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付亚平

2019-01-24  点击:[]

 

 

付亚平,博士,副教授,硕士生导师

邮箱:fuyaping0432@163.com.

 

教育背景:

2015.9-2016.4 东北大学 系统工程 博士

2011.8-2015.4 东北电力大学 企业管理 硕士

 

研究方向

制造系统计划与调度、进化多目标优化、仿真优化

 

科研成果:

Journal paper:

1. Fu Y. P., Ding J. L., Wang H. F. and Wang J.W.* (2018), Two-objective stochastic flow-shop scheduling with deteriorating and learning effect in Industry 4.0-based manufacturing system, Applied Soft Computing, 68: 847-855. (SCI index)

2. Fu Y. P. Wang H. F., Huang Min (2018), Integrated scheduling for a distributed manufacturing system: a stochastic multi-objective model, Enterprise Information Systems, Doi: 10.1080/17517575.2018.1545160. (SCI index)

3. Fu Y. P., Wang H. F.*, Tian G. D., Li Z. W. and Hu H. S. (2018), Two-agent stochastic flow shop deteriorating scheduling via a hybrid multi-objective evolutionary algorithm, Journal of Intelligent Manufacturing, Doi: org/10.1007/s10845-017-1385-4. (SCI index)

4. Fu Y. P.,Wang H. F., Huang M., Ding J. L. (2017), Multiobjective flow shop deteriorating scheduling problem via an adaptive multipopulation genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2017(2), doi: 10.1177/0954405417691553. (SCI index)

5. Fu Y. P., Wang Z. Z,Zhang J. H., Wang Z. L. (2017),A blocking flow shop deteriorating scheduling problem via a hybrid chemical reaction optimization. Advances in Mechanical Engineering, 2017,9(6):168781401770137. (SCI index)

6. Fu Y. P., Tian G. D., Li. Z. W., Wang Z. L. (2017), Parallel machine scheduling with dynamic resource allocation via a master-slave genetic algorithm. IEEJ Transactions on Electrical and Electronic Engineering. 2018, 13(5): 748-756. (SCI index)

7. Fu Y. P. Jiang G. J., Tian G. D., Wang Z. L., Job scheduling and resource allocation in parallel-machine system via a hybrid nested partition method, IEEJ Transactions on Electrical and Electronic Engineering, 2018, doi.org/10.1002/tee.22842.

8. Fu Y. P., Wang H.F., Huang M. and Wang J.W.* (2017). A decomposition based multiobjective genetic algorithm with adaptive multipopulation strategy for flowshop scheduling problem. Natural Computing, doi:10.1007/s11047-016-9602-1.

9. Wang H. F., Fu Y.P., Huang M., Huang G.Q. and Wang J.W.* (2017). A NSGA-II based memetic algorithm for multiobjective parallel non-identical flowshop scheduling problem, Computers & Industrial Engineering, doi:10.1016/j.cie.2017.09.009. (SCI index)

10. Wang H. F., Fu Y. P., Huang M., G.Q. Huang and Wang J.W.* (2017). A hybrid evolutionary algorithm with adaptive multi-population strategy for multi-objective optimization problems. Soft Computing, 21(20): 5975-5987. (SCI index)

11. Wang H.F., Fu Y. P., Huang M. and Wang J.W.* (2016). Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs, Enterprise Information Systems, 10(3): 268-285. (SCI index)

12. 付亚平,王洪峰*,黄敏,王兴伟. 基于自适应多种群策略的混合多目标优化算法. 系统工程学报, 2017, 32(6): 737-749.

13. 黄敏,付亚平*,王洪峰,朱兵虎,王兴伟. 设备具有恶化特性的作业车间调度模型与算法.自动化学报, 2015,41(3):551-558.EI index

14. 付亚平,黄敏,王洪峰*,王兴伟. 混合并行机调度问题的多目标优化模型及算法.控制理论与应用, 2014, 31(11):1510-1516. (EI index)

15. 付亚平,王洪峰*,黄敏,王兴伟. 面向多目标流水车间调度的自适应多种群多目标遗传算法. 控制理论与应用, 2016, 33(10): 1281-1288. (EI index)

16. 付亚平,王洪峰*,黄敏,王兴伟. 设备具有恶化特性的多目标流水车间调度模型与算法. 系统工程理论与实践, 2016, 36(11): 2941-2950. (EI index)

17. 付亚平, 王洪峰*, 黄敏. 面向多目标优化问题的多种群遗传算法. 东北大学学报(自然科学版), 2016, 37(3): 314-318. (EI index)

18. Fu Y. P., Wang H. F.*, Huang M (2014). Locate multiple Pareto optima using a species-based multi-objective genetic algorithm. Bio-Inspired Computing-Theories and Applications. Springer Berlin Heidelberg, 2014: 128-137. (EI index)

 

Conference paper:

1. Fu Y. P., Zhou M. C., Guo X. W., Qi Liang, (2018) Stochastic disassembly sequence optimization for the minimal cost and energy consumption [C]// In Proceeding Conference of IEEE Systems, Man and Cybernetics, System. (EI Index)

2. Fu Y. P., Huang M., Wang H. F. (2014). Guanjie Jiang. An improved NSGA-II to solve multi-objective optimization problem [C]// The 26th IEEE Chinese Control and Decision Conference (2014 CCDC), IEEE, 2014: 1037-1040. (EI index)

3. Wang H. F., Fu Y. P., Huang M. (2015). A species based multiobjective evolutionary algorithm for multiobjective flow shop scheduling problem [C]//The 2015 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2015: 3243-3247. (EI index)

4. Jiang G. J., Fu Y. P. (2015). A two-phase method based on Markov and TOPSIS for evaluating project risk management strategies [C]//The 27th IEEE Chinese Control and Decision Conference (2015 CCDC), IEEE, 2015: 1994-1998. (EI index)

5. Wang N., Wang H. F.,Fu Y. P., Wamg D. W. (2015). A decomposition based memetic multi-objective algorithm for continuous multi-objective optimization problem[C]//The 27th IEEE Chinese. Control and Decision Conference (2015 CCDC), IEEE, 2015: 896-900. (EI index)

 

Project list:

国家自然科学基金青年科学基金项目,61703220,基于进化计算和最优计算量分配的随机多目标柔性作业车间调度问题研究,22万元,2018/01-2020/12,主持

中国博士后科学基金面上项目,2017M610407,随机环境下多目标柔性作业车间恶化调度模型与算法研究,8万元,2017/07-2018/12,主持

山东省自然科学基金,ZR2016PF02,面向动态多峰优化问题的进化计算方法及其应用研究,4万元,2016/11-2018/06,主持

青岛市博士后应用研究项目,2016026,考虑能耗的柔性作业车间随机型恶化调度模型与算法,5万元,2017/01-2018/07,主持

国家自然科学基金面上项目,61673228,供应链多层智能agent网络模型与竞争合作分析,2017/01-2020/12,61万元,参与(4/7)

山东省自然科学基金ZR2017PF005,基于强化学习的AGV系统路径规划和冲突解决方法,2017/07月-2018/12,4万元, 参与(2/6)

 

 

 

 

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