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王凌，博士，教授，博士生导师

清华大学自动化系，北京 100084

电话：86-10-62783125-272, 62785845-272

传真：86-10-62786911

Last Update: 2012/03/22 English Version

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简历	研究兴趣
教学	学生
项目及负责经费	获奖
学位论文	专著和论文
学术兼职和评委

l 简历

[1] 教授，清华大学自动化系，2008年12月~

[2] 博士生导师，清华大学自动化系，2008年9月~

[3] 访问学者，美国密西根大学工业与运作工程系，2007年1月~2008年1月

[4] 副教授，清华大学自动化系，2002年12月~2008年11月

[5] 讲师，清华大学自动化系，1999年10月~2002年11月

[6] 博士生(直博)，清华大学自动化系，1995~1999

[7] 本科生，清华大学自动化系，1990~1995

[8] 出生日期和地点：1972-08-03，江苏武进

l 研究兴趣

[1] 生产系统建模、计划、调度与优化

[2] 基于计算智能的优化理论、算法与应用，包括遗传算法、模拟退火、禁忌搜索、微粒群、差分进化、分布估计算法、和声搜索、人工蜂群算法、蛙跳算法、神经网络、量子计算等

[3] 仿真优化、序优化

l 教学

[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) [北京市精品课程] [国家精品课程]

[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)

l 学生

博士生:

李令莱 (’2001)

郭一楠 (’2001)

刘波 (’2001)

钱斌 (’2004) [清华大学优秀博士论文]

方晨 (’2008)

许烨 (’2009)

王圣尧 (’2010)

郑晓龙 (’2011)

硕士生:

张亮 (’2002) [清华大学优秀硕士论文]

潘晖 (’2003)

李彬彬 (’2004) [清华大学优秀硕士论文]

何锲 (’2005) [清华大学优秀硕士论文]

黄付卓 (’2006)

李灵坡 (’2007) [清华大学优秀硕士论文]

周刚 (’2009)

张鹏 (’2010)

工程硕士生:

陆屹 (’2003)

马亮 (’2006)

本科生:

李文峰，闫铭 (’2000)

李令莱，朱伟荣 (’2001)

张亮，周崴 (’2002)

吉利军，黄璇 (’2003)

李彬彬，吴昊 (’2004)

何锲 (’2005) [清华大学优秀本科论文]

黄付卓，周昱 (’2006)

邹斌 (’2008)

许烨 (’2009)

王圣尧 (’2010) [清华大学优秀本科论文]

范雪婷 (’2010)

郑晓龙，钟响 (’2011)

l 项目

[1] 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。(590,000RMB，负责人) (2012.1~2015.12)

[2] 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。(250,000RMB，负责人) (2009.1~2011.12)

[3] 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。(270,000RMB，负责人) (2008.1~2010.12)

[4] 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。(150,000RMB，负责人) (2004.1~2006.12)

[5] 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。(200,000RMB，负责人) (2003.1~2005.12)

[6] 国家自然科学基金项目(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。(2,000,000RMB，骨干) (2009.1~2012.12)

[7] 国家自然科学基金项目(60574072)：复杂生产过程基于微粒群的优化调度理论与方法研究。(230,000RMB) (2006.1~2008.12)

[8] 国家自然科学基金项目(60174022)：鲁棒控制建模中几个关健问题的研究。 (50,000RMB，骨干) (2002.1~2002.12)

[9] 国家自然科学基金项目(69684001)：一类混合动态系统控制与优化的理论和方法。(149,000RMB，骨干) (1997.1~1999.12)

[10] 教育部新世纪优秀人才支持计划(NCET-10-0505)。(500,000RMB，负责人) (2010.1~2012.12)

[11] 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。(60,000RMB，负责人) (2011.1~2013.12)

[12] 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。(70,000RMB，负责人) (2004.7~2007.7)

[13] 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。(20,000RMB，负责人) (2009.1~2010.12)

[14] 973计划子课题(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。(3,080,000RMB，成员) (2011.01~2013.08)

[15] 973计划子课题(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。(340,000RMB，主要承担者) (2002.12~2008.5)

[16] 973计划子课题(G1998020310)：混杂电力系统。(个人负责经费20,000RMB，成员) (1998.12~2003.5)

[17] 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。 (710,000RMB，副组长) (2008.1~2009.12)

[18] 863计划项目(2001AA411220)：中国石化自动化系统的总体方案和关键技术。 (个人负责经费39,000RMB，骨干) (2001.12~2002.11)

[19] 863计划项目(863-511-930)：流程工业CIMS的管理模式和集成技术。(个人负责经费70,000RMB，骨干) (2001.1~2001.12)

[20] 863计划项目：大连石化CIMS初步设计。(个人负责经费20,000RMB，骨干) (1999.10~2000.3)

[21] 清华大学骨干人才计划：混合优化算法的研究。(60,000RMB，负责人) (2000.6~2002.5)

[22] 985规划项目：21世纪面向流程工业的系统集成理论、方法和技术。(个人负责经费10,000 RMB，成员) (2001~2002)

[23] 清华大学学术新人奖及教学、论文资助经费。(250,000RMB，负责人) (2002~2011)

[24] 国际合作项目：服务网络的有效仿真和优化。(个人负责经费65,000RMB，骨干) (2002.4~2004.4)

[25] 横向合作：HIS系统的开发。(个人负责50,000RMB，负责人) (2001.5~2001.12)

l 获奖

[1] 2009年度教育部新世纪优秀人才支持计划.

[2] 2009年度清华大学学术新人奖.

[3] 2004年度北京市科技新星.

[4] 2010年度Scopus青年科学之星新人奖.

[5] 进化优化理论与关键技术及其应用研究。2011年度中国电子学会电子信息科学技术奖二等奖.

[6] 基于计算智能的混合优化与调度方法。2008年度北京市科学技术奖三等奖.

[7] 复杂不确定环境下软计算技术及其应用。2007年度高等学校科学技术奖自然科学奖二等奖.

[8] 模型集辨识及其在控制综合中的应用。2003年度教育部提名国家自然科学一等奖.

[9] An effective co-evolutionary particle swarm optimization for constrained engineering design problems. 2005-2010 Engineering Applications of Artificial Intelligence Top Cited Article Awarded by Elsevier.

[10] An estimation of distribution algorithm for the flexible job-shop scheduling problem. IEEE国际智能计算会议最佳论文奖，ICIC’2011.

[11] An effective hybrid particle swarm optimization for designing IIR filters. IET咨询与控制技术国际会议优秀论文，ICT’2006.

[12] Order-based genetic algorithm for flow shop scheduling. IEEE机器学习和控制论国际会议优秀论文奖，ICMLC’2002.

[13] An estimation of distribution algorithm for resource-constrained project scheduling problem. Finalist for Zhang Si-Ying Outstanding Youth Paper Award, CCDC’1010.

[14] 仿真优化的集成框架及其关键问题。中国控制与决策年会优秀论文，CCDC’2004.

[15] 基于假设检验的智能优化算法及其比较。中国控制与决策年会优秀论文，CCDC’2004.

[16] 混合优化策略和神经网络中若干问题的研究。清华大学优秀博士论文一等奖.

[17] The Academic Keys Who's Who in Engineering Higher Education (WWEHE)

[18] 车间调度及其遗传算法。2008年度清华大学优秀教材二等奖.

[19] 智能优化算法及其应用。2004年度清华大学优秀教材二等奖.

[20] 智能优化算法及其应用。2002年度清华大学出版社第11届图书节优秀教材一等奖.

[21] 2005年度清华大学优秀班主任一等奖.

[22] 2004年度清华大学优秀班主任一等奖.

l 学位论文

[1] 博士论文：混合优化策略和神经网络中若干问题的研究，1999.

[2] 硕士论文：随机优化算法及其混合策略，1997.

