职称：讲师

办公室：新行政中心240
研究方向：计算智能、群体智能、人工智能
论文被引：Google学术被引436次，H指数10
微信号：wenji_2020
Email:liwj@stu.edu.cn
教育背景
1、2014.9-2020.12汕头大学，结构工程，工学博士
2、2010.9-2013.6汕头大学，机械设计及理论，工学硕士
3、2006.9-2010.6武汉工程大学，材料工程，工学学士
工作背景
1、2020.12-至今汕头大学，工学院电子信息工程系，讲师
2、2013.7-2014.7汕头大学，工学院电子信息工程系，科研助理
科研项目
1、2020.5-2022.5，中央军委科技委重点项目，共识主动性群体协同机理与环境感知技术研究，经费：140万元，在研，参加
2、2018.11-2020.12，中央军委科技委基础研究项目，群体聚合形态动态转换机理研究，经费：60万元，在研，参加
3、2019.1-2021.12，广东省国际科技合作基地项目，融合多目标进化计算和深度神经网络的机器人设计自动化平台，项目编号：2019A，100万元，在研，参加
科研论文
1、期刊论文
[1] Z Fan,W Li, X Cai, H Li, C Wei, Q Zhang, K Deb, & E Goodman. Difficulty adjustable and scalable constrained multiobjective test problem toolkit.Evolutionary Computation, 2020, 28(3):339-378.（SCI计算科学理论与方法1区，IF=3.933，除导师外第一作者）
[2] Z Fan,W Li, X Cai, H Li, C Wei, Q Zhang, K Deb, & E Goodman. Push and pull search for solving constrained multi-objective optimization problems.Swarm and Evolutionary Computation, 2019, 44:665-679.（SCI人工智能1区Top期刊，IF=6.912，除导师外第一作者）
[3] Z Fan,W Li, X Cai, H Huang, Y Fang, Y You, J Mo, C Wei, & E Goodman. An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions.Soft Computing, 2019, 23:12491-12510.（SCI人工智能2区，IF=3.05，除导师外第一作者）
[4] Q Wang, H Qiao,W Li?, Y You, Z Fan, & N Tiwari. Parameter Optimization of Absorber for Wind-induced Vibration Mitigation of a Tall Building.Wind and Structures, 2020, 31(3):241-253.（SCI土木工程2区，IF=1.922，通讯作者）
[5] Z Fan, Y Fang,W Li, X Cai, C Wei, & E Goodman. MOEA/D with angle- based constrained dominance principle for constrained multi-objective optimization problems.Applied Soft Computing, 2019, 74:621-633.（SCI人工智能1区Top期刊，IF=5.472，除导师外共同第一作者）
[6] Z Fan, Z Wang,W Li, Y Yuan, Y You, Z Yang, F Sun, & J Ruan. Push and pull search embedded in an M2M framework for solving constrained multi- objective optimization problems.Swarm and Evolutionary Computation, 2020, 54:100651.（SCI人工智能1区Top期刊，IF=6.912）
[7] Z Fan, Y You, X Cai, H Zheng, G Zhu,W Li, A Garg, K Deb, & E Goodman. Analysis and multi-objective optimization of a kind of teaching manipulator.Swarm and Evolutionary Computation, 2019, 50:100554.（SCI人工智能1区Top期刊，IF=6.912）
[8]范衠,朱贵杰,李文姬,游煜根,李晓明,林培涵,辛斌.进化计算在复杂机电系统设计自动化中的应用综述.自动化学报, 2020. DOI: 10.16383/j.aas.c190767
2、会议论文
[1] Fan Z, Yang Z, Tang Y,Li W, Xu B, Wang Z, Long Z, and Zhu G.An Improved Epsilon Method with M2M for Solving Imbalanced CMOPs with Simultaneous Convergence-hard and Diversity-hard Constraints.2021 11th International Conference on Evolutionary Multi-Criterion Optimization (EMO). Springer, 2021
[2] Fan Z, Ruan J,Li W, You Y, Cai X, Xu Z, Yang Z, Sun F, Wang Z, Yuan Y,et al.A Learning Guided Parameter Setting for Constrained Multi-Objective Optimization.2019 1st International Conference on Industrial Artificial Intelligence (IAI). IEEE, 2019 1–6
[3] Fan Z, Fang Y,Li W, Yuan Y, Wang Z, and Bian X. LSHADE44 with an ImprovedεConstraint-Handling Method for Solving Constrained Single-Objective Optimization Problems.2018 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2018 1–8
