1990年9月至1995年7月 在清华大学自动化系过程控制专业学习，获学士学位
1995年9月至1999年10月 在清华大学自动化系控制理论与控制工程专业学习，获博士学位
1999年10月至2002年11月 清华大学自动化系过程控制工程研究所 讲师
2002年12月至2008年11月 清华大学自动化系过程控制工程研究所 副教授
2007年1月至2008年1月 美国密西根大学工业与运作工程系 访问学者
2008年12月至今 清华大学自动化系过程控制工程研究所 教授 博士生导师
[1] 中国仿真学会常务副理事长
[2] 中国仿真学会智能优化与调度专委会荣誉主任
[3] 中国人工智能学会自然计算与数字智能城市专委会副主任委员
[4] 中国运筹学会智能工业数据解析与优化专委会副理事长
[5] 中国自动化学会过程控制专委会常务委员
[6] 中国自动化学会控制理论与应用专委会委员
[7] 中国自动化学会能源互联网专委会常务理事
[8] 中国人工智能学会智能优化专委会常务理事
[9] 北京自动化学会常务理事
[10] Expert Systems with Applications主编
[11] Swarm and Evolutionary Computation主编
[12] International Journal of Automation and Control主编
[13] Complex System Modeling and Simulation执行主编
[14] IEEE Transactions on Evolutionary Computation副编辑
[15] Egyptian Informatics Journal副编辑
[16] Memetic Computing编委
[17] 《控制理论与应用》编委
[18] 《控制与决策》编委
[19] 《控制工程》编委
[20] 《工业工程》编委
[21] 《系统工程与电子技术》编委
[22] 《计算机集成制造系统》编委
智能优化理论、方法与应用
复杂生产过程建模、优化与调度
[1] 国家杰出青年科学基金(61525304)：智能优化调度理论与方法。(负责人) (2016~2020)
[2] 国家自然科学基金联合重点项目(U24A20273)：面向锡化工生产的全流程建模及学习型智能优化理论与方法。(课题负责人) (2025~2028)
[3] 国家自然科学基金项目(62273193)：面向车间能效调度的增强智能优化理论与方法。(负责人) (2023~2026)
[4] 国家自然科学基金项目(61873328)：分布式生产调度的协同群智能优化理论与方法。(负责人) (2019~2022)
[5] 国家自然科学基金项目(61174189)：复杂资源受限项目调度问题及其混合智能算法研究。(负责人) (2012~2015)
[6] 国家自然科学基金项目(70871065)：基于学习机制的群智能调度理论与方法研究。(负责人) (2009~2011)
[7] 国家自然科学基金项目(60774082)：复杂生产系统基于差分进化和量子进化的优化调度理论与方法。(负责人) (2008~2010)
[8] 国家自然科学基金项目(60374060)：复杂生产系统的智能仿真优化理论与方法研究。(负责人) (2004~2006)
[9] 国家自然科学基金项目(60204008)：复杂系统基于计算智能的混合优化理论与方法。(负责人) (2003~2005)
[10] 国家自然科学基金重点项目(60834004)：复杂芯片制造过程实时调度与优化控制理论和算法研究及应用。(课题负责人) (2009~2012)
[11] 教育部新世纪优秀人才支持计划(NCET-10-0505)。(负责人) (2010~2012)
[12] 高等学校博士学科点专项科研基金(20130002110057)：基于协同分布估计算法的分布式车间调度研究。(负责人) (2014~2016)
[13] 高等学校博士学科点专项科研基金(20100002110014)：基于新型混合群智能的资源约束项目调度研究。(负责人) (2011~2013)
[14] 北京市科技新星计划(2004A41)：混合智能优化调度理论与算法研究。(负责人) (2004~2007)
[15] 教育部留学回国启动基金：基于混合差分进化的优化调度研究。(负责人) (2009~2010)
[16] 国家重点研发计划项目(2023YFB3308000)：离散制造业智能工厂制造运营管理平台（MOM）。(课题负责人) (2023~2026)
[17] 国家重点研发计划(2016YFB0901900)：能源互联网的规划、运行与交易基础理论。(课题负责人) (2016~2020)
[18] 973计划课题(2013CB329503)：面向脑信息编解码的机器学习方法。(骨干) (2013~2017)
[19] 973计划课题(2009CB320602)：复杂生产制造全流程基于数据和知识的实时智能运行优化理论和方法研究。(骨干) (2011~2013)