[3] 本科论文：1/N顾客流路径的优化研究，1995.

l 专著和论文

[Till 2011-09-01, SCI Times Cited 1075, h index=20, Google Scholar Times Cited > 4000, CNKI Times Cited > 4000]

A. 专著:

[1] Wang L, Li BB. Quantum-inspired genetic algorithms for flow shop scheduling. In: Quantum Inspired Intelligent Systems, Nedjah N, Coelho LDS and Mourelle LDM, Eds. Berlin: Springer, 2008. Studies in Computational Intelligence (SCI), 2008, 121: 17-56.

[2] 王凌, 刘波. 微粒群优化与调度算法. 北京: 清华大学出版社, 2008(第1次印刷); 2011(第2次印刷). (SCI Times Cited 3)

[3] 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.

[4] 王凌. 启发式优化算法. 见：《中国大百科全书》(第二版). 北京: 中国大百科全书出版社, 2004.

[5] 王凌. 车间调度及其遗传算法. 北京: 清华大学&Springer出版社, 2003. (SCI Times Cited 37, Google Scholar Times Cited > 200, CNKI Times Cited > 400)

[6] 王凌. 智能优化算法及其应用. 北京: 清华大学&Springer出版社, 2001.10(第1次印刷); 2003.3(第2次印刷); 2004.3(第3次印刷); 2004.11(第4次印刷). (SCI Times Cited 56, Google Scholar Times Cited > 1000, CNKI Times Cited > 2000)

B. 国际期刊论文：

² Forthcoming

[1] Wang L, Zhou G, Xu Y, Liu M. An enhanced Pareto-based artificial bee colony algorithm for the multi-objective flexible job-shop scheduling. International Journal of Advanced Manufacturing Technology. (SCI, EI-IP51645712)

[2] Wang L, Zhou G, Xu Y, Wang SY, Liu M. An effective artificial bee colony algorithm for the flexible job-shop scheduling problem. International Journal of Advanced Manufacturing Technology. (SCI, EI-IP51602110)

[3] Wang L, Xu Y, Zhou G, Wang SY, Liu M. A novel decoding method for the hybrid flow-shop scheduling problem with multiprocessor tasks. International Journal of Advanced Manufacturing Technology. (SCI, EI-IP51553269)

² 2012

[4] 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. (SCI, EI-IP51797003)

[5] Chen J, Pan QK, Wang L, Li JQ. A hybrid dynamic harmony search algorithm for identical parallel machines scheduling. Engineering Optimization, 2012, 44(2): 209-224. (SCI, EI-20120514733885)

[6] Zhao JQ, Wang L, Zeng P, Fan WH. An effective hybrid genetic algorithm with flexible allowance technique for constrained engineering design optimization. Expert Systems with Applications, 2012, 39(5): 6041-6051. (SCI, EI-20120314701282)

[7] Wang L, Wang SY, Xu Y. An effective hybrid EDA-based algorithm for solving multidimensional knapsack problem. Expert Systems with Applications, 2012, 39(5): 5593-5599. (SCI, EI-20120314701225)

[8] Wang L, Li LP. A coevolutionary differential evolution with harmony search for reliability-redundancy optimization. Expert Systems with Applications, 2012, 39(5): 5271-5278. (SCI, EI-20120314701182)

[9] Wang L, Zhong X, Liu M. A novel group search optimizer for multi-objective optimization. Expert Systems with Applications, 2012, 39(3): 2939-2946. (SCI-858SP, EI-20114514491400)

[10] Wang L, Fang C. A hybrid estimation of distribution algorithm for solving the resource-constrained project scheduling problem. Expert Systems with Applications, 2012, 39(3): 2451-2460. (SCI-858SP, EI-20114514491345)

[11] Fang C, Wang L. An effective shuffled frog-leaping algorithm for resource-constrained project scheduling problem. Computers & Operations Research, 2012, 39(5): 890-901. (SCI-834YO, EI-20113614298097)

[12] 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. (SCI-825WG)

[13] 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. (SCI-828YK, EI-20112414050974)

² 2011

[14] 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) (SCI-725UL, EI-20110913706589, SCI Times Cited 1)

[15] Pan QK, Wang L, Gao L. A chaotic harmony search algorithm for the flow shop scheduling with limited buffers. Applied Soft Computing, 2011, 11(8): 5270-5280. (SCI-841UI, EI-20114114412316, SCI Times Cited 1)

[16] Xu Y, Wang L. Differential evolution algorithm for hybrid flow-shop scheduling problem. Journal of Systems Engineering and Electronics, 2011, 22(5): 794-798. (SCI-838IW, EI-20120114654782)

[17] Wang L, Xu Y. An effective hybrid biogeography-based optimization algorithm for parameter estimation of chaotic systems. Expert Systems with Applications, 2011, 38(12): 15103-15109. (SCI-824HQ, EI-20113514271085)

[18] 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. (SCI-802ZG, EI-20113014172409)

[19] Liu B, Wang L, Liu Y, Wang SY. A unified framework for population-based metaheuristics. Annals of Operations Research, 2011, 186(1): 231-262. (SCI-777UX)

[20] 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. (SCI-775KN, EI-20112013986796, SCI Times Cited 1)

[21] Liang JJ, Pan QK, Chen TJ, Wang L. Solving the blocking flow shop scheduling problem by a dynamic multi-swarm particle swarm optimizer. International Journal of Advanced Manufacturing Technology, 2011, 55(5-8): 755-762. (SCI-774MF, EI-20112514072979)

[22] Pan QK, Wang L, Gao L, Li JQ. An effective shuffled frog-leaping algorithm for lot-streaming flow shop scheduling problem. International Journal of Advanced Manufacturing Technology, 2011, 52(5-8): 699-713. (SCI-712IT, EI-20110713659710, SCI Times Cited 1)

[23] Zhao JQ, Wang L. Center based genetic algorithm and its application to the stiffness equivalence of the aircraft wing. Expert Systems with Applications, 2011, 38(5): 6254-6261. (SCI-722GK, EI-20110513630546, SCI Times Cited 2)

[24] Wang L, Xu Y, Li LP. Parameter identification of chaotic systems by hybrid Nelder-Mead simplex search and differential evolution algorithm. Expert Systems with Applications, 2011, 38(4): 3238-3245. (SCI-715RY, EI-20110113541979, SCI Times Cited 1)

[25] 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. (SCI-692AD, EI-20104713413039)

[26] 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. (SCI-658XO, EI-20104513359260, SCI Times Cited 4)

² 2010

[27] Wang L, Pan QK, Tasgetiren MF. Minimizing the total flow time in a flow shop with blocking by using hybrid harmony search algorithms. Expert Systems with Applications, 2010, 37(12): 7929-7936. (SCI-643ZJ, EI-20104213294206, SCI Times Cited 2)

[28] Wang L, Huang FZ. Parameter analysis based on stochastic model for differential evolution algorithm. Applied Mathematics and Computation, 2010, 217(7): 3263-3273. (SCI-670QM, EI-20104413343023, SCI Times Cited 1)

[29] Wang L, Li LP. An effective differential evolution with level comparison for constrained engineering design. Structural and Multidisciplinary Optimization, 2010, 41(6): 947-963. (SCI-584SH, EI-20102212976552)

[30] 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. (SCI-580DK, EI-20101012749537, SCI Times Cited 3)

[31] Wang L, Li LP. An effective hybrid quantum-inspired evolutionary algorithm for parameter estimation of chaotic systems. Expert Systems with Applications, 2010, 37(2): 1279-1285. (SCI-528GZ, EI-20095112558418, SCI Times Cited 3)

[32] 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. (SCI-514BU, EI-20093912346643, SCI Times Cited 7)

² 2009

[33] 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. (SCI-548CU, EI-20093712299943, SCI Times Cited 2)

