Resume of Ling Wang (L

Resume of Dr. Ling WANG (L. WANG)

AFFILIATION

Professor, Dr. Ling WANG (王凌)

Department of Automation, Tsinghua University, Beijing 100084, P. R. China

Email:

Tel: 86-10-62783125-272, 62785845-272

Fax: 86-10-62786911

EXPERIENCE & EDUCATION

[1]Full Professor, Department of Automation, Tsinghua University, 2008.12~

[2]Visiting Scholar, Department of Industrial and Operations Engineering, University of Michigan, 2007.01-2008.01

[3]Associate Professor, Department of Automation, Tsinghua University, 2002.12~2008.11

[4]Assistant Professor, Department of Automation, Tsinghua University, 1999.10~2002.11

[5]Ph.D. student in Department of Automation, Tsinghua University, 1995~1999

[6]B.S. student in Department of Automation, Tsinghua University, 1990~1995

[7]Birth Date and Place: 1972-08-03, Wujin City of Jiangsu Province

RESEARCH INTEREST

[1]Modeling, planning, scheduling and optimization of manufacturing systems

[2]Optimization theory, algorithms and applications based on computational intelligence, including genetic algorithm, simulated annealing, tabu search, particle swarm optimization, differential evolution, neural networks, quantum computing, etc

[3]Simulation optimization, ordinal optimization

CURRICULUM

[1]Intelligent optimization algorithms and applications. (for undergraduate students)

[2]Principles of Automatic Control. (for undergraduate students)

[3]Production scheduling and intelligent optimizations. (for graduate students)

[4]Neural networks. (for graduate students)

[5]Literatures retrieving and paper writing. (for graduate students)

STUDENT

Ph.D. STUDENT

Ling-Lai LI (’2001)

Yi-Nan GUO (’2001)

Bo LIU (’2001)

Bin QIAN (’2004)

Ye XU (’2009)

MS STUDENT

Liang ZHANG (’2002) [Excellent Thesis Award]

Hui PAN (’2003)

Bin-Bin LI (’2004) [Excellent Thesis Award]

Qie HE (’2005) [Excellent Thesis Award]

Fu-Zhuo HUANG (’2006)

Ling-PO LI (’2007)

ENGINEERING MS STUDENT

Yi LU (’2003)

Yi-Xi SONG (’2008)

UNDERGRADUATE STUDENT

Wen-Feng LI, Ming YAN (’2000)

Ling-Lai LI, Wei-Rong ZHU (’2001)

Liang ZHANG, Wei ZHOU (’2002)

Li-Jun JI, Xuan HUANG (’2003)

Bin-Bin LI, Hao WU (’2004)

Qie HE (’2005)

Fu-Zhuo HUANG, Yu ZHOU (’2006)

Bin ZOU (’2008)

Ye XU (’2009)

PROJECT

[1]NSFC Project (70871065): Study on learning-based swarm intelligent scheduling theory and algorithms. (250,000RMB, PI) (2009.1~2011.12)

[2]NSFC Project (60774082): Optimization and scheduling theory and algorithms based on differential evolution and quantum evolution for complex manufacturing systems. (270,000RMB, PI) (2008.1~2010.12)

[3]NSFC Project (60374060): Study on intelligent simulation optimization theory and algorithms for complex manufacturing systems. (150,000RMB, PI) (2004.1~2006.12)

[4]NSFC Project (60204008): Computational intelligence based hybrid optimization theory and algorithms for complex systems. (200,000RMB, PI) (2003.1~2005.12)

[5]NSFC Project (60834004):Research on theories and algorithms of real-time scheduling and optimization control for complex manufacturing process of chips and their applications. (2,000,000RMB, Investigator) (2009.1~2012.12)

[6]NSFC Project (60574072): Study on optimization and scheduling theory and algorithms based on PSO for complex manufacturing process. (230,000RMB) (2006.1~2008.12)

[7]NSFC Project (60174022): Study on several key problems about robust control modeling. (50,000RMB, Investigator) (2002.1~2002.12)

[8]NSFC Project (69684001): Control and optimization theory and methods for a class of hybrid dynamic systems. (149,000RMB, Investigator) (1997.1~1999.12)

[9]New Star of Science and Technology of Beijing City (2004A41). (70,000RMB, PI) (2004.7~2007.7)

[10]The Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry: Study on optimization and scheduling based on hybrid differential evolution. (20,000RMB, PI) (2009.1~2010.12)

[11]973 Sub-Project (2002CB312203): Study on real-time, intelligent operation and optimization theories and methods for complex manufacturing process. (340,000RMB, Investigator) (2002.12~2008.5)

[12]973 Sub-Project (G1998020310): Hybrid electrical systems. (Personal funding 20,000RMB, Investigator) (1998.12~2003.5)

