个人简介
华中科技大学机械学院教授、博士生导师，国家级高层次青年人才、湖北省杰青，获全国优秀博士学位论文提名奖。现从事智能制造系统、车间调度、智能优化与机器学习等方面的科研工作。主持国家自然科学基金项目3项、国家重点研发计划课题1项、国家科技创新2030“新一代人工智能”重大项目子课题1项等科研项目10余项；参与973课题、国家科技支撑计划、国家自然科学基金重点项目及企业委托课题等。出版专著4部，发表SCI论文100余篇，Web of Science他引3400余次，授权发明专利24项。担任IET Collaborative Intelligent Manufacturing（EI收录）Associate Editor、Sensors（SCI收录） Editorial Board Member、《工业工程》编委。获教育部自然科学一等奖1项、海洋科学技术二等奖1项、中国运筹学会“青年科技奖”提名奖、中国仿真学会智能仿真优化与调度专委会“青年科学家奖”、IFAC会刊EAAI Paper Prize Award (Practice、通讯作者)。
开设课程
《运筹学》
《调度：原理、算法及系统》
承担的科研项目：
1、2019.12～2022.11，国家重点研发计划课题“基于数字孪生的电子产品生产调度与物料传输协同优化及决策技术”（2019YFB1704603），305万。
2、2019.12～2022.12，国家科技创新2030—“新一代人工智能”重大项目子课题“基于边缘计算的增强智能分析与自适应协同优化方法”， 52.8万。
3、2018.1～2021.12，国家自然科学基金面上项目“数据-模型混合驱动的车间动态调度理论与方法”（51775216），63万。
代表性著作：
1、Li X Y, Gao L. Effective Methods for Integrated Process Planning and Scheduling. Springer, 2020. ISBN 978-3-662-55303-9. https://doi.org/10.1007/978-3-662-55305-3
2、高亮, 李新宇, 文龙等. 工艺规划与车间调度的智能算法. 清华大学出版社, 35万字, 2019. ISBN 978-7-302-51964-5
3、潘全科, 高亮, 李新宇. 流水车间调度及其优化算法. 华中科技大学出版社, 43万字, 2013. ISBN 978-7-5609-8423-0
4、高亮, 张春江, 李新宇等. 类电磁机制算法的研究与应用. 华中科技大学出版社, 33.2万字, 2017. ISBN 978-7-5680-3436-4
近期论文
查看导师新发文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
1. Li X Y, Gao L, Pan Q K, Wan L, Chao K M. An effective hybrid genetic algorithm and variable neighborhood search for integrated process planning and scheduling in a packaging machine workshop. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2019, 49(10): 1933-1944.
2. Li X Y, Lu C, Gao L, Xiao S Q, Wen L. An Effective Multi-Objective Algorithm for Energy Efficient Scheduling in a Real-Life Welding Shop. IEEE Transactions on Industrial Informatics, 2018, 14(12): 5400-5409.
3. Li X Y, Gao L, Wang W W, Wang C Y, Wen L. Particle swarm optimization hybridized with genetic algorithm for uncertain integrated process planning and scheduling with interval processing time. Computers & Industrial Engineering, 2019, 135: 1036-1046.
4. Li X Y, Xiao S Q, Wang C Y, Yi J. Mathematical Modeling and a Discrete Artificial Bee Colony Algorithm for the Welding Shop Scheduling Problem. Memetic Computing, 2019, 11: 371-389.
5. Li X Y, Gao L. An Effective Hybrid Genetic Algorithm and Tabu Search for Flexible Job Shop Scheduling Problem. International Journal of Production Economics, 2016, 174: 93-110.
6. Liu Q H, Li X Y*, Gao L. A Novel MILP Model Based on the Topology of a Network Graph for Process Planning in an Intelligent Manufacturing System. Engineering, 2021.
7. Liu Q H, Li X Y*, Gao L, Li Y L. A Modified Genetic Algorithm with New Encoding and Decoding Method for Integrated Process Planning and Scheduling Problem. IEEE Transactions on Cybernetics, 2020.
8. Wang K P, Gao L, Li X Y*, Li P G. Energy-Efficient Robotic Parallel Disassembly Sequence Planning for End-of-Life Products. IEEE Transactions on Automation Science and Engineering, 2021.
9. Wang Y C, Gao L, Li X Y*, Gao Y P, Xie X T. A New Graph-based Method for Class Imbalance in Surface Defect Recognition. IEEE Transactions on Instrumental Measurement, 2021, 70: 5007816.
10. Wen L, Gao L, Li X Y*, Zeng B. Convolutional Neural Network with Automatic Learning Rate Scheduler for Fault Classification. IEEE Transactions on Instrumental Measurement, 2021, 70: 3509912.
11. Gao Y P, Gao L, Li X Y*. A Generative Adversarial Network-based Deep Learning Method for Low-quality Defect Image Reconstruction and Recognition. IEEE Transactions on Industrial Informatics, 2021, 17(5): 3231-3240.
12. Gao Y P, Gao L, Li X Y*, Wang X. A Multi-Level Information Fusion-based Deep Leaning Method for Vision-based Defect Recognition. IEEE Transactions on Instrumentation & Measurement, 2020, 69(7): 3980-3991.
13. Lu C, Gao L, Li X Y*, Xiao S Q. A hybrid multi-objective grey wolf optimizer for dynamic scheduling in a real-world welding industry. Engineering Applications of Artificial Intelligence, 2017, 57: 61-79.
14. Wen L, Bo N, Ye X C, Li X Y*. A Novel Auto-LSTM based State of Health Estimation Method for Lithium-ion Batteries. Journal of Electrochemical Energy Conversion and Storage, Transactions of the ASME, 2021, 18: 030902.
15. Zhou Y Z, Yi W C, Gao L, Li X Y*. Adaptive differential evolution with sorting crossover rate for continuous optimization problems. IEEE Transactions on Cybernetics, 2017, 47(9): 2742-2753.
学术兼职
担任中国机械工程学会工业大数据与智能系统分会总干事、湖北省机械工程学会工业工程专业委员会副理事长、湖北省运筹学会理事/副秘书长、中国仿真学会智能仿真优化与调度专业委员会副秘书长/常务委员、航天智能制造技术创新联盟智能系统与工业互联专业委员会委员等。
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