[34] Peng B, Liu B, Zhang FY, Wang L. Differential evolution algorithm-based parameter estimation for chaotic systems. Chaos, Solitons and Fractals, 2009, 39(5): 2110-2118. (SCI-443DZ, EI-20091612035798, SCI Times Cited 11)

[35] 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. (SCI-416BI, EI-20091311980732, SCI Times Cited 4)

[36] 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. (SCI-411EG, EI-090511884603, SCI Times Cited 6)

[37] 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. (SCI-372OC, EI-084811740642, SCI Times Cited 7)

[38] 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. (SCI-362NL, EI-082411317635, SCI Times Cited 17)

² 2008

[39] 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) (SCI-317KX, EI-082811372109, SCI Times Cited 9)

[40] Pan QK, Wang L. No-idle permutation flow shop scheduling based on a hybrid discrete particle swarm optimization algorithm. International Journal of Advanced Manufacturing Technology, 2008, 39(7-8): 796-807. (SCI-359BP, EI-084911757568, SCI Times Cited 5)

[41] Pan QK, Wang L, Zhao BH. An improved iterated greedy algorithm for the no-wait flow shop scheduling with makespan criterion. International Journal of Advanced Manufacturing Technology, 2008, 38(7-8): 778-786. (SCI-338ZJ, EI-083411477796, SCI Times Cited 6)

[42] Qian B, Wang L, Hu R, Wang WL, Huang DX, Wang X. A hybrid differential evolution for permutation flow-shop scheduling. International Journal of Advanced Manufacturing Technology, 2008, 38(7-8): 757-777. (SCI-338ZJ, EI-083411477795, SCI Times Cited 7)

[43] Pan QK, Wang L, Tasgetiren MF, Zhao BH. A hybrid discrete particle swarm optimization algorithm for the no-wait flow shop scheduling problem with makespan criterion. International Journal of Advanced Manufacturing Technology, 2008, 38(3-4): 337-347. (SCI-335UQ, EI-083411469080, SCI Times Cited 8)

[44] Pan QK, Wang L, Qian B. A novel multi-objective particle swarm optimization algorithm for no-wait flow shop scheduling problems. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2008, 222(4): 519-539. (SCI-316MU, EI-082711351016)

[45] 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. (SCI-271PO, EI-080611085891, SCI Times Cited 21)

[46] Pan QK, Wang L. A novel differential evolution algorithm for the no-idle permutation flow shop scheduling problems. European Journal of Industrial Engineering, 2008, 2(3): 279-297. (SCI-446MN, EI-081511199136, SCI Times Cited 6)

[47] Qian B, Wang L, Huang DX, Wang X. Scheduling multi-objective job shops using a memetic algorithm based on differential evolution. International Journal of Advanced Manufacturing Technology, 2008, 35(9-10): 1014-1027. (SCI-252TY, EI-080511064635, SCI Times Cited 12)

[48] Pan H, Wang L, Liu B. Chaotic annealing with hypothesis test for function optimization in noisy environment. Chaos, Solitons and Fractals, 2008, 35(5): 888-894. (SCI-236ID, EI-074210873572, SCI Times Cited 8)

² 2007

[49] 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). (SCI-170DJ, EI-072210618572, SCI Times Cited 25)

[50] 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). (SCI-135CN, EI-071110477409, SCI Times Cited 39)

[51] He Q, Wang L, Liu B. Parameter estimation for chaotic systems by particle swarm optimization. Chaos, Solitons and Fractals, 2007, 34(2): 654-661. (SCI-175OE, EI-071610552661, SCI Times Cited 28)

[52] Liu B, Wang L, Jin YH, Tang F, Huang DX. Control and synchronization of chaotic systems by differential evolution algorithm. Chaos, Solitons and Fractals, 2007, 34(2): 412-419. (SCI-175OE, EI-071610552631, SCI Times Cited 14)

[53] Li LL, Zhou DH, Wang L. Fault diagnosis of nonlinear systems based on hybrid PSOSA optimization algorithm. International Journal of Automation and Computing, 2007, 4(2): 183-188. (EI-073110728194)

[54] He Q, Wang L. A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization. Applied Mathematics and Computation, 2007, 186(2): 1407-1422. (SCI-163MK, EI-071410523957, SCI Times Cited 31)

[55] Huang FZ, Wang L, He Q. An effective co-evolutionary differential evolution for constrained optimization. Applied Mathematics and Computation, 2007, 186(1): 340-356. (SCI-161FD, EI-071210505763, SCI Times Cited 21)

[56] Liu B, Wang L, Jin YH. An effective hybrid particle swarm optimization for no-wait flow shop scheduling. International Journal of Advanced Manufacturing Technology, 2007, 31(9-10): 1001-1011. (SCI-138AQ, EI-070310376551, SCI Times Cited 29)

[57] 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. (SCI-128GV, EI-064510229471, SCI Times Cited 52, EAAI Top Cited Article 2005-2010 Awarded by Elsevier)

² 2006

[58] 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. (SCI-031EL, EI-06079696641, SCI Times Cited 28)

[59] Pan H, Wang L, Liu B. Particle swarm optimization for function optimization in noisy environment. Applied Mathematics and Computation, 2006, 181(2): 908-919. (SCI-110NK, EI-064410216773, SCI Times Cited 10)

[60] Li LL, Wang L, Liu LH. An effective hybrid PSOSA strategy for optimization and its application to parameter estimation. Applied Mathematics and Computation, 2006, 179(1): 135-146. (SCI-088LZ, EI-063410080518, SCI Times Cited 12)

[61] Wang L, Zhang L Stochastic optimization using simulated annealing with hypothesis test. Applied Mathematics and Computation, 2006, 174(2): 1329-1342. (SCI-027HY, EI-06109743893, SCI Times Cited 5)

[62] Liu B, Wang L, Jin YH, Tang F, Huang DX. Directing orbits of chaotic systems by particle swarm optimization. Chaos, Solitons and Fractals, 2006, 29(2): 454-461. (SCI-028JV, EI-06059677656, SCI Times Cited 16)

[63] Wang L, Zhang L. Determining optimal combination of genetic operators for flow shop scheduling. International Journal of Advanced Manufacturing Technology, 2006, 30(3-4): 302-308. (SCI-068RV, EI-063210059005, SCI Times Cited 3)

[64] Zhang L, Wang L, Zheng DZ. An adaptive genetic algorithm with multiple operators for flow shop scheduling. International Journal of Advanced Manufacturing Technology, 2006, 27(5-6): 580-587. (SCI-990EJ, EI-05509542884, SCI Times Cited 5)

² 2005

[65] Wang L, Tang F, Wu H. Hybrid genetic algorithm based on quantum computing for numerical optimization and parameter estimation. Applied Mathematics and Computation, 2005, 171(2): 1141-1156. (SCI -015GM , EI-06059668761, SCI Times Cited 19)

[66] Wang L. A hybrid genetic algorithm-neural network strategy for simulation optimization. Applied Mathematics and Computation, 2005, 170(2): 1329-1343. (SCI-980YQ, EI-05449448565, SCI Times Cited 17)

[67] Wang L, Li LL, Tang F. Optimal reduction of models using a hybrid searching strategy. Applied Mathematics and Computation, 2005, 168(2): 1357-1369. (SCI-976UW, EI-05419411614, SCI Times Cited 4)

[68] Tang F, Wang L. An adaptive active control for the modified Chua’s circuit. Physics Letters A, 2005, 346(5-6): 342-346. (SCI-979HD, SCI Times Cited 21)

[69] 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 (SCI-929NL, EI-05219111132, SCI Times Cited 116)

[70] Wang L, Zhang L, Zheng DZ. Genetic ordinal optimisation for stochastic flow shop scheduling. International Journal of Advanced Manufacturing Technology, 2005, 27(1-2): 166-173. (SCI-986QH, EI-05489516760, SCI Times Cited 2)

[71] Wang L, Zhang L, Zheng DZ. A class of hypothesis-test based genetic algorithm for flow shop scheduling with stochastic processing time. International Journal of Advanced Manufacturing Technology, 2005, 25(11-12): 1157-1163. (SCI-928MA, EI-05229127233, SCI Times Cited 9)

² 2004

[72] Wang L, Zhang L, Zheng DZ. The ordinal optimisation of genetic control parameters for flow shop scheduling. International Journal of Advanced Manufacturing Technology, 2004, 23(11-12): 812-819. (SCI-829DZ, EI-04308280893, SCI Times Cited 2).

