, 37 (2015): 774-786. (IF: 4.87, SCI, JCR一区)

[29] Guohua Wu, D. Qiu, Y. Yu, W. Pedrycz, M. Ma. Superior solution guided particle swarm optimization combined with local search techniques. Expert Systems with Applications: 41 (2014): 7536-7548. (IF: 4.30, SCI, JCR一区)

[30] Guohua Wu, R. Mallipeddi, P. N. Suganthan, "Problem Definitions and Evaluation Criteria for the CEC 2017 Competition and Special Session on Constrained Single Objective Real-Parameter Optimization", Technical Report, Nanyang Technological University, Singapore, December 2016.

[31] Guohua Wu, Manhao Ma, Jianghan Zhu, and Dishan Qiu. Multi-satellite observation integrated scheduling method oriented to emergency tasks and common tasks. Journal of Systems Engineering and Electronics: 23(2012):723-733 (IF: 0.72, SCI,JCR四区)

[32] Guohua Wu, W. Pedrycz, H. Li, D. Qiu, M. Ma, and J. Liu. Complexity reduction in the use of evolutionary algorithms to function optimization: a variable reduction strategy. Scientific World Journal: 2013,1-8. (SCI检索WOS:000326531800001,JCR二区)

[33] Guohua Wu, Witold Pedrycz, Manhao Ma, Dishan Qiu, Haifeng Li, and Jin Liu. A Particle swarm optimization variant with an inner variable learning strategy. Scientific World Journal: 2014,2014 ,1-12 (SCI检索WOS:000326531800001,JCR二区)

[34] Guohua Wu, Witold Pedrycz, Dishan Qiu, and Manhao Ma. A New granular particle swarm optimization variant for granular optimization problems. 2013 Joint IFSA World Congress NAFIPS Annual Meeting:2013 ,24-28

[35] 王慧林, 伍国华*(通讯), 马满好. 多类异构对地观测平台协同任务规划方法 航空学报, 2016, 37(3):997-1014. (一级学报, EI检索)

[36] Xincheng Hu, Witold Pedrycz, Guohua Wu, Xianmin Wang. Data Reconstruction with Information Granules:An Augmented Method of Fuzzy Clustering. Applied Soft Computing, 55(2017):523–532. (IF: 4.87, SCI检索源,JCR一区)

[37] Rui Wang, Guozheng Li, Mengjun Ming, Guohua Wu, Ling Wang. An efficient multi-objective model and algorithm for sizing a stand-alone hybrid renewable energy system. Energy, 2017, DOI: 10.1016/j.energy.2017.11.085 (IF:4.5, SCI检索源)

[38] Wei Sun, Anping Lin, Hongshan Yu, Qiaokang Liang, Guohua Wu. All dimension neighborhood particle swarm optimization with randomly selected neighbors. Information Sciences, 405(2017): 141-156. (IF:5.53,SCI检索源,JCR一区)

[39] Rui Wang, Jian Xiong, Guohua Wu, et.al., On the effect of reference point in MOED/D for multi-objective optimization. Applied Soft Computing,58 (2017): 25-34. (IF:4.87,SCI检索源,JCR一区)

[40] Houyi Yan., Lvlin Hou, Y. Ling, Guohua Wu. (2016). Optimizing complex networks controllability by local structure information. International Journal of Modern Physics C, 165-178. (IF:1.20, SCI检索WOS:000382830200005,JCR三区)

[41] R Mallipeddi, Guohua Wu, M Lee, PN Suganthan.Gaussian adaptation based parameter adaptation for differential evolution. 2014 IEEE Congress on Evolutionary Computation (CEC),45-52 ( EI检索)

[42] KeBin Gao, Guohua Wu*, and J. H. Zhu. "Multi-Satellite Observation Scheduling Based on a Hybrid Ant Colony Optimization." Advanced Materials Research 765-767(2013):532-536. (EI检索, 通讯作者)

[43] Dishan Qiu, Qun Tan, Manhao Ma, Guohua Wu. Research on Satisfied Degree Evaluation Method for Satellite Imaging Reconnaissance Requirement, Computer Engineering, 2012, 38(8):256-259. ( EI检索)

[44] Guohua Wu, Manhao Ma, Huilin Wang. Multi-satellite Observation Scheduling Based on Task Clustering, Acta Aeronautica ET Astronautica Sinica, 2011, 7: 1275-1282 (In Chinese)

伍国华, 马满好, 王慧林, 等. 基于任务聚类的多星观测调度方法[J]. 航空学报. 2011,(07):1275-1282. (EI检索,一级学报)

[45] Guohua Wu, Manhao Ma, Huilin Wang, Dishan Qiu, Multi-Phase Scheduling Method with Task Clustering for Satellite Observation, Journal of Astronautics, 2011, 10: 2273-2279. (In Chinese)

伍国华, 马满好, 王慧林, 等. 考虑任务聚类的多星观测分阶段调度方法研究[J]. 宇航学报. 2011,(10):2273-2279. EI检索)

[46] 伍国华, 马满好. 路径交叉检测与消除方法和邻节点置换方法改进TSP的解[J]. 计算机应用研究, 2011, 28(2):485-487.

[47] 伍国华, 马满好, 邱涤珊,等. 基于PDDL的对地观测卫星任务规划建模研究[J]. 遥感信息, 2010, 2010(3):94-98.

[48] 王慧林, 黄维, 邱涤珊, 伍国华. 空域频域不确定条件下电磁探测卫星规划方法研究[J]. 国防科技大学学报. 2011,(01):149-154.(EI检索)

[49] 邱涤珊, 郭浩, 贺川, 伍国华. 敏捷成像卫星多星密集任务调度方法[J]. 航空学报. 2013,(04):882-889 (EI检索)

[50] 江建清, 朱晓敏, 伍国华, 等. 面向应急对地观测任务的多飞艇协同分配方法[J]. 系统工程与电子技术. 2013,(02):317-325.(EI检索)

[51] 郭浩, 邱涤珊, 伍国华, 等. 基于改进蚁群算法的敏捷成像卫星任务调度方法[J]. 系统工程理论与实践. 2012,(11):2533-2539.(EI检索)

[52] 郭浩, 伍国华, 邱涤珊. 敏捷成像卫星密集任务聚类方法[J]. 系统工程与电子技术. 2012,(05):931-935.(EI检索)

[53] 贺川, 邱涤珊, 朱晓敏,伍国华 . 基于滚动优化策略的成像侦察卫星应急调度方法[J]. 系统工程理论与实践, 2013, 33(10):2685-2694.(EI检索)

[54] 王慧林, 黄小军, 伍国华,等. 基于时序自组半边图的航天资源任务聚合结构研究[J]. 系统仿真学报, 2010(10):2302-2306.(EI检索)









学术奖励

2018年,吴文俊人工智能自然科学二等奖(排名第二)

2018年,中国仿真学会优秀科技工作者

2019年,湖南省自然科学三等奖(排名第二)

2018年,IEEE CEC 2018 国际高维目标优化竞赛第二名(AMPDEA算法, Huangke Chen and Guohua Wu)

2018年,智能仿真优化与调度大会优秀论文三等奖

2018年,IEEE CEC 2018 高维目标优化竞赛第二名

2016年,国防科技大学教学成果一等奖(排名第6)

2016年,国防科技大学本科教学优秀个人三等奖

2016年,优秀基层干部

2016年,优秀本科毕业论文指导老师

2015年,优秀基层干部

2014年,三等功

2014年,国防科技大学优秀博士毕业生