[20] 973计划课题(2002CB312203)：复杂生产制造过程实时、智能控制与优化理论和方法研究。(骨干) (2002~2008)
[21] 973计划课题(G1998020310)：混杂电力系统。(骨干) (1998~2003)
[22] 863计划项目(2007AA04Z155)：流程工业企业生产过程的智能计划与动态优化调度技术。(课题负责人) (2008~2009)
[23] 国家科技重大专项(2011ZX02504-008)：集成电路生产线智能调度与质量优化控制技术研究。(骨干) (2011~2013)
[24] 美团合作项目：即时配送场景基于自适应学习机制的鲁棒优化调度。(负责人) (2021~2022)
[25] 美团合作项目：即时配送多目标鲁棒调度场景的优化问题研究。(负责人) (2019~2020)
[1] 2015年度国家杰出青年科学基金
[2] 2016年度中国自动化学会青年科学家奖
[3] 2009年度教育部新世纪优秀人才支持计划
[4] 2009年度清华大学学术新人奖
[5] 2004年度北京市科技新星
[6] 2010年度Scopus青年科学之星新人奖
[7] 2014年度国家自然科学奖二等奖
[8] 2022年度高等学校科学技术奖自然科学奖二等奖
[9] 2007年度高等学校科学技术奖自然科学奖二等奖
[10] 2003年度教育部提名国家自然科学一等奖
[11] 2022年度湖南省自然科学奖二等奖
[12] 2021年度湖北省自然科学奖二等奖
[13] 2017年度云南省自然科学奖三等奖
[14] 2008年度北京市科学技术奖三等奖
[15] 2024年度中国仿真学会创新技术奖一等奖
[16] 2022年度中国仿真学会自然科学奖一等奖
[17] 2021年度中国仿真学会自然科学奖一等奖
[18] 2019年度中国仿真学会创新技术奖一等奖
[19] 2011年度中国电子学会电子信息科学技术奖二等奖
[20] 2022年度《Tsinghua Science and Technology》 Best Paper Award
[21] 2022年度《Complex System Modeling and Simulation》 Best Paper Award
[22] 2017年度《控制与决策》优秀论文奖
[23] 2016年度《控制理论与应用》优秀论文奖
[24] 2014年度《自动化学报》优秀论文奖
[25] 领跑者5000, 中国精品科技期刊顶尖学术论文, 证书编号(13857): S001200812001
[26] 领跑者5000, 中国精品科技期刊顶尖学术论文, 证书编号(7597): S026201203014
[27] 领跑者5000, 中国精品科技期刊顶尖学术论文, 证书编号(10418): R060201402004
[28] 北京地区广受关注学术论文, 2020
[29] 2005-2010 Engineering Applications of Artificial Intelligence Top Cited Article Awarded by Elsevier
[30] IEEE TEVC Outstanding Associate Editor
[31] 《控制理论与应用》优秀编委奖
[32] 《控制与决策》优秀编委奖
[33] 2023’ INFORMS Franz Edelman Finalist Award
[34] 2018’ IEEE ICIC Outstanding Leadership Award
[35] ICIC’2018 Best Paper Award
[36] ICHSA’2015 Best Paper Award
[37] CPCC’2014 Best Poster Award
[38] IWACIII’2013 Best Paper Award
[39] ICIC’2011 Best Paper Award
[40] CCDC’2010 Finalist for Zhang Si-Ying Outstanding Youth Paper Award
[41] ICMLC’2002 Best Paper Award
[42] 清华大学优秀博士论文一等奖
[43] 清华大学优秀教材二等奖 (2004, 2008, 2012, 2016, 2020)
[44] 清华大学第19届良师益友 (2024)
[45] 清华大学第18届良师益友 (2022)
[46] 清华大学第17届良师益友 (2020)
[47] 清华大学第14届良师益友 (2014)
[48] 清华大学优秀班主任一等奖 (2004, 2005)
代表性论著：
[1] 王凌, 王圣尧, 方晨. 分布估计调度算法. 北京: 清华大学出版社, 2017
[2] 王凌, 钱斌. 混合差分进化与调度算法. 北京: 清华大学出版社, 2012.