[73] Wang L, Li LL, Tang F. Directing orbits of chaotic systems using a hybrid optimization strategy. Physics Letters A. 2004, 324(1): 22-25. (SCI-808CX, SCI Times Cited 8)

² 2003

[74] Wang L, Zhang L, Zheng DZ. A class of order-based genetic algorithm for flow shop scheduling. International Journal of Advanced Manufacturing Technology. 2003, 22(11-12): 828-835. (SCI-752CH, EI-04037817728, SCI Times Cited 17)

[75] Wang L, Zheng DZ. A modified evolutionary programming for flow shop scheduling. International Journal of Advanced Manufacturing Technology, 2003, 22(7-8): 522-527. (SCI-741NA, EI-03507780860, SCI Times Cited 14)

[76] Wang L, Zheng DZ. An effective hybrid heuristic for flow shop scheduling. International Journal of Advanced Manufacturing Technology, 2003, 21(1): 38-44. (SCI-653WV, EI-03087368196, SCI Times Cited 63)

[77] Jiang YH, Wang L, Jin YH. Bottleneck analysis for network flow model. Advances in Engineering Software, 2003, 34(10): 641-651. (SCI-727WR, EI-03417667435, SCI Times Cited 1)

² 2002

[78] Wang L, Zheng DZ. Finite-time performance analysis for genetic algorithm. Progress in Natural Science, 2002, 12(12): 940-944. (SCI-620AV, EI-03047337279)

[79] Wang L, Zheng DZ. A modified genetic algorithm for job shop scheduling. International Journal of Advanced Manufacturing Technology, 2002, 20(1): 72-76. (SCI-587DX, EI-02357058287, SCI Times Cited 18)

[80] Zhou T, Wang L, Sun ZS. Closed-loop model set validation under a stochastic framework. Automatica, 2002, 38(9): 1449-1461. (SCI -586AC , EI-02307032983, SCI Times Cited 6)

² 2001

[81] Wang L, Zheng DZ. An effective hybrid optimization strategy for job-shop scheduling problems. Computers & Operations Research, 2001, 28(6): 585-596. (SCI-413MP, EI-01015497525, SCI Times Cited 72)

C. 国际会议论文：

² 2012

[1] Wang SY, Wang L, Xu Y. A compact estimation of distribution algorithm for solving hybrid flow-shop scheduling problem. The 10th World Congress on Intelligent Control and Automation, Beijing , WCICA’2012. (EI)

[2] Xu Y, Wang L, Wang SY. A hybrid algorithm based on simplex search and differential evolution for hybrid flow-shop scheduling. The 10th World Congress on Intelligent Control and Automation, Beijing , WCICA’2012. (EI)

² 2011

[3] Wang L, Xu Y, Fang C. A hybrid algorithm based on simplex search and differential evolution for resource-constrained project scheduling problem. The 2011 International Conference on Intelligent Computing, Zhengzhou , ICIC’2011. Lecture Notes in Computer Science, 2011, 6838: 568-575. (EI-20120914805584)

[4] Xu Y, Wang L, Zhou G, Wang SY. An effective shuffled frog leaping algorithm for solving hybrid flow-shop scheduling problem. The 2011 International Conference on Intelligent Computing, Zhengzhou , ICIC’2011. Lecture Notes in Computer Science, 2011, 6838: 560-567. (EI-20120914805583)

[5] Zhou G, Wang L, Xu Y, Wang SY. An effective artificial bee colony algorithm for multi-objective flexible job-shop scheduling problem. The 2011 International Conference on Intelligent Computing, Zhengzhou , ICIC’2011. Lecture Notes in Artificial Intelligence, 2011, 6839: 1-8. (EI-20120314683799)

[6] Wang SY, Wang L, Zhou G, Xu Y. An estimation of distribution algorithm for the flexible job-shop scheduling problem. The 2011 International Conference on Intelligent Computing, Zhengzhou , ICIC’2011. Lecture Notes in Artificial Intelligence, 2011, 6839: 9-16. EI-20120314683810, Best Paper Award)

[7] Tasgetiren MF, Pan QK, Wang L, Chen AHL. A DE based variable iterated greedy algorithm for the no-idle permutation flowshop scheduling problem with total flowtime criterion. The 2011 International Conference on Intelligent Computing, Zhengzhou , ICIC’2011. Lecture Notes in Artificial Intelligence, 2011, 6839: 83-90. (EI-20120314683801)

² 2010

[8] Huang XL, Jia PF, Liu B, Wang L. Control of Hénon chaotic systems by chaotic particle swarm optimization. The 9th IEEE International Conference on Cognitive Informatics, Beijing , ICCI’2010, 117-121. (EI-20105013469236)

[9] Huang XL, Jia PF, Liu B, Wang L. Chaotic particle swarm optimization for synchronization of finite dimensional Hénon dynamical system. The 6th International Conference on Natural Computation, Jinan , ICNC’2010, v 5, 2600-2604. (EI-20104613375432)

² 2009

[10] Li LP, Wang L, Xu Y. Differential evolution with level comparison for constrained optimization. The 2009 International Conference on Intelligent Computing, Ulsan , ICIC’2009. Lecture Notes in Artificial Intelligence, 2009, 5755: 351-360. (EI-20094612450581, ISTP-BLM65)

[11] Xu Y, Wang L, Li LP. An effective hybrid algorithm based on simplex search and differential evolution for global optimization. The 2009 International Conference on Intelligent Computing, Ulsan , ICIC’2009. Lecture Notes in Artificial Intelligence, 2009, 5755: 341-350. (EI-20094512418317, ISTP-BLM65, SCI Times Cited 2)

[12] Li LP, Wang L. A DE-based memetic algorithm for re-entrant permutation flowshop scheduling problems. The 20th International Conference on Production Research, IFPR, Shanghai, ICPR’2009.

[13] Li LP, Wang L. Hybrid algorithms based on harmony search and differential evolution for global optimization. The 2009 World Summit on Genetic and Evolutionary Computation, ACM/SIGEVO, Shanghai, GEC’2009, 271-278. (EI-20093012219499, ISTP-BRC96)

² 2008

[14] Liu B, Wang L, Qian B, Jin YH. Hybrid particle swarm optimization for stochastic flow shop scheduling with no-wait constraint. The 17th IFAC World Congress, Seoul , 2008, 15855-15860. (EI-20094012355265)

[15] Huang FZ, Wang L. A hybrid differential evolution with double populations for constrained optimization. IEEE Congress on Evolutionary Computation, Hongkong, CEC’2008, 18-25. (ISTP-BIW46, EI-084611709657, SCI Times Cited 2)

[16] He Q, Wang L, Huang FZ. Nonlinear constrained optimization by enhanced co-evolutionary PSO. IEEE Congress on Evolutionary Computation, Hongkong, CEC’2008, 83-89. (ISTP-BIW46, EI-084611709666, SCI Times Cited 1)

[17] Hu R, Wang L, Qian B, Huang FZ. Differential evolution method for stochastic flow shop scheduling with limited buffers. IEEE Congress on Evolutionary Computation, Hongkong, CEC’2008, 1295-1301. (ISTP-BIW46, EI-084611709838)

