张国晨 简历

张国晨，1980.9，男，十大网投正规信誉官网, 复杂系统与计算智能研究所所长， 副教授。2015年毕业于兰州理工大学，控制科学与工程专业，博士。计算机学会太原分会副秘书长、山西省通信协会理事、中国仿真学会智能仿真优化与调度专委会委员。主要研究方向：计算机网络，车辆调度，智能计算等。已发表SCI、EI论文二十余篇，主持山西省自然科学基金两项、主持省教改项目一项、安徽省重点实验室开放课题一项、参与多项国家基金和横向合作项目的研究工作。多年来一直从事计算机网络课程的教学工作，获得山西省教学成果一等奖一项、作为指导老师带领学生多次参加互联网+、计算机博弈等比赛并取得多次获一等奖、二等奖优异成绩。

教育与工作经历：

(1) 2015.9至今,     十大网投正规信誉官网， 十大网投正规信誉官网,  教师

(2) 2006.9–20015.9,  十大网投正规信誉官网,  应用科学学院,  教师

(3) 2010.9–2015.12,  兰州理工大学,  控制理论与控制工程,  博士

(4) 2003.9–2006.7,  十大网投正规信誉官网,  计算机科学与技术,  硕士

(5) 1999.9–2003.7,  十大网投正规信誉官网,  计算机科学与技术,  学士

科研项目：

(1)山西省教学改革创新项目，新工科理念下基于项目导入模式的计算机网络课程教学改革，2022.6-2024.6，在研，主持

(2)安徽大学开放课题，求解计算费时约束优化问题的进化算法研究，2021.7-2023.7，在研，主持

(3)山西省自然科学基金，201901D111264，代理模型辅助的动态车辆调度问题优化方法研究，2019.12-2022.12，在研，主持

(4)山西省青年科学基金，201601D021083，结合不确定性的混凝土罐车调度问题 研究，2016.01-2018.12，已结题，主持

(5)山西省优秀人才科技创新项目，201805D211028，数据驱动的复杂系统进化优化，2018.12-2021.12，已结题，参加

(6)山西省面上自然基金项目，201801D121131, 代理模型辅助的优化算法在复杂多目标优化问题中的应用研究，2018.12-2020.12，已结题，参加

(7) 国家青年科学基金项目，71701140，可修多部件系统视情非完美维修及其与备件库存的联合决策研究，2018.01-2020.12，已结题，参加

(8) 国家青年科学基金项目，61703297，具有随机相关性的多部件系统剩余寿命预测方法和维修决策建模研究，2018.01-2020.12，已结题，参加。

(9) 山西省高等学校大学生创新创业训练项目，PassWord-Shell的设计和实现，2017.6-2019.6，结题，指导老师

主讲课程：

本科：计算机网络，数据结构

研究生：高级/高等计算机网络

获奖：

(1)山西省教学成果奖， 基于项目任务驱动的计算机网络课程教学模式改革与实践，一等奖，2019

(2)互联网+创新创业大赛优秀指导教师，2019

(3)全国计算机博弈大赛优秀指导教师，2019-2022

(4)计算机博弈大赛，一等奖1次，二等奖1次，指导教师，2022

(5)计算机博弈大赛，一等奖1次，指导教师，2021

(6)计算机博弈大赛，一等奖1次，二等奖2次，指导教师，2020

(7)十大网投正规信誉官网教学竞赛，二等奖，2010

论文：

[1] Zhang G, Zeng J, Zhang J. Rescheduling strategy of ready-mixed concrete vehicles: A case study of dynamic requirements of customers[J]. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2017, (SCI)

[2] Zhang G C, Zeng J C, Zhang J H. Modelling and optimising of ready-mixed concrete vehicle scheduling problem with stochastic transportation time[J]. International Journal of Wireless and Mobile Computing, 2016, (EI)

[3]Guochen Zhang, Hui Shi, Zhaobo Chen, Xiaobo Li. Research on preventive maintenance strategy of multi-equipment system based on the Internet of things[J]. Int. J. Wireless and Mobile Computing. 2020, (EI)

[4] Zhang G C, Zeng J C, Modelling and solving for ready-mixed concrete scheduling problems with time dependence[J] , Int.J of Computing Science and Mathematics, 2013,(EI)