[3] 王凌, 刘波. 微粒群优化与调度算法. 北京: 清华大学出版社, 2008.
[4] 王京春, 王凌, 金以慧 (译). 过程的动态特性与控制. 北京: 电子工业出版社, 2006.
[5] 王凌. 车间调度及其遗传算法. 北京: 清华大学出版社, 2003.
[6] 王凌. 智能优化算法及其应用. 北京: 清华大学出版社, 2001.
[7] Wu YT, Wang L, Chen JF. A branch-and-bound enhanced cooperative evolutionary algorithm for the hybrid seru system scheduling considering worker heterogeneity. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[8] Li R, Wang L, Gong WY, Ming F. An evolutionary multitasking memetic algorithm for multiobjective distributed heterogeneous welding flow shop scheduling. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[9] Qi S, Wang R, Zhang T, Huang WX, Qing F, Hu T, Wang L. A Thompson sampling-based sparse evolutionary operator for sparse large-scale multi-objective optimization. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[10] Zhang GH, Wang J, Dang QL, Wang L, Dong CX. Knowledge transfer driven distributed memetic architecture and algorithm for distributed differentiation flowshop integrated scheduling. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[11] Yu H, Gao KZ, Ma ZF, Wang L. Exact and deep Q-network assisted swarm intelligence methods for scheduling multi-objective heterogeneous unmanned surface vehicles. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[12] Wang YJ, Wang GG, Wang L. A tree-based multiobjective evolutionary algorithm for energy-efficient hybrid flow-shop scheduling. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[13] Wang JJ, Han HG, Wang L. A feedback learning-based memetic algorithm for energy-aware distributed flexible job-shop scheduling with transportation constraints. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[14] Pan ZX, Wang L, Wang JJ, Zhang QF. A bi-learning evolutionary algorithm for transportation-constrained and distributed energy-efficient flexible scheduling. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[15] Li GH, Wang ZK, Gao WF, Wang L. Decoupling constraint: Task clone-based multi-tasking optimization for constrained multi-objective optimization. IEEE Transactions on Evolutionary Computation. (Regular Paper).
[16] Zhao FQ, Yin FM, Wang L, Yu Y. A co-evolution algorithm with dueling reinforcement learning mechanism for the energy-aware distributed heterogeneous flexible flow-shop scheduling problem. IEEE Transactions on Systems, Man, and Cybernetics: Systems. (Regular Paper).
[17] Yao LZ, Zhang Y, Wang L, Li R, He TT. Natural gas pipeline leak detection based on dual feature drift in acoustic signals. IEEE Transactions on Industrial Informatics. (Regular Paper).
[18] Li BS, Gao WF, Xie J, Gong MG, Wang L, Li H. Federated multidiscriminators multigenerators for heterogeneous industrial IoT. IEEE Transactions on Industrial Informatics. (Regular Paper).
[19] Dang QL, Zhang GH, Wang L, Yang S, Zhan T. A generative adversarial networks model based evolutionary algorithm for multimodal multi-objective optimization. IEEE Transactions on Emerging Topics in Computational Intelligence. (Regular Paper).
[20] Ren YL, Tan M, Su YX, Wang R, Wang L. Two-stage adaptive robust charging scheduling of electric vehicle station based on hybrid demand response. IEEE Transactions on Transportation Electrification. (Regular Paper).