² 2007

[18] Liu B, Wang L, Jin YH, Huang DX. Designing neural networks using PSO-based memetic algorithm. International Symposium on Neural Networks, Nanjing , ISNN’2007. Lecture Notes in Computer Science, 2007, 4493: 219-224. (ISTP-BGH87, EI-080311036869, SCI Times Cited 2)

[19] Liu Y, Liu B, Huang JK, Wu YH, Wang L, Jin YH. An intelligent differential evolution algorithm for designing trading-ratio system of water market. International Symposium on Neural Networks, Nanjing , ISNN’2007. Lecture Notes in Computer Science, 2007, 4493: 1058-1066. (ISTP-BGH87, EI-080311036970)

² 2006

[20] Liu B, Wang L, Jin YH, Huang DX. An effective PSO-based memetic algorithm for TSP. International Conference on Intelligent Computing, Kunming , ICIC’2006. Lecture Notes in Control and Information Sciences, 2006, 345: 1151-1156. (SCI-BEZ63, ISTP-BEZ63, SCI Times Cited 1)

[21] Qian B, Wang L, Huang DX, Wang X. Multi-objective flow shop scheduling using differential evolution. International Conference on Intelligent Computing, Kunming , ICIC’2006. Lecture Notes in Control and Information Sciences, 2006, 345: 1125-1136. (SCI-BEZ63, ISTP-BEZ63, SCI Times Cited 2)

[22] Huang FZ, Wang L, Liu B. Improved differential evolution with dynamic population size. International Conference on Intelligent Computing, Kunming , ICIC’2006. Lecture Notes in Computer Science, 2006, 4113: 725-730. (EI-064210172676, ISTP-BPE89)

[23] Li BB, Wang L. A hybrid quantum-inspired genetic algorithm for multi-objective scheduling. International Conference on Intelligent Computing, Kunming , ICIC’2006. Lecture Notes in Computer Science, 2006, 4113: 511-522. (EI-064210172653, ISTP-BPE89, SCI Times Cited 4)

[24] Pan H, Wang L. Blending scheduling under uncertainty based on particle swarm optimization with hypothesis test. International Conference on Intelligent Computing, Kunming , ICIC’2006. Lecture Notes in Bioinformatics, 2006, 4115: 109-120. (SCI-BEY16, ISTP-BEY16, EI-064210172349, SCI Times Cited 1)

[25] Wang L, Liu LH, Liu B, Pan QK. An effective hybrid particle swarm optimization for designing IIR filters. International Conference on Informatics and Control Technologies, Shenzhen, ICT’2006, 181-186.

[26] Liu Y, Huang JK, Wu YH, Liu B, Wang L, Jin YH. An intelligent particle swarm optimization for designing trading-ratio system of water market. International Conference on Sensing, Computing and Automation, Chengdu , ICSCA’2006. Dynamics of Continuous Discrete and Impulsive Systems-Series B-Applications & Algorithms, 2006, 13E: 1757-1761. (ISTP-201OS)

² 2005

[27] Liu B, Wang L, Jin YH. Hybrid particle swarm optimization for flow shop scheduling with stochastic processing time. International Conference on Computational Intelligence and Security, Xi’an , CIS’2005. Lecture Notes in Artificial Intelligence, 2005, 3801: 630-637. (SCI-BDQ19, ISTP-BDQ19, SCI Times Cited 8)

[28] Wang L, Wu H, Zheng DZ. A quantum-inspired genetic algorithm for scheduling problems. International Conference on Natural Computation, Changsha , ICNC’2005. Lecture Notes in Computer Science, 2005, 3612: 417-423. (SCI-BDA32, EI-05439427037, ISTP-BDA32, SCI Times Cited 3)

[29] Wang L, Wu H, Tang F, Zheng DZ. A hybrid quantum-inspired genetic algorithm for flow shop scheduling. International Conference on Intelligent Computing, Hefei , ICIC’2005. Lecture Notes in Computer Science, 2005, 3645: 636-644. (SCI-BDC10, EI-05449443744, ISTP-BDC10, SCI Times Cited 7)

[30] Liu B, Wang L, Jin YH, Huang DX. Designing neural networks using hybrid particle swarm optimization. International Symposium on Neural Networks, Chongqing , ISNN'2005. Lecture Notes in Computer Science, 2005, 3496: 391-397. (SCI-BCN38, EI-05399382245, ISTP-BCN38, SCI Times Cited 9)

² 2004

[31] Wang L, Tang F. NN-based GA for engineering optimization. International Symposium on Neural Networks, Dalian , ISNN'2004. Lecture Notes in Computer Science, 2004, 3173: 448-453. (SCI-BAT64, ISTP-BAT64)

[32] Zhang L, Wang L. Genetic ordinal optimization for stochastic traveling salesman problem. The 5th World Congress on Intelligent Control and Robotics, Hangzhou , WCICA’2004. 2086-2090. (EI-04388368171)

[33] Wang L, Zheng DZ, Huang DX. Hybrid strategy for parameter estimation and PID tuning. The 7^th International Symposium on Advanced Control of Chemical Processes, Hongkong, ADCHEM’2003. 1011-1016.

² 2003

[34] Zhang L, Wang L. Optimal parameters selection for simulated annealing with limited computational effort. IEEE International Conference on Neural Networks & Signal Processing, Nanjing , ICNNSP'2003. 412-415. (ISTP-BY77R, SCI Times Cited 1)

[35] Li LL, Tang F, Wang L. Directing orbits of chaotic dynamical systems based on simplex-annealing strategy. IEEE International Conference on Neural Networks & Signal Processing, Nanjing , ICNNSP'2003. 748-750. (ISTP-BY77R)

[36] Zhang L, Wang L, Tang F. Hypothesis-test based simulated annealing for stochastic flow shop scheduling. The Second International Conference on Machine Learning and Cybernetics, Xi'an , ICMLC’2003. 1607-1612. (EI-04128072128, ISTP-BY 61C )

² 2002

[37] Zhang L, Wang L, Tang F. Order-based genetic algorithm for flow shop scheduling. The First International Conference on Machine Learning and Cybernetics, Beijing , ICMLC’2002. 139-144. (Outstanding Paper Award, ISTP-BW27J, EI-03127405529, SCI Times Cited 1)

[38] Yang C, Ye H, Wang JC, Wang L. An artificial life and genetic algorithm based on optimization approach with new selecting methods. The First International Conference on Machine Learning and Cybernetics, Beijing , ICMLC’2002. 684-688. (ISTP-BW27J, EI-03127405646)

[39] Wang L, Zheng DZ, Tang F. An improved evolutionary programming for optimization. The 4th World Congress on Intelligent Control and Robotics, Shanghai , WCICA’2002. Volume 3, 1769-1773. (ISTP-BV 45G , EI-03047336817, SCI Times Cited 5)

² 2001

[40] Wang L, Li WF, Zheng DZ. Design higher-order digital differentiator with simulated annealing. The 5th International Conference on Electronic Measurement & Instruments, Guilin , ICEMI’2001. 883-886. (ISTP-BU70Y)

[41] Wang L, Li WF, Zheng DZ. A class of hybrid strategy for adaptive IIR filter design. The 8th International Conference on Neural Information Processing, Shanghai , ICONIP’2001. 85-89. (ISTP-BU 46F )

² 2000

[42] Wang L, Zheng DZ. Global derivative-free training for feed-forward neural networks. The 3rd Asian Control Conference, Shanghai , ASCC’2000. 1570-1575. (SCI Times Cited 2)

D. 国内期刊论文：

² 2011

[1] 王圣尧, 王凌, 方晨, 许烨. 分布估计算法研究进展. 控制与决策. (EI)

[2] 王圣尧, 王凌, 许烨, 周刚. 求解混合流水车间调度问题的分布估计算法. 自动化学报, 2012, 38(3): 437-443. (EI)

[3] 王凌, 王圣尧, 方晨. 求解多维背包问题的一种混合分布估计算法. 控制与决策, 2011, 26(8): 1121-1125. (EI-20113714332583)

[4] 王凌, 周刚, 许烨, 金以慧. 混合流水线调度研究进展. 化工自动化及仪表, 2011, 38(1): 1-8.

