MBA硕士生导师-李岸达

发表时间:2024-03-12

一、个人信息:

基本信息:李岸达,男,博士,管理学院副教授,人力资源管理系主任,新西兰惠灵顿维多利亚大学访问学者(2018.7-2018.12),天津市工业工程学会理事,IEEE会员,中国优选法统筹法与经济数学研究会会员。

教育背景:

1.2013-9至2016-6,天津大学,管理科学与工程,博士

2.2011-9至2013-6,天津大学,工业工程,硕士

3. 2007-9至2011-6,北京邮电大学,物流工程,本科

获得荣誉:

1.2018年度天津市“131”创新型人才培养工程第三层次人选

2.入选天津市高校“青年后备人才支持计划”

3.天津市教学团队成员

4.2019年天津商业大学优秀教师

Email:adli@tjcu.edu.cn

个人主页:https://andali89.github.io/homepage/

二、学科领域:质量管理与质量工程,计算智能,机器学习,人力资源管理。

三、代表性论文:

[1]Li, A.-D.*, He, Z., Wang, Q., & Zhang, Y.* (2019). Key quality characteristics selection for imbalanced production data using a two-phase bi-objective feature selection method. European Journal of Operational Research, 274(3), 978–989. (ABS4, FMS A类, SCI)

[2]Li, A.-D.*, Xue, B., & Zhang, M. (2023). Multi-objective particle swarm optimization for key quality feature selection in complex manufacturing processes. Information Sciences, 641, 119062. (FMS B类, CCF B类, SCI)

[3]Li, A.-D.*, Xue, B., & Zhang, M. (2020). Multi-objective feature selection using hybridization of a genetic algorithm and direct multisearch for key quality characteristic selection. Information Sciences, 523, 245–265. (FMS B类, CCF B类, SCI)

[4]Li, A.-D., He, Z., & Zhang, Y.* (2022). Robust multi-response optimization considering location effect, dispersion effect, and model uncertainty using hybridization of NSGA-II and direct multi-search. Computers & Industrial Engineering, 169, 108247. (ABS2, FMS B类, SCI)

[5]Li, A.-D.*, Xue, B., & Zhang, M. (2021). Improved binary particle swarm optimization for feature selection with new initialization and search space reduction strategies. Applied Soft Computing, 106, 107302. (SCI)

[6]Li, A.-D.*, & He, Z. (2020). Multiobjective feature selection for key quality characteristic identification in production processes using a nondominated-sorting-based whale optimization algorithm. Computers & Industrial Engineering, 149, 106852. (ABS2, FMS B类, SCI)

[7]Li, A.-D., He, Z.*, & Zhang, Y. (2016). Bi-objective variable selection for key quality characteristics selection based on a modified NSGA-II and the ideal point method. Computers in Industry, 82, 95–103. (ABS3, SCI)

[8] Liu, X., & Li, A.-D.* (2023). An improved probability-based discrete particle swarm optimization algorithm for solving the product portfolio planning problem. Soft Computing. doi:10.1007/s00500-023-08530-0 (SCI)

[9] He Z., Hu H., Zhang M., Zhang Y., &Li A.-D.* (2022). A decomposition-based multi-objective particle swarm optimization algorithm with a local search strategy for key quality characteristic identification in production processes. Computers & Industrial Engineering.https://doi.org/10.1016/j.cie.2022.108617(ABS2, FMS B类, SCI)

[10] Zhang, Y., Shang, Y., Hu, X., &Li, A.-D.* (2022). An improved exponential EWMA chart for monitoring time between events. Quality and Reliability Engineering International.doi:10.1002/qre.3102(SCI)

[11]李岸达,何桢, &何曙光(2016).基于NSGA-Ⅱ的非平衡制造数据关键质量特性识别.系统工程理论与实践, 36(6): 1472-1479. (FMS中文T1级)

四、科研项目:

[1] 基于机器学习的复杂制造过程关键质量因素识别与在线质量预测研究,国家自然科学基金青年科学基金项目 (72101182), 2022-01至2024-12,在研,主持

[2]多阶段复杂产品制造过程关键质量特性识别研究,教育部人文社会科学研究青年基金项目(19YJC630071), 2019-01至2022-12,结题,主持

[3]复杂制造过程中轮廓数据监控方法研究,国家自然科学基金青年科学基金项目 (71401123), 2015-01至2017-12,结题,参与

[4]基于信息熵的事件动态控制图研究,教育部人文社会科学研究青年基金项目(19YJC630221), 2019-01至2021-12,在研,第一参与人

[5]基于非平衡数据的复杂产品关键质量特性识别研究,天津市高等学校人文社会科学研究项目, 2017-01至2019-12,结题,主持

五、团队成员:张阳,刘晓杰,刘超超,李娟,刘盟,陈芳