[21] Wang R, Liu W, Li KW, Zhang T, Wang L, Xu X. Solving orienteering problems by hybridizing evolutionary algorithm and deep reinforcement learning. IEEE Transactions on Artificial Intelligence. (Regular Paper).
[22] Li WH, Wang R, Heng Y, Zhang T, Wang L. Knowledge-guided evolutionary optimization for large-scale air defense resource allocation. IEEE Transactions on Artificial Intelligence. (Regular Paper).
[23] Wang JJ, Wang L, Han HG. A knowledge-driven cooperative coevolutionary algorithm for integrated distributed production and transportation scheduling problem. IEEE Transactions on Automation Science and Engineering. (Regular Paper).
[24] Pan ZX, Wang L, Wang JJ, Yu Y, Li R. Distributed energy-efficient flexible manufacturing with assembly and transportation: A knowledge based bi-hierarchical optimization approach. IEEE Transactions on Automation Science and Engineering. (Regular Paper).
[25] Liu H, Zhao FQ, Wang L, Xu TP, Dong CX. Evolutionary multitasking memetic algorithm for distributed hybrid flow-shop scheduling problem with deterioration effect. IEEE Transactions on Automation Science and Engineering. (Regular Paper).
[26] Zhao FQ, Song LS, Jiang T, Wang L, Dong CX. A policy-based meta-heuristic algorithm for energy-aware distributed no-wait flow-shop scheduling in heterogeneous factory systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2025, 55(1): 620-634. (Regular Paper).
[27] Chen JF, Wang L, Liang YL, Yu Y, Feng J, Zhao JX, Ding XT. Order dispatching via GNN-based optimization algorithm for on-demand food delivery. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(10): 13147-13162. (Regular Paper).
[28] Han YY, Wang YT, Pan QK, Wang L, Tasgetiren MF. Accelerated evaluation of blocking flowshop scheduling with total flow time criteria using a generalized critical machine-based approach. European Journal of Operational Research, 2024, 318(2): 424-441.
[29] Li R, Wang L, Gong WY, Chen JF, Pan ZX, Wu YT, Yu Y. Evolutionary computation and reinforcement learning integrated algorithm for distributed heterogeneous flowshop scheduling. Engineering Applications of Artificial Intelligence, 2024, 135: 108775.
[30] Wu YT, Wang L, Li R, Chen JF. A reinforcement learning-driven adaptive decomposition algorithm for multi-objective hybrid seru system scheduling considering worker transfer. Swarm and Evolutionary Computation, 2024, 88: 101602.
[31] Wu YT, Wang L, Chen JF, Zheng J, Pan ZX. A reinforcement learning driven two-stage evolutionary optimization for hybrid seru system scheduling with worker transfer. International Journal of Production Research, 2024, 62(11): 3952-3971.
[32] Li R, Gong WY, Wang L, Lu C, Pan ZX, Zhuang XY. Double DQN-based coevolution for green distributed heterogeneous hybrid flowshop scheduling with multiple priorities of jobs. IEEE Transactions on Automation Science and Engineering, 2024, 21(4): 6550-6562. (Regular Paper)
[33] Liu H, Wu GH, Ji B, Wang L. Multi-objective variable neighborhood descent for heterogeneous multi-UAV coordinated scheduling. IEEE Transactions on Aerospace and Electronic Systems, 2024, 60(2): 1808-1823. (Regular Paper).
[34] Chen Z, Laili YJ, Zhang L, Wang L. A Trans-Ptr-Nets based transfer optimization method for multi-objective flexible job shop scheduling in IIoT. IEEE Internet of Things Journal, 2024, 11(14): 25382-25393.
[35] Dang QL, Zhang GH, Wang L, Yang S, Zhan T. Hybrid IoT device selection with knowledge transfer for federated learning. IEEE Internet of Things Journal, 2024, 11(7): 12216-12227.