² 2010

[5] 潘全科, 王凌, 高亮, 桑红燕. 基于差分进化与块结构邻域的作业车间调度优化. 机械工程学报, 2010, 46(22): 182-188. (EI-20105113512677)

[6] 方晨, 王凌. 资源约束项目调度研究综述. 控制与决策, 2010, 25(5): 641-650,656. (EI-20102513030536)

² 2009

[7] 潘全科, 王凌, 高亮. 离散微粒群优化算法的研究进展. 控制与决策, 2009, 24(10): 1441-1449. (EI-20094812504029)

[8] 王凌, 黄付卓, 李灵坡. 基于混合双种群差分进化的电力系统经济负荷分配. 控制与决策, 2009, 24(8): 1156-1160,1166. (EI-20093712302656)

[9] 钱斌, 王凌, 黄德先, 江永亨, 王雄. 动态零等待流水线调度问题的滚动策略及优化算法. 控制与决策, 2009, 24(4): 481-487. (EI-20092012082873)

² 2008

[10] 王凌. 量子进化算法研究进展. 控制与决策, 2008, 23(12): 1321-1326. (EI-090111830321)

[11] 潘全科, 王凌, 赵保华. 解决零空闲流水线调度问题的离散粒子群算法. 控制与决策, 2008, 23(2): 191-194. (EI-081311170208)

[12] 王凌, 何锲, 金以慧. 智能约束处理技术综述. 化工自动化及仪表, 2008, 35(1): 1-7.

² 2007

[13] 刘波, 王凌, 金以慧. 差分进化算法研究进展. 控制与决策, 2007, 22(7): 721-729. (EI-073210754583, SCI Times Cited 2)

² 2006

[14] 潘晖, 王凌, 刘波, 金以慧. 噪声环境下参数估计和模型降阶的一种有效方法. 化工自动化及仪表, 2006, 33(5): 13-17. (EI-065110317733)

[15] 刘丽姮, 王凌, 刘波, 金以慧. 基于一类混合PSO算法的函数优化与模型降阶研究. 化工自动化及仪表, 2006, 33(2): 9-12. (EI-06229913045)

² 2005

[16] 刘波, 王凌, 金以慧, 黄德先. 微粒群优化算法研究进展. 化工自动化及仪表, 2005, 32(3): 1-7. (EI-05279198140, SCI Times Cited 11)

[17] 王凌, 张亮. 有限缓冲区流水线调度的多搜索模式遗传算法. 计算机集成制造系统, 2005, 11(7): 1041-1046. (EI-05359331186)

[18] 王凌, 李彬彬, 郑大钟. 模型降阶和参数估计的一种快速遗传算法. 控制与决策, 2005, 20(4): 426-429,433. (EI-05229136659)

[19] 王凌, 吴昊, 唐芳, 郑大钟. 混合量子遗传算法及其性能分析. 控制与决策, 2005, 20(2): 156-160. (EI-05149025694)

² 2004

[20] Zhang L, Wang L, Zheng DZ. Hypothesis-test based genetic algorithm for stochastic optimization problems. Control Theory and Applications, 2004, 21(6): 885-889. (EI-05108875003, SCI Times Cited 1)

[21] 李彬彬, 王凌, 郑大钟. 基于插值评价的遗传算法及其在参数估计中的应用. 化工自动化及仪表, 2004, 31(6): 14-17. (EI-05279198084)

[22] 王凌, 黄璇, 郑大钟. 一类带筛选策略的改进遗传算法及其性能分析. 控制与决策, 2004, 19(11): 1290-1293, 1297. (EI-05048803655)

[23] 李令莱, 王凌, 郑大钟. 基于一类SMSA策略的模型最优降阶. 控制与决策, 2004, 19(8): 947-950, 953. (EI-04468459062)

[24] 王凌, 童行行, 郑大钟. TSP基于参考点的相邻插入法和两阶段方法. 控制与决策, 2004, 19(7): 831-833, 837. (EI-04438424613)

[25] 王凌, 吉利军, 郑大钟. 基于代理模型和遗传算法的仿真优化研究. 控制与决策. 2004, 19(6): 626-630. (EI-04378354978)

[26] 王凌, 郑大钟. 随机优化问题一类基于假设检验的模拟退火算法. 控制与决策, 2004, 19(2): 183-186. (EI-04248214379, SCI Times Cited 1)

[27] 张亮, 王凌, 郑大钟. 有限计算量下模拟退火算法的参数序优化. 控制与决策, 2004, 19(2): 226-229.

² 2003

[28] 王凌, 李令莱, 郑大钟. 非线性系统参数估计的一类有效搜索策略. 自动化学报, 2003, 29(6): 953-958. (SCI Times Cited 2)

[29] 王凌, 李文峰, 郑大钟. 非最小相位系统控制器的优化设计. 自动化学报, 2003, 29(1): 135-141. (SCI Times Cited 2)

[30] 王凌, 张亮, 郑大钟. 仿真优化研究进展. 控制与决策, 2003, 18(3): 257-262, 271. (SCI Times Cited 3)

[31] 王凌, 张亮, 唐芳. 遗传算法参数和操作的序优化. 中南工业大学学报, 2003, 34(4): 350-354.

[32] 王凌, 王雄. 流程工业CIMS体系结构和生产执行系统. 计算机工程与应用, 2003, 39(10): 16-18.

[33] 李令莱, 王凌. 基于多操作SMSA算法的化工过程优化. 化工自动化及仪表, 2003, 30(1): 25-28. (EI-04328307443)

² 2002

[34] 王凌, 张亮, 郑大钟. 随机仿真优化的一类遗传序优化框架. 控制与决策, 2002, 17(S): 699-702. (EI-03087370158)

[35] 王凌, 郑大钟. 混合优化策略统一结构的探讨. 控制与决策, 2002, 17(1): 33-36,40. (EI-02397107558)

[36] 蓝海, 王雄, 王凌. 复杂函数最优化的改进遗传退火算法. 清华大学学报, 2002, 42(9): 1237-1240. (EI-03027313247, SCI Times Cited 1)

[37] 李令莱, 王凌, 郑大钟, 等. 基于Simplex-annealing混合方法的模型参数估计. 清华大学学报, 2002, 42(9): 1207-1208, 1213. (EI-03027313239, SCI Times Cited 1)

[38] 郭一楠, 王凌, 谭德健, 郝榕. 基于遗传算法和神经网络混合优化的配煤控制. 中国矿业大学学报, 2002, 31(5): 404-406. (EI-02457195019)

[39] 王凌, 李令莱, 郑大钟. 设计自适应IIR滤波器的一种单纯形-退火策略. 系统工程与电子技术, 2002, 24(7): 99-102.

[40] 王凌, 郑大钟. 求解同顺序加工调度问题的一种改进遗传算法. 系统工程理论与实践, 2002, 22(6): 74-79. (EI-02417136470)

[41] 王凌, 唐芳. 基于遗传退火策略的PID整定研究. 化工自动化及仪表, 2002, 29(3): 21-24.

[42] 童行行, 王凌, 何京芮. 旅行商问题基于参考点的相邻插入法及其改进. 计算机工程与应用, 2002, 38(20): 63-65.

[43] 王凌, 王雄. 流程工业CIMS设计的若干要点. 计算机工程与应用, 2002, 38(10): 50-52,108.

[44] 王凌, 郑大钟. 多目标优化的一类模拟退火算法. 计算机工程与应用, 2002, 38(8): 4-5, 55. (SCI Times Cited 1)

[45] 唐芳, 王凌. 从局部极小到全局最优. 计算机工程与应用, 2002, 38(6): 56-58.

