人物經歷
教育背景
1990年9月至1995年7月 在清華大學自動化系過程控制專業學習，獲學士學位。
1995年9月至1999年10月 在清華大學自動化系控制理論與控制工程專業學習，獲博士學位。
工作履歷
1999年10月至2002年11月 清華大學自動化系過程控制工程研究所 講師。
2002年12月至2008年11月 清華大學自動化系過程控制工程研究所 副教授。
2007年1月至2008年1月 美國密西根大學工業與運作工程系 訪問學者。
2008年12月至今 清華大學自動化系過程控制工程研究所 教授 博士生導師。
主講課程
[1] 智慧型最佳化算法及其套用 (本科生課程)。
[2] 自動控制原理 (本科生課程) [北京市精品課程] [國家精品課程]。
[3] 生產調度及其智慧型最佳化 (研究生課程)。
[4] 人工神經網路 (研究生課程)。
[5] 文獻檢索與論文寫作 (工程碩士課程)。
研究方向
智慧型最佳化理論、方法與套用。
複雜生產過程建模、最佳化與調度。
主要貢獻
學術兼職
1. 中國自動化學會過程控制專委會委員、控制理論專委會委員。
2. 中國運籌學會排序專委會常務理事。
3. 中國運籌學會智慧型工業數據解析與最佳化專委會常務理事。
4. 中國人工智慧學會智慧型最佳化專委會常務理事。
5. 北京市自動化學會常務理事。
6.中國自動化學會能源網際網路專委會常務理事。
7. International J of Automation and Control (InderScience) 編委。
8. International J of Applied and Computational Mathematics (Spriner)副編輯。
9. Memetic Computing (Springer)編委。
10.Swarm and Evolutionary Computation (Elsevier) 副編輯。
11. 《控制與決策》 編委。
12. 《控制工程》 編委。
研究概況
[1] 國家傑出青年科學基金(61525304)：智慧型最佳化調度理論與方法。(負責人) (2016.1~2020.12)
[2] 國家自然科學基金項目(61174189)：複雜資源受限項目調度問題及其混合智慧型算法研究(負責人) (2012.1~2015.12)
[3] 國家自然科學基金項目(70871065)：基於學習機制的群智慧型調度理論與方法研究。(負責人) (2009.1~2011.12)
[4] 國家自然科學基金項目(60774082)：複雜生產系統基於差分進化和量子進化的最佳化調度理論與方法。(負責人) (2008.1~2010.12)
[5] 國家自然科學基金項目(60374060)：複雜生產系統的智慧型仿真最佳化理論與方法研究。(負責人) (2004.1~2006.12)
[6] 國家自然科學基金項目(60204008)：複雜系統基於計算智慧型的混合最佳化理論與方法。(負責人) (2003.1~2005.12)
[7] 國家自然科學基金重點項目(60834004)：複雜晶片製造過程實時調度與最佳化控制理論和算法研究及套用。(骨幹) (2009.1~2012.12)
[8] 教育部新世紀優秀人才支持計畫(NCET-10-0505)。(負責人) (2010.1~2012.12)
[9] 高等學校博士學科點專項科研基金(20130002110057)：基於協同分布估計算法的分散式車間調度研究。(負責人) (2014.1~2016.12)
[10] 高等學校博士學科點專項科研基金(20100002110014)：基於新型混合群智慧型的資源約束項目調度研究。(負責人) (2011.1~2013.12)
[11] 北京市科技新星計畫(2004A41)：混合智慧型最佳化調度理論與算法研究。(負責人) (2004.7~2007.7)
[12] 教育部留學回國啟動基金：基於混合差分進化的最佳化調度研究。(負責人) (2009.1~2010.12)
[13] 973計畫課題(2013CB329503)：面向腦信息編解碼的機器學習方法。(骨幹) (2013.01~2017.12)
[14] 國家重點研發計畫(2016YFB0901900)：能源網際網路的規劃、運行與交易基礎理論。(課題一負責人) (2016.7~2020.6)
學術成果
[1] 王凌, 錢斌. 混合差分進化與調度算法. 北京: 清華大學出版社, 2012.
[2] 王凌, 劉波. 微粒群最佳化與調度算法. 北京: 清華大學出版社, 2008.
[3] 王京春, 王凌, 金以慧 (譯). 過程的動態特性與控制. 北京: 電子工業出版社, 2006.
[4] 王凌. 車間調度及其遺傳算法. 北京: 清華大學&Springer出版社, 2003.
[5] 王凌. 智慧型最佳化算法及其套用. 北京: 清華大學&Springer出版社, 2001.
[6] Wang SY, Wang L. An estimation of distribution algorithm-based memetic algorithm for the distributed assembly permutation flow-shop scheduling problem. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2016, 46(1): 139-149. (Regular Paper).
[7] Shi L, Jiang YH, Wang L, Huang DX. Efficient Lagrangian decomposition approach for solving refinery production scheduling problems involving operational transitions of mode switching. Industrial & Engineering Chemistry Research, 2015, 54(25): 6508-6526.