[36] Li BS, Gao WF, Xie J, Gong MG, Wang L, Li H. Prototype-based decentralized federated learning for the heterogeneous time-varying IoT systems. IEEE Internet of Things Journal, 2024, 11(4): 6916-6927.
[37] Pan ZX, Wang L, Dong CX, Chen JF. A knowledge-guided end-to-end optimization framework based on reinforcement learning for flow shop scheduling. IEEE Transactions on Industrial Informatics, 2024, 20(2): 1853-1861. (Regular Paper).
[38] Yao LZ, Zong X, Wang L, Li R, Yi J. Explicit evolutionary framework with multitasking feature fusion for optimizing operational parameters in aluminum electrolysis process. IEEE Transactions on Cybernetics, 2024, 54(12): 7527-7540. (Regular Paper).
[39] Zhang GH, Liu B, Wang L, Xing KY. Distributed heterogeneous co-evolutionary algorithm for scheduling a multi-stage fine-manufacturing system with setup constraints. IEEE Transactions on Cybernetics, 2024, 54(3): 1497-1510. (Regular Paper).
[40] Deng LB, Di YZ, Wang L. A reinforcement-learning-based three-dimensional estimation of distribution algorithm for fuzzy distributed hybrid flow-shop scheduling considering on-time-delivery. IEEE Transactions on Cybernetics, 2024, 54(2): 1024-1036. (Regular Paper).
[41] Li SJ, Gong WY, Wang L, Gu Q. Evolutionary multitasking via reinforcement learning. IEEE Transactions on Emerging Topics in Computational Intelligence, 2024, 8(1): 762-775. (Regular paper).
[42] Yao F, Chen YG, Wang L, Chang ZX, Huang PQ, Wang Y. A bilevel evolutionary algorithm for large-scale multiobjective task scheduling in multi-agile earth observation satellite systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 54(6): 3512-3524. (Regular Paper).
[43] Zhao FQ, Zhuang CX, Wang L, Dong CX. An iterative greedy algorithm with Q-learning mechanism for the multiobjective distributed no-idle permutation flowshop scheduling. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 54(5): 3207-3219. (Regular Paper).
[44] Li WH, Wang R, Huang SJ, Zhang T, Wang L. Large-scale binary matrix optimization for multimicrogrids network structure design. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 54(3): 1633-1644. (Regular Paper).
[45] Li R, Gong WY, Wang L, Lu C, Dong CX. Co-evolution with deep reinforcement learning for energy aware distributed heterogeneous flexible job shop scheduling. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2024, 54(1): 201-211. (Regular Paper).
[46] Yu KJ, Zhang DZ, Liang J, Qu BY, Liu MN, Chen K, Yue CT, Wang L. A framework based on historical evolution learning for dynamic multiobjective optimization. IEEE Transactions on Evolutionary Computation, 2024, 28(4): 1127-1140. (Regular Paper).
[47] Ming F, Gong WY, Wang L, Gao L. Constrained multi-objective optimization problems via multitasking and knowledge transfer. IEEE Transactions on Evolutionary Computation, 2024, 28(1): 77-89. (Regular Paper).
[48] Dong NJ, Zhang T, Wang R, Liao XK, Wang L. An evolutionary algorithm based on fully connected weight networks for mixed-variable multi-objective optimization. Information Sciences, 2024, 659: 120053.
[49] Su YX, Zhang T, Xu MY, Tan M, Zhang YZ, Wang R, Wang L. Rough knowledge enhanced dueling deep Q-network for household integrated demand response optimization. Sustainable Cities and Society, 2024, 101: 105065.
[50] Ming F, Gong WY, Wang L, Jin YC. Constrained multi-objective optimization with deep reinforcement learning assisted operator selection. IEEE/CAA Journal of Automatica Sinica, 2024, 11(4): 919-931.
