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张新功
2015-04-28 14:16     (点击: )

个 人 信 息

姓名

张新功

性别

民族

出生日期

政治面貌

中共党员

职称/职务

教授

毕业学校

上海理工大学

学历

博士

博导/硕导

硕导

学科专业

运筹学、管理科学与工程

研究方向

组合最优化、排序论

联系方式

zhangxingong@cqnu.edu.cn

个人简历

20029—20056月 河南大学 数学与统计学院本科;

20059—20086月 郑州大学数学系,运筹学与控制论 硕士;

20089—20176月 上海理工大学 管理科学与工程,博士;

20117月至今重庆师范大学数学学院.

主要研究项目与科研奖励

主持的科研项目

1.重庆市教委重点项目:公平定价下的双代理新型排序问题研究,KJZD-K20200050120201001-20230930

2.重庆市教委研究生教改重点项目: 基于创新理念的系统理论研究生专业课程体系优化研究,yjg182019201805-202104

3.重庆市科委项目: 多代理竞争排序的新型排序研究,cstc2018jcyjAX0631,  20180701-20210630

4.重庆市教委项目: 与时间相关的若干机器排序问题研究, KJ1600326, 201607-201806

5.国家自然科学基金青年基金: 基于退化效应或可控加工时间的竞争排序研究, 11401065,  201501-201712 

6.重庆市自然科学基金:  学习或退化效应下的重新排序和竞争排序研究, cstc2014jcyjA00003, 2014-2016 

7.中国博士后基金资助项目: 基于退化效应或可控加工时间的竞争排序研究(2014T70854)

8.中国博士后基金面上项目: 学习或退化效应下重新排序和竞争排序研究(2013M540698)

9.国家自然科学基金天元专项基金: 重新排序问题及其研究,11226237201301-201312

10.重庆市教委项目: 现代排序模型研究,KJ120624201201-201412

11.上海市创新基金项目: 学习与退化效应下排序模型研究;(JWCXSL100)201001-201201;

12.重庆市高校首批精品在线开放课程(渝教高函〔201753)重庆市教委;

13.重庆市级教改项目203298,基于在线开放课程资源的混合式课堂教学模式实践与探索---以高等代数为例.

参与项目

1.国家科学基金重大项目:最优化问题的人工智能方法11991020。子课题组合优化的人工智能求解方法及应用11991022,子课题第二参与人,202001-202412

2.国家自然科学基金面上项目:11971443机器具有指派费用的若干排序问题研究,2020.01-2023.12

3.国家社科基金项目面上项目:18BKS151,习近平新时代中国特色社会主义德育思想研究,2018.06-2021.06

4.国家自然科学基金面上项目:11571321同类机上的若干排序问题研究,2016/01-2019/12 

5.国家自然科学基金青年基金:61302180,忆阻神经网络建模分析与应用,2014/01-2016/12

代表性成果

1.Parallel-machine  scheduling with linear deteriorating jobs and preventive maintenance  activities under a potential machine disruption, 2020, Computers & Industrial Engineering,  2020, 145,  106482.

2.Metaheuristics for  two-stage flow-shop assembly problem with a truncation learning function,  Engineering Optimization, 202010.1080/0305215X.2020.1757089

3.Exact and heuristic  algorithms for scheduling on two identical machines with early work  minimization. Computers & Industrial  Engineering, 2020, 144, 106449. 

4.Single machine and  flowshop scheduling problems with sum-of-processing time based learning  phenomenon. Journal of Industrial and Management Optimization, 2020, 16(1):  231-244.

5.Heuristic and  iterative greedy algorithms for the total weighted completion time order  scheduling with release times. Swarm and Evolutionary Computation, 2019, 44: 913-926. 

6.Tardiness  minimization for a customer order scheduling problem with  sum-of-processing-time-based learning effect. Journal of the Operational  Research Society, 2019, 70:3, 487-501.

7.Competitive  two-agents scheduling problems to minimize the weighted combination of  makespan on two-machine open shop. Engineering Optimization, 2018, 50,  684-697.

8.Machine scheduling  problems under deteriorating effects and deteriorating rate-modifying  activities.  Journal of the Operational Research Society. 2018, 69(3):  439-448.

9.Single-machine  scheduling problems with a learning effect matrix. Iranian Journal of Science and Technology, Transactions A:  Science, 2018,  42(3): 1327–1335.

10.  Resource-constrained  scheduling problems with general truncated sum-of-processing-time-dependent  effect under single machine and unrelated parallel machines. Computers &  Industrial Engineering, 2017, 110: 344–352.

11.Single-machine common/slack due window  assignment problems with linear decreasing processing times. Engineering  Optimization, 2017, 49(8): 1388–1400.  

12.Two-agent scheduling problems on a  single-machine to minimize the total weighted late work, Journal of Combinatorial Optimization,  2017, 33 (3): 945–955.  

13.Scheduling with  non-decreasing deterioration jobs and variable maintenance activities on a  single machine. Engineering Optimization, 2017, 49, (1): 84-97.

14.Patients scheduling problems with  deferred deteriorated functions. Journal of Combinatorial Optimization, 2015, 30(4):  1027-1041.  

15.Single-machine  scheduling CON/SLK due window assignment problems with sum-of-processed times  based learning effect. Applied Mathematics and Computation, 2015, 250:  628-635.

16.Common due-window  assignment and scheduling of job-dependent deteriorating jobs and multiple  deteriorating maintenance activities. Asia-Pacific Journal of Operational  Research. 2014, DOI: 10.1142/S0217595914500043.

17.A note on machine  scheduling with sum-of-logarithm-processing-time based and position-based  learning effects .Information Sciences, 2012, 187: 298-304.

18.Single-machine  scheduling problems with time-dependent and position-dependent learning  effects. Annals of Operations Research, 2011, 186:345-356.

19.Single-machine  scheduling problems with release time of jobs depending on resource  allocated. International Journal of Advanced Manufacture Technology, 2011,  57:1175-1181.

20.Machine scheduling  problems with a general learning effect. Mathematical and Computer Modeling,  2010, 51:84-90.

21.Single-machine group  scheduling problems with deteriorated and learning effect. Applied  Mathematics and Computation, 2010, 56:1259-1266.

22.Single-machine  scheduling problems with a sum-of-processing time- based learning function.  International Journal of Combinatorics, 2009, 624108.

 

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重庆师范大学数学科学学院  地址:重庆市沙坪坝区大学城中路37号 汇贤楼
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