[8] Zheng HY, Wang L. Reduction of carbon emissions and project makespan by a Pareto-based estimation of distribution algorithm. International Journal of Production Economics, 2015, 164: 421-432.
[9] Wang SY, Wang L, Liu M, Xu Y. An order-based estimation of distribution algorithm for stochastic hybrid flow-shop scheduling problem. International Journal of Computer Integrated Manufacturing, 2015, 28(3): 307-320.
[10] Zheng HY, Wang L. An effective teaching-learning-based optimization algorithm for RCPSP with ordinal interval numbers. International Journal of Production Research, 2015, 53(6): 1777-1790.
[11] Zhang X, Chen MY, Wang L, Peng ZH, Zhou DH. Connection-graph-based event-triggered output consensus in multi-agent systems with time-varying couplings. IET Control Theory and Applications, 2015, 9(1): 1-9.
[12] Shi L, Jiang YH, Wang L, Huang DX. Refinery production scheduling involving operational transitions of mode switching under predictive control system. Industrial & Engineering Chemistry Research, 2014, 53(19): 8155-8170.
[13] Pan QK, Wang L, Li JQ, Duan JH. A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimization. OMEGA-International Journal of Management Science, 2014, 45: 42-56.
[14] Wang L, Fang C, Mu CD, Liu M. A Pareto-archived estimation-of-distribution algorithm for multi-objective resource-constrained project scheduling problem. IEEE Transactions on Engineering Management, 2013, 60(3): 617-626. (Regular Paper).
[15] Wang SY, Wang L, Liu M, Xu Y. An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem. International Journal of Production Economics, 2013, 145(1): 387-396.
[16] Pan QK, Wang L, Sang HY, Li JQ, Liu M. A high performing memetic algorithm for the flowshop scheduling problem with blocking. IEEE Transactions on Automation Science and Engineering, 2013, 10(3): 741-756. (Regular Paper).
[17] Wang L, Zhou G, Xu Y, Liu M. A hybrid artificial bee colony algorithm for the fuzzy flexible job-shop scheduling problem. International Journal of Production Research, 2013, 51(12): 3593-3608.
[18] Wang L, Wang SY, Liu M. A Pareto-based estimation of distribution algorithm for the multi-objective flexible job-shop scheduling problem. International Journal of Production Research, 2013, 51(12): 3574-3592.
[19] Wang L, Zheng XL, Wang SY. A novel binary fruit fly optimization algorithm for solving the multidimensional knapsack problem. Knowledge-Based Systems, 2013, 48: 17-23.
[20] Pan QK, Wang L, Mao K, Zhao JH, Zhang M. An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process. IEEE Transactions on Automation Science and Engineering, 2013, 10(2): 307-322. (Regular Paper).
[21] Wang L, Wang SY, Xu Y, Zhou G, Liu M. A bi-population based estimation of distribution algorithm for the flexible job-shop scheduling problem. Computers & Industrial Engineering, 2012, 62(4): 917-926.
[22] Fang C, Wang L. An effective shuffled frog-leaping algorithm for resource-constrained project scheduling problem. Computers & Operations Research, 2012, 39(5): 890-901.
[23] Pan QK, Wang L. Effective heuristics for the blocking flowshop scheduling problem with makespan minimization. OMEGA-International Journal of Management Science, 2012, 40(2): 218-229.
[24] Wang L, Fang C. An effective estimation of distribution algorithm for the multi-mode resource-constrained project scheduling problem. Computers & Operations Research, 2012, 39(2): 449-460.
[25] Wang L, Li LP. Fixed-structure H∞ controller synthesis based on differential evolution with level comparison. IEEE Transactions on Evolutionary Computation, 2011, 15(1): 120-129. (Regular paper).
[26] Wang L, Fang C. An effective shuffled frog-leaping algorithm for multi-mode resource-constrained project scheduling problem. Information Sciences, 2011, 181(20): 4804-4822.
[27] Liu B, Wang L, Liu Y, Wang SY. A unified framework for population-based metaheuristics. Annals of Operations Research, 2011, 186(1): 231-262.
[28] Wang L, Pan QK, Tasgetiren MF. A hybrid harmony search algorithm for the blocking permutation flow shop scheduling problem. Computers & Industrial Engineering, 2011, 61(1): 76-83.
[29] Pan QK, Wang L, Gao L, Li WD. An effective hybrid discrete differential evolution algorithm for the flow shop scheduling with intermediate buffers. Information Sciences, 2011, 181(3): 668-685.
[30] Pan QK, Suganthan PN, Wang L, Gao L, Mallipeddi R. A differential evolution algorithm with self-adapting strategy and control parameters. Computers & Operations Research, 2011, 38(1): 394-408.
[31] Wang L, Li LP. An effective differential evolution with level comparison for constrained engineering design. Structural and Multidisciplinary Optimization, 2010, 41(6): 947-963.
[32] Liu B, Wang L, Liu Y, Qian B, Jin YH. An effective hybrid particle swarm optimization for batch scheduling of polypropylene processes. Computers & Chemical Engineering, 2010, 34(4): 518-528.
[33] Wang L, Huang FZ. Parameter analysis based on stochastic model for differential evolution algorithm. Applied Mathematics and Computation, 2010, 217(7): 3263-3273.