[5] Zhang G C, Zeng J C, Ready-Mixed Concrete Vehicle Rescheduling Method Based on the Internet of Things[J], Sensor Letters, 2014, (EI)

[6] Zhang G C, Zeng J C, Optimizing of ready-mixed concrete vehicle scheduling problem by hybrid heuristic algorithm[J], Computer Modelling & New Technologies. 2014,(EI)

[7] 张国晨，孙超利，石慧，李晓波，结合车辆日检的混凝土罐车调度问题研究，工业工程，2020，（核心）

[8] 张国晨, 刘鹏飞，孙超利. 一种新环境选择策略的多模态多目标优化算法. 应用科学学报. 2022，（核心）

[8]Hao Wang, Chaoli Sun, Guochen Zhang, Jonathan E. Fieldsend, Yaochu Jin, Non-dominated Sorting on Performance Indicators for Evolutionary Many-objective Optimization, Information Sciences, 2021, 551, 23-38. (SCI,)

[9]Peng Liao, Chaoli Sun, Guochen Zhang, Yaochu Jin, Multi-surrogate Multi-tasking Optimization of Expensive problems, Knowledge-Based Systems, 2020, 205, 106262. (SCI,)

[10]Yi Zhao, Chaoli Sun, Jianchao Zeng, Ying Tan, Guochen Zhang, A Surrogate-ensemble Assisted Expensive Many-objective Optimization, Knowledge-Based Systems, 2021, 211, 106520. (SCI)

[11]Hao Wang, Mengnan Liang, Chaoli Sun, Guochen Zhang, Liping Xie, Multiple-strategy learning particle swarm optimization for large-scale optimization problems, Complex & Intelligent Systems, 2020, accepted. (SCI,)

[12]Shufen Qin, Chaoli Sun, Guochen Zhang, Xiaojuan He, Ying Tan, A modified particle swarm optimization based on decomposition with different ideal points for many-objective optimization problems, Complex & Intelligent Systems, 2020, 6(2), 263-274. (SCI)

[13]Guoxia Fu, Chaoli Sun, Ying Tan, Guochen Zhang, Yaochu Jin, A Surrogate-assisted Evolutionary Algorithm with Random Feature Selection for Large-scale Expensive Problems, 16th International Conference on Parallel Problem Solving from Nature (PPSN), 2020, accepted. (CCF B类会议)

[14]Shufen Qin, Chaoli Sun, Yaochu Jin, Guochen Zhang, Bayesian Approaches to Surrogate-Assisted Evolutionary Multi-objective Optimization: A Comparative Study, 2019 IEEE Symposium Series on Computational Intelligence (SSCI)

[15]Wang, H., Sun, C., Zhang, G., Fieldsend, J. E., & Jin, Y. Non-dominated sorting on performance indicators for evolutionary many-objective optimization. Information Sciences, 2021,(SCI)

[16]Qin, S., Sun, C., Zhang, G., He, X., & Tan, Y. A modified particle swarm optimization based ondecomposition with different ideal points for many-objective optimization problems. Complex & Intelligent Systems, 2020,(SCI)

[17]Qin, S., Li, C., Sun, C., Zhang, G., & Li, X. Multiple infill criterion-assisted hybrid evolutionary optimization for medium-dimensional computationally expensive problems. Complex & Intelligent Systems, 2022,(SCI)

[18]Wang, H., Liang, M., Sun, C., Zhang, G., & Xie, L. Multiple-strategy learning particle swarm optimization for large-scale optimization problems. Complex & Intelligent Systems, 2021,(SCI)

[19]Zhao, Y., Sun, C., Zeng, J., Tan, Y., & Zhang, G. A surrogate-ensemble assisted expensive many-objective optimization. Knowledge-Based Systems, 2021,(SCI)

[20]王浩,孙超利 & 张国晨..基于估值不确定度排序顺序均值采样的昂贵高维多目标进化算法. 控制与决策. 2021,(EI)

[21]孙超利,李婵,秦淑芬,张国晨 & 李晓波.基于不确定度采样准则的费时问题优化算法. 控制与决策,2022,(EI)