[51] Chen JF, Wang L, Pan ZX, Wu YT, Zheng J, Ding XT. A matching algorithm with reinforcement learning and decoupling strategy for order dispatching in on-demand food delivery. Tsinghua Science and Technology, 2024, 29(2): 386-399.
[52] Wang X, Wang L, Dong CX, Ren H, Xing K. Reinforcement learning-based dynamic order recommendation for on-demand food delivery. Tsinghua Science and Technology, 2024, 29(2): 356-367.
[53] Tao M, Ren YL, Pan R, Wang L, Chen J. Fair and efficient electric vehicle charging scheduling optimization considering the maximum individual waiting time and operating cost. IEEE Transactions on Vehicular Technology, 2023, 72(8): 9808-9820. (Regular Paper).
[54] Li WH, Yao XY, Li KW, Wang R, Zhang T, Wang L. Coevolutionary framework for generalized multimodal multi-objective optimization. IEEE/CAA Journal of Automatica Sinica, 2023, 10(7): 1544-1556.
[55] Wu YT, Wang L, Zhuang XY, Wang JJ, Chen JF, Zheng J. A cooperative coevolutionary algorithm with problem-specific knowledge for energy-efficient scheduling in seru system. Knowledge-Based Systems, 2023, 274: 110663.
[56] Zhao FQ, Hu XT, Wang L, Xu TP, Zhu NN, Jonrinaldi. A reinforcement learning-driven brain storm optimisation algorithm for multi-objective energy-efficient distributed assembly no-wait flow shop scheduling problem. International Journal of Production Research, 2023, 61(9): 2853-2871.
[57] Zhao FQ, Zhang H, Wang L. A Pareto-based discrete Jaya algorithm for multiobjective carbon-efficient distributed blocking flow shop scheduling problem. IEEE Transactions on Industrial Informatics, 2023, 19(8): 8588-8599. (Regular Paper).
[58] Zhao FQ, Jiang T, Wang L. A reinforcement learning driven cooperative meta-heuristic algorithm for energy-efficient distributed no-wait flow-shop scheduling with sequence-dependent setup time. IEEE Transactions on Industrial Informatics, 2023, 19(7): 8427-8440. (Regular Paper).
[59] Zhao FQ, Xu ZS, Wang L, Zhu NN, Xu TP, Jonrinaldi. A population-based iterated greedy algorithm for distributed assembly no-wait flow-shop scheduling problem. IEEE Transactions on Industrial Informatics, 2023, 19(5): 6692-6705. (Regular Paper).
[60] Wang XH, Dai YP, Wang L, Jia ZY. Transient analysis and scheduling of Bernoulli serial lines with multi-type products and finite buffers. IEEE Transactions on Automation Science and Engineering, 2023, 20(4): 2367-2382. (Regular Paper).
[61] Zhao FQ, Wang ZY, Wang L. A reinforcement learning driven artificial bee colony algorithm for distributed heterogeneous no-wait flowshop scheduling problem with sequence-dependent setup times. IEEE Transactions on Automation Science and Engineering, 2023, 20(4): 2305-2320. (Regular Paper).
[62] Ma ZQ, Wu GH, Ji B, Wang L, Luo QZ, Chen XJ. A novel scattered storage policy considering commodity classification and correlation in robotic mobile fulfillment systems. IEEE Transactions on Automation Science and Engineering, 2023, 20(2): 1020-1033. (Regular Paper).
[63] Li R, Gong WY, Wang L, Lu C, Zhuang XY. Surprisingly popular-based adaptive memetic algorithm for energy-efficient distributed flexible job shop scheduling. IEEE Transactions on Cybernetics, 2023, 53(12): 8013-8023. (Regular Paper).
[64] Ming F, Gong WY, Wang L, Gao L. A constrained many-objective optimization evolutionary algorithm with enhanced mating and environmental selections. IEEE Transactions on Cybernetics, 2023, 53(8): 4934-4946. (Regular paper).