[34] Wang L, Pan QK, Suganthan PN, Wang WH, Wang YM. A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems. Computers & Operations Research, 2010, 37(3): 509-520.
[35] Qian B, Wang L, Hu R, Huang DX, Wang X. A DE-based approach to no-wait flow-shop scheduling. Computers & Industrial Engineering, 2009, 57(3): 787-805.
[36] Qian B, Wang L, Huang DX, Wang X. Multi-objective no-wait flow-shop scheduling with a memetic algorithm based on differential evolution. Soft Computing, 2009, 13(8-9): 847-869.
[37] Pan QK, Wang L, Qian B. A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems. Computers & Operations Research, 2009, 36(8): 2498-2511.
[38] Qian B, Wang L, Huang DX, Wang X. An effective hybrid DE-based algorithm for flow shop scheduling with limited buffers. International Journal of Production Research, 2009, 47(1): 1-24.
[39] Qian B, Wang L, Huang DX, Wang WL, Wang X. An effective hybrid DE-based algorithm for multi-objective flow shop scheduling with limited buffers. Computers & Operations Research, 2009, 36(1): 209-233.
[40] Li BB, Wang L, Liu B. An effective PSO-based hybrid algorithm for multi-objective permutation flow shop scheduling. IEEE Transactions on Systems, Man and Cybernetics-Part A: Systems and Humans, 2008, 38(4): 818-831. (Regular paper).
[41] Liu B, Wang L, Jin YH. An effective hybrid PSO-based algorithm for flow shop scheduling with limited buffers. Computers & Operations Research, 2008, 35(9): 2791-2806.
[42] Li BB, Wang L. A hybrid quantum-inspired genetic algorithm for multi-objective flow shop scheduling. IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 2007, 37(3): 576-591. (Regular paper).
[43] Liu B, Wang L, Jin YH. An effective PSO-based memetic algorithm for flow shop scheduling. IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 2007, 37(1): 18-27. (Regular paper). (ESI)
[44] He Q, Wang L. An effective co-evolutionary particle swarm optimization for constrained engineering design problems. Engineering Applications of Artificial Intelligence, 2007, 20(1): 89-99. (ESI)
[45] Wang L, Zhang L, Zheng DZ. An effective hybrid genetic algorithm for flow shop scheduling with limited buffers. Computers & Operations Research, 2006, 33(10): 2960-2971.
[46] Liu B, Wang L, Jin YH, Tang F, Huang DX. Improved particle swarm optimization combined with chaos. Chaos, Solitons and Fractals, 2005, 25(5): 1261-1271. (ESI)
[47] Wang L, Zheng DZ. An effective hybrid heuristic for flow shop scheduling. International Journal of Advanced Manufacturing Technology, 2003, 21(1): 38-44.
[48] Jiang YH, Wang L, Jin YH. Bottleneck analysis for network flow model. Advances in Engineering Software, 2003, 34(10): 641-651.
[49] Zhou T, Wang L, Sun ZS. Closed-loop model set validation under a stochastic framework. Automatica, 2002, 38(9): 1449-1461.
[50] Wang L, Zheng DZ. An effective hybrid optimization strategy for job-shop scheduling problems. Computers & Operations Research, 2001, 28(6): 585-596.
獎勵與榮譽
[1] 2015年度國家傑出青年科學基金。
[2] 2009年度教育部新世紀優秀人才支持計畫。
[3] 2009年度清華大學學術新人獎。
[4] 2004年度北京市科技新星。
[5] 2010年度Scopus青年科學之星新人獎。
[6] 2014年度國家自然科學獎二等獎。
[7] 2011年度中國電子學會電子信息科學技術獎二等獎。
[8] 2008年度北京市科學技術獎三等獎。
[9] 2007年度高等學校科學技術獎自然科學獎二等獎。
[10] 2003年度教育部提名國家自然科學一等獎。
[11] 2014年度自動化學報優秀論文獎、2016年度控制理論與套用優秀論文獎。
[12] 2005-2010 Engineering Applications of Artificial Intelligence Top Cited Article Awarded by Elsevier。
[13] 國際和聲搜尋算法會議最佳論文獎, ICHSA’2015。
[14] 中國過程控制年會Poster論文獎, CPCC’2014。
[15] 高等計算智慧型與智慧型信息國際會議最佳論文獎, IWACIII’2013。
[16] IEEE國際智慧型計算會議最佳論文獎, ICIC’2011。
[17] Finalist for Zhang Si-Ying Outstanding Youth Paper Award, CCDC’2010。
[18] IET諮詢與控制技術國際會議優秀論文, ICT’2006。
[19] 中國控制與決策年會優秀論文, CCDC’2004。
[20] IEEE機器學習和控制論國際會議優秀論文獎, ICMLC’2002。
[21] 清華大學優秀博士論文一等獎。
[22] 清華大學優秀教材二等獎 (2004, 2008, 2012)。
[23] 清華大學第14屆良師益友 (2014)。
[24] 清華大學優秀班主任一等獎 (2004, 2005)。