[46] 王凌, 张亮, 郑大钟. 一种广义TSP型交通模型及其优化. 计算机工程与应用, 2002, 38(2): 15-16,42.

[47] 王凌, 郑大钟. 一类改进进化规划及其优化性能分析. 计算机工程与应用, 2002, 38(1): 8-10.

[48] 王凌, 郑大钟. 几类动态反馈神经网络的稳定性分析. 计算技术与自动化, 2002, 21(1): 1-6.

² 2001

[49] 王凌, 郑大钟. 一种GASA混合优化策略. 控制理论与应用, 2001, 18(4), 552-554. (EI-01556802755)

[50] 王凌, 郑大钟. 基于遗传算法的Job Shop调度研究进展. 控制与决策, 2001, 16(S): 641-646. (EI-02246976076)

[51] 王凌, 李文峰, 郑大钟. 基于一类混合策略的模型参数估计和控制器参数整定研究. 控制与决策, 2001, 16(5): 530-534. (EI-02236966472, SCI Times Cited 1)

[52] 王凌, 李文峰, 郑大钟. 基于模拟退火算法的高阶数字微分器设计. 系统工程与电子技术, 2001, 23(12): 1-3.

[53] 王凌, 李令莱, 郑大钟, 等. 非线性时变系统时滞和参数在线联合估计的SMSA方法. 化工自动化及仪表, 2001, 28(6): 5-9. (SCI Times Cited 1)

[54] 王凌, 王雄, 金以慧. MES--流程工业CIMS发展的关键. 化工自动化及仪表, 2001, 28(4): 1-5.

[55] 王凌, 王雄, 金以慧, 萧德云. 基于生命周期和集成平台思想的流程工业CIMS体系结构. 化工自动化及仪表, 2001, 28(1): 1-4,8.

[56] 王凌, 闫铭, 李清生, 郑大钟. 高维复杂函数的一类有效混合优化策略. 清华大学学报, 2001, 41(9):118-121. (EI-02116885825, SCI Times Cited 3)

[57] 王凌, 郑大钟. 一类含同工件流水线调度问题的优化研究. 计算机工程与应用, 2001, 37(19): 76-78.

[58] 蓝海, 王雄, 王凌. 一类遗传退火算法的函数优化性能分析. 系统仿真学报, 2001, 13(S): 111-113.

[59] 李清生, 王凌, 郑大钟. 水轮机系统的控制器整定研究. 基础自动化, 2001, 8(3): 10-12,50.

[60] 王凌, 李文峰, 郑大钟. 模型参数估计的一类混合策略. 基础自动化, 2001, 8(1): 5-7,38.

[61] 王凌, 郑大钟, 李清生. 混沌优化方法的研究进展. 计算技术与自动化, 2001, 20(1): 1-5. (SCI Times Cited 18)

² 2000

[62] 王凌, 郑大钟. 一种基于退火策略的混沌神经网络优化算法. 控制理论与应用, 2000, 17(1): 139-142. (EI-00095313837, SCI Times Cited 1)

[63] 王凌, 郑大钟. Meta-heuristic 算法研究进展. 控制与决策, 2000, 15(3): 257-262. (SCI Times Cited 1)

[64] 王凌, 郑大钟. 基于一类非线性特性的FNN训练算法. 控制与决策, 2000, 15(1): 19-22. (EI-00095311003)

[65] 王凌, 王雄, 金以慧, 萧德云. 流程工业CIMS体系结构的探讨. 自动化博览, 2000, 17(S): 38-40, 50.

[66] 王凌, 郑大钟. 基于Cauchy和Gaussian分布状态发生器的模拟退火算法. 清华大学学报, 2000, 40(9): 109-112. (EI-01436700268, SCI Times Cited 3)

[67] 王凌, 郑大钟. 邻域搜索算法的统一结构和混合优化策略. 清华大学学报, 2000, 40(9): 125-128. (EI-01436700272)

[68] 王凌, 王雄. 间歇化工过程最优化的研究进展. 清华大学学报, 2000, 40(S2): 265-269.

² 1999

[69] 王凌, 郑大钟. TSP及其基于Hopfield神经网络优化的研究. 控制与决策, 1999, 14(6): 669-674. (EI-00095310999)

[70] 王凌, 郑大钟. 径向基函数网络结构的混合优化策略. 清华大学学报, 1999, 39(7): 50-53. (EI-00045122367)

² Before 1999

[71] 王凌, 郑大钟. 一类GASA混合策略及其收敛性研究. 控制与决策, 1998, 13(6): 699-672. (SCI Times Cited 1)

[72] 王凌, 郑大钟. TSP问题次优化求解方法的比较. 控制与决策, 1998, 13(1): 79-83.

[73] 王凌, 郑大钟. 前向网络的两种混合学习策略. 清华大学学报, 1998, 38(9): 95-97, 101. (EI-99094800492)

[74] 郑学哲, 王凌, 金国藩, 等. 实现ICF均匀照明的二元光学器件的混合优化设计. 中国激光A, 1998, 25(3): 265-269. (EI-99084739370)

[75] 宋铁英, 王凌. 森林空间数据的统计与仿真. 北京林业大学学报, 1997, 19(3): 74-78.

[76] 王凌, 郑大钟. 模拟退火算法中若干问题的研究. 清华大学研究生学报, 1996, 26(1): 28-35.

E. 国内会议论文：

² 2010

[1] Fang C, Wang L, Xu Y. An estimation of distribution algorithm for resource-constrained project scheduling problem. Chinese Control and Decision Conference, Xuzhou , 2010. 265-270. (Finalist for Zhang Si-Ying Outstanding Youth Paper Award, EI-20103213140314, ISTP-BUV61)

² 2005

[2] 王凌, 吴昊, 郑大钟. 基于混合量子遗传算法的模型参数估计. 2005’ 中国控制与决策学术年会. 哈尔滨, 2005, 527-530. (ISTP-BFR69)

² 2004

[3] 王凌, 郑大钟. 仿真优化的集成框架及其关键问题. 2004’ 中国控制与决策学术年会. 黄山, 2004, 799-802, 806. (大会优秀论文, EI-04428413058, ISTP-BFR67)

[4] 张亮, 王凌. 基于假设检验的智能优化算法及其比较. 2004’ 中国控制与决策学术年会. 黄山, 2004, 338-341. (大会优秀论文, EI-04428413016, ISTP-BFR67)

² 2002

[5] 王凌, 张亮, 郑大钟. 遗传序优化方法的初步研究. 2002’ 中国过程控制会议, 澳门, 2002, 98-102.

² 2001

[6] 王凌, 郑大钟, 唐芳. 一种新的优化技术—混沌. 2001’ 中国控制会议. 大连, 2001, 185-189.

[7] 李清生, 王凌. 基于混合算法的二元光学器件优化设计. 2001’ 中国控制与决策学术年会. 西安, 2001, 346-349.

[8] 李清生, 王凌. 复杂函数的一种混合优化方法. 2001’ 中国控制与决策学术年会. 西安, 2001, 350-353.

² Before 2001

[9] 王凌, 郑大钟. 基于不同邻域函数的模拟退火算法性能研究. 2000’ 中国控制会议, 香港, 2000, 430-434.

[10] 王凌, 郑大钟. 一类批量可变流水线调度问题的研究. 1998’ 中国控制会议. 宁波, 1998. 491-494.

[11] 王凌, 郑大钟. 模拟退火算法求解Flow-shop问题的研究. 1997’ 中国控制与决策学术年会. 庐山, 1997. 390-394.

[12] 王凌, 郑大钟. 前向网络的两种混合训练策略. 1997’ 中国控制会议. 庐山, 1997.1059-1062.