[65] Liang J, Qiao KJ, Yu KJ, Qu BY, Yue CT, Guo WF, Wang L. Utilizing the relationship between unconstrained and constrained Pareto fronts for constrained multi-objective optimization. IEEE Transactions on Cybernetics, 2023, 53(6): 3873-3886. (Regular paper).
[66] Zhao FQ, Di SL, Wang L. A hyper-heuristic with Q-learning for the multi-objective energy-efficient distributed blocking flow shop scheduling problem. IEEE Transactions on Cybernetics, 2023, 53(5): 3337-3350. (Regular Paper).
[67] Zhen HX, Gong WY, Wang L, Ming F, Liao ZW. Two-stage data-driven evolutionary optimization for high-dimensional expensive problems. IEEE Transactions on Cybernetics, 2023, 53(4): 2368-2379. (Regular paper).
[68] Ming F, Gong WY, Wang L, Gao L. A constraint-handling technique for decomposition-based constrained many-objective evolutionary algorithms. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2023, 53(12): 7783-7793. (Regular Paper).
[69] Zhao FQ, Zhu B, Wang L. An estimation of distribution algorithm-based hyper-heuristic for the distributed assembly mixed no-idle permutation flowshop scheduling problem. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2023, 53(9): 5626-5637. (Regular Paper).
[70] Zhao FQ*, Zhou G, Wang L. A cooperative scatter search with reinforcement learning mechanism for the distributed permutation flowshop scheduling problem with sequence-dependent setup times. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2023, 53(8): 4899-4911. (Regular Paper).
[71] Zheng J, Wang L, Wang L, Wang SY, Chen JF, Wang X. Solving stochastic online food delivery problem via iterated greedy algorithm with decomposition-based strategy. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(2): 957-969. (Regular Paper).
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开设课程
[1] 智能优化算法及其应用 (本科生课程)
[2] 自动控制原理 (本科生课程) [国家精品课程] [北京市精品课程]
[3] 生产调度及其智能优化 (研究生课程)
[4] 人工神经网络 (研究生课程)
[5] 文献检索与论文写作 (工程硕士课程)
博士后:
常志琦、陈靖方 [博新计划、水木学者]
博士生:
刘波、钱斌 [清华大学优秀博士论文]、方晨、许烨 [清华大学优秀博士论文, 清华大学优秀博士毕业生, 北京市优秀毕业生]、王圣尧 [清华大学优秀博士论文, 清华大学优秀博士毕业生, 北京市优秀毕业生]、施磊、郑晓龙 [清华大学优秀博士论文, 清华大学优秀博士毕业生]、张旭、沈婧楠、吴楚格、蒋恩达、陈靖方 [北京自动化学会优秀博士生]、王兴、王晶晶 [中国仿真学会优秀博士论文, 清华大学优秀博士论文, 清华大学优秀博士毕业生, 北京市优秀毕业生]、郑洁 [中国仿真学会优秀博士论文, 清华大学优秀博士论文, 清华大学优秀博士毕业生, 北京市优秀毕业生]、潘子肖 [清华大学优秀博士论文, 清华大学优秀博士毕业生, 北京市优秀毕业生, 北京自动化学会优秀博士生]、吴玉婷、堵君懿、李瑞 [北京自动化学会优秀博士生]、徐钰翔
硕士生:
张亮 [清华大学优秀硕士论文]、潘晖、李彬彬 [清华大学优秀硕士论文]、何锲 [清华大学优秀硕士论文]、黄付卓、李灵坡 [清华大学优秀硕士论文, 清华大学优秀硕士毕业生]、周刚 [清华大学优秀硕士论文, 清华大学优秀硕士毕业生, 北京市优秀毕业生]、张鹏、郑环宇 [清华大学优秀硕士论文, 清华大学优秀硕士毕业生]、邓瑾 [清华大学优秀硕士论文]、王晶晶 [清华大学优秀硕士论文]、陆佳文 [清华大学优秀硕士论文]、孙斌奇 [清华大学优秀硕士论文, 清华大学优秀硕士毕业生]