[4] Fan Z, Wang Z, Fang Y,Li W, Yuan Y, and Bian X. Adaptive Recombination Operator Selection in Push and Pull Search for Solving Constrained Single Objective Optimization Problems.International Conference on Bio-Inspired Computing: Theories and Applications. Springer, 2018 355–367
[5] Mo J, Fan Z,Li W, Fang Y, You Y, and Cai X. Multi-factorial evolutionary algorithm based on M2M decomposition.Asia-Pacific Conference on Simulated Evolution and Learning. Springer, 2017 134–144
[6] Fan Z,Li W, Cai X, Fang Y, Lu J, and Wei C. A comparative study of constrained multi-objective evolutionary algorithms on constrained multi-objective optimization problems.2017 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2017 209–216
[7] Fan Z,Li W, Cai X, Li H, Huang H, Cai Z, and Wei C. An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems.Computational Intelligence (SSCI), 2016 IEEE Symposium Series on. IEEE, 2016 1–8
[8] Fan Z, Hu K, Li F, Rong Y,Li W, and Lin H. Multi-objective evolutionary algorithms embedded with machine learning—A survey.2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2016 1262–1266
[9] Xiao Y, Fan Z,Li W, Chen S, Zhao L, and Xie H. A Manipulator Design Optimization Based on Constrained Multi-objective Evolutionary Algorithms.Industrial Informatics-Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII), 2016 International Conference on. IEEE, 2016 199–205
[10] Fan Z,Li W, Cai X, Huang H, Xie S, and Goodman E. An opposition-based repair operator for multi-objective evolutionary algorithm in constrained optimization problems.2015 11th International Conference on Natural Computation (ICNC). IEEE, 2015 330–336
[11] Fan Z,Li W, Cai X, Li H, Hu K, and Yin H. Difficulty controllable and scalable constrained multi-objective test problems.2015 International Conference on Industrial Informatics-Computing Technology, Intelligent Technology, Industrial Information Integration. IEEE, 2015 76–83
[12] Fan Z,Li W, Cai X, Li H, Hu K, and Yin H. An Improved Ideal Point Setting in Multiobjective Evolutionary Algorithm Based on Decomposition.2015 International Conference on Industrial Informatics-Computing Technology, Intelligent Technology, Industrial Information Integration. IEEE, 2015 63–70
[13]Li W, Fan Z, Cai X, Lin H, Xie S, and Wang S. Design optimization of MEMS using constrained multi-objective evolutionary algorithm.Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation.ACM, 2014 1175–1180
[14] Fan Z, Cai X,Li W, Lin H, Xie S, and Wang S. Evolutionary synthesis of dynamical systems: the past, current, and future.Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation.ACM, 2014 1169–1174
[15] Lin H, Fan Z, Cai X,Li W, Wang S, Li J, and Zhang C. Hybridizing infeasibility driven and constrained-domination principle with MOEA/D for constrained multi-objective evolutionary optimization.International Conference on Technologies and Applications of Artificial Intelligence. Springer, 2014 249–261
科研成果
1、软件著作权：
[1]群体机器人聚合形态自动化设计平台V1.0，登记号：2020SR**
[2]机器人设计自动化平台V1.0，登记号：2018SR212300
2、授权专利：
[1]范衠;游煜根;陈文钊;郑浩东;李文姬;朱贵杰;一种自主移动机器人平台控制装置, 2017-04-19,中国, ZL3.4.
[2]范衠;游煜根;陈文钊;郑浩东;李文姬;朱贵杰;一种自主移动机器人平台用控制系统、方法及装置, 2019-06-07,中国, ZL8.1