[13] 王凌, 郑大钟. 几种次优化求解TSP方法的比较研究. 1996’ 中国控制会议. 青岛, 1996. 604-607.

l 学术兼职和评委

[1] 北京市自动化学会常务理事

[2] 国家自然科学基金项目通讯评议专家

[3] 国家863项目通讯评议专家

[4] 北京市自然科学基金项目通讯评议专家

[5] 霍英东基金项目通讯评议专家

[6] 教育部博士点基金项目通讯评议专家

[7] 教育部自然科学奖通讯评议专家

[8] 教育部科技进步奖通讯评议专家

[9] 山东大学威海分校兼职教授

[10] 聊城大学兼职教授

[11] Member, IEEE CIS (Computational Intelligence Society) ETTC (Emergent Technology Technical Committee)

[12] Co-Editor-in-Chief, The Open Operational Research Journal (国际期刊)

[13] Editor-in-Chief, Research Journal of Information Technology (国际期刊)

[14] Regional Editor, Research Journal of Applied Sciences, Engineering and Technology (国际期刊)

[15] Associate Editor, International Journal of Metaheuristics (国际期刊)

[16] Editorial Board Member, International Journal of Automation and Control (国际期刊)

[17] Editorial Board Member, European Journal of Industrial Engineering (国际期刊)

[18] Editorial Board Member: International Journal of Artificial Intelligence and Soft Computing (国际期刊)

[19] Editorial Board Member, Memetic Computing Journal (国际期刊)

[20] Editorial Board Member, Swarm and Evolutionary Computation (国际期刊)

[21] Editorial Board Member, The Open Statistics & Probability Journal (国际期刊)

[22] Editorial Board Member, ICTACT Journal of Soft Computing (国际期刊)

[23] Editor, International Journal of Soft Computing (国际期刊)

[24] Editor, International Journal of Electric and Power Engineering (国际期刊)

[25] Editor, Asian Journal of Information Technology (国际期刊)

[26] Editor, Journal of Engineering and Applied Sciences (国际期刊)

[27] Reviewer, IEEE Computational Intelligence Magazine (国际期刊)

[28] Reviewer, IEEE Transaction on Automation Science and Engineering (国际期刊)

[29] Reviewer, IEEE Transaction on Evolutionary Computation (国际期刊)

[30] Reviewer, IEEE Transaction on Neural Networks (国际期刊)

[31] Reviewer, IEEE Transaction on Signal Processing (国际期刊)

[32] Reviewer, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics (国际期刊)

[33] Reviewer, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews (国际期刊)

[34] Reviewer, Applied Mathematical Modelling (国际期刊)

[35] Reviewer, Applied Mathematics and Computation (国际期刊)

[36] Reviewer, Computers & Industrial Engineering (国际期刊)

[37] Reviewer, Computers & Operations Research (国际期刊)

[38] Reviewer, Engineering Applications of Artificial Intelligence (国际期刊)

[39] Reviewer, European Journal of Operational Research (国际期刊)

[40] Reviewer, Information Sciences (国际期刊)

[41] Reviewer, International Journal of Production Economics (国际期刊)

[42] Reviewer, Journal of Computational and Applied Mathematics (国际期刊)

[43] Reviewer, Journal of Manufacturing Systems (国际期刊)

[44] Reviewer, Mathematics and Computers in Simulation (国际期刊)

[45] Reviewer, Neurocomputing (国际期刊)

[46] Reviewer, Simulation Modelling Practice and Theory (国际期刊)

[47] Reviewer, Discrete Event Dynamic Systems: Theory and Applications (国际期刊)

[48] Reviewer, International Journal of Advanced Manufacturing Technology (国际期刊)

[49] Reviewer, Journal of Computer Science & Technology (国际期刊)

[50] Reviewer, Journal of Global Optimization (国际期刊)

[51] Reviewer, Journal of Systems Science and Systems Engineering (国际期刊)

[52] Reviewer, Neural Computing & Applications (国际期刊)

[53] Reviewer, Soft Computing (国际期刊)

[54] Reviewer, Structural and Multidisciplinary Optimization (国际期刊)

[55] Reviewer, Chemical Engineering Communications (国际期刊)

[56] Reviewer, Engineering Optimization (国际期刊)

[57] Reviewer, International Journal of Production Research (国际期刊)

[58] Reviewer, Computer Jouornal (国际期刊)

[59] Reviewer, International Journal of Artificial Intelligence Tools (国际期刊)

[60] Reviewer, Journal of Computing in Civil Engineering (国际期刊)

[61] Reviewer, ETRI Journal (国际期刊)

[62] Reviewer, International Journal of Operations Research (国际期刊)

[63] Reviewer, Asia Pacific Management Review (国际期刊)

[64] Reviewer, Proceedings of the Institution of Mechanical Engineers, Part B, Journal of Engineering Manufacture (国际期刊)

[65] Reviewer, 中国科学A/E/F

[66] Reviewer, 科学通报

[67] Reviewer, 自动化学报

[68] Reviewer, 控制理论与应用 (中英文版)

[69] Reviewer, 控制与决策

[70] Reviewer, 信息与控制

[71] Reviewer, 软件学报

[72] Reviewer, 计算机学报

[73] Reviewer, 电子学报 (中英文版)

[74] Reviewer, 计算机集成制造系统

[75] Reviewer, 系统工程理论与实践

[76] Reviewer, 系统工程与电子技术 (中英文版)

[77] Reviewer, 中国化学工程学报 (英文版)

[78] Reviewer, 高技术通讯 (中英文版)

[79] Reviewer, 化工学报

[80] Reviewer, 清华大学学报

[81] Reviewer, 浙江大学学报

[82] Reviewer, 北京航空航天大学学报

[83] Reviewer, 武汉大学学报

[84] Reviewer, 西安交通大学学报

[85] Reviewer, 北京科技大学学报

[86] Reviewer, 北京邮电大学学报

[87] Reviewer, 北京理工大学学报

[88] Reviewer, 北方交通大学学报

[89] Reviewer, 北京信息科技大学学报

[90] Reviewer, 上海交通大学学报 (中英文版)

[91] Reviewer, 天津大学学报

[92] Reviewer, 东北大学学报

[93] Reviewer, 中南大学学报

[94] Reviewer, 哈尔滨工业大学学报

[95] Reviewer, 青岛大学学报

[96] Reviewer, 中国科技大学学报

[97] Reviewer, 大连理工大学学报

[98] Reviewer, 华南理工大学学报

[99] Reviewer, 西南交通大学学报

[100] Chair, 2013 IEEE Symposium on Computational Intelligence in Scheduling (IEEE-CISched 2013)

[101] Program Committee Member: 2013 IEEE Symposium on Differential Evolution (SDE 2013)

[102] Publicity Co-Chair: 2012 International Conference on Intelligent Computing (ICIC 2012)

[103] Program Committee Member: 2012 International Conference on Operations Research and Enterprise Systems (ICORES 2012)

[104] Program Committee Member: 2011 IEEE Symposium on Differential Evolution (SDE 2011)

[105] Program Committee Member: 2011 International Conference on Swarm Intelligence (ICSI 2011)

[106] Program Committee Member: 2011 International Conference on Intelligent Computing (ICIC 2011)

[107] Program Committee Member: 2011 International Conference on Artificial Intelligence and Soft Computing (ICAISC 2011)

[108] Program Committee Member: 2011 International Conference on Evolutionary Multi-Criterion Optimization (EMO 2011)

[109] Program Committee Member: 2010 International Conference on Swarm Intelligence (ICSI 2010)

[110] Program Committee Member: 2010 International Conference on Intelligent Computing (ICIC 2010)

[111] Program Committee Member: 2010 International Workshop on Advanced Computational Intelligence (IWACI2010)

[112] Program Committee Member: 2010 Conference on Genetic and Evolutionary Computing (ICGEC 2010)

[113] Program Committee Member: 2009 International Conference on Intelligent Computing (ICIC 2009)

[114] Program Committee Member: 2009 World Summit on Genetic and Evolutionary Computation (GEC 2009)