[13]863 Project (2007AA04Z155): Intelligent planning and dynamic optimization & scheduling technologies for manufacturing processes in process industrial enterprises. (710,000RMB, Co-PI) (2008.1~2009.12)

[14]863 Project (2001AA411220): Overall plan and key technology for Chinese petrochemical automatic systems. (Personal funding 39,000RMB, Investigator) (2001.12~2002.11)

[15]863 Project (863-511-930): Management mode and integration technology for process CIMS industries. (Personal funding 70,000RMB, Investigator) (2001.1~2001.12)

[16]863 Project: CIMS for Dalian petrochemical company. (Personal funding 20,000RMB, Investigator) (1999.10~2000.3)

[17]Key Member Program of Tsinghua University: Study on hybrid optimization algorithms. (Personal funding 60,000RMB) (2000.6~2002.5)

[18]985 Project: Theory, methods and technologies of system integration for 21 century oriented process industries. (Personal funding 10,000RMB, Investigator) (2001~2002)

[19]Teaching and Paper Foundation. (90,000RMB, PI) (2002~2004)

[20]International Cooperation Project: Effective simulation and optimization for service network. (65,000RMB for me, Investigator) (2002.4~2004.4)

[21]Company Cooperation Project: Development of HIS. (50,000RMB, Co-PI) (2001.5~2001.12)

AWARD

[1]2003’ National Natural Science Award (1st Place Prize) nominated by Ministry of Education of China.

[2]2007’ Natural Science Award (2nd Place Prize) by MOE of China.

[3]Outstanding Ph.D. Dissertation Award of Tsinghua University (1st Place Prize).

[4]2002’Outstanding Paper Award of IEEE International Conference on Machine Learning and Cybernetics, IEEE-ICMLC’02.

[5]2006’ Excellent Paper of IET International Conference on Informatics and Control Technologies, IET-ICT’06.

[6]2004’Excellent Paper of Chinese Control and Decision Conference, CDC'04.

[7]2004’New Star of Science and Technology of Beijing City.

[8]2004’ Excellent Textbook of Tsinghua University (2nd Place Prize).

[9]2008’ Excellent Textbook of Tsinghua University (2nd Place Prize).

[10]2002’Excellent Textbook in 11th Textbook Festival of Tsinghua University Press (1st Place Prize).

[11]The AcademicKeys Who's Who in Engineering Higher Education (WWEHE)

[12]2004’Excellent Class Advisor of Tsinghua University (1st Place Prize).

[13]2005’Excellent Class Advisor of Tsinghua University (1st Place Prize).

DISSERTATION

[1]Ph. D. Dissertation: Study on some problems for hybrid optimization strategies and neural networks, 1999.

[2]M.S. Dissertation: Stochastic optimization algorithms and their hybrid strategies, 1997.

[3]B.S. Dissertation: Optimization problem on route of 1/N custom stream, 1995.

PUBLICATIONS

[Till 2008-9-1, SCI Times Cited 451, Google Scholar Times Cited > 2000, CNKI Times Cited > 3500]

BOOK:

[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]Wang L, Liu B. Particle swarm optimization and scheduling algorithms. Beijing: Tsinghua University Press, 2008

[3]Wang JC, Wang L, Jin YH (Translation). Process dynamics and control (2nd edition). Beijing: Publishing House of Electronics Industry, 2006

[4]Wang L. Heuristic optimization method. In: Chinese Encyclopedia, 2nd ed. Beijing: Chinese Encyclopedia Press, 2004

[5]Wang L. Shop scheduling with genetic algorithms. Beijing: Tsinghua University & Springer Press, 2003. (SCI Times Cited 23, Google Scholar Times Cited > 200, CNKI Times Cited > 350)

[6]Wang L. Intelligent optimization algorithms with applications. Beijing: Tsinghua University & Springer Press, 2001.10(First), 2003.03(Second), 2004.03(Third), 2004.11(Fourth). (SCI Times Cited 42, Google Scholar Times Cited > 900, CNKI Times Cited 1700)

INTERNATIONAL JOURNAL PAPER:

Forthcoming

[1]Qian B, Wang L, Hu R, Huang DX, Wang X. A DE-based approach to no-wait flow-shop scheduling. Computers & Industrial Engineering. (SCI, EI)

[2]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.(SCI, EI)

2009

[3]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, EI)

[4]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)

[5]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)

[6]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)

[7]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 2)

2008

[8]Li BB, Wang L, Liu B. An effectivePSO-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)

[9]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)

[10]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 2)

[11]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 2)

[12]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 2)

[13]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)

[14]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 1)

[15]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. (EI-081511199136)

[16]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 1)

[17]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 1)

2007

[18]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 8)

[19]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 10)

[20]He Q, Wang L, Liu B. Parameter estimation for chaotic systems by particle swarmoptimization. Chaos, Solitons and Fractals, 2007, 34(2): 654-661. (SCI-175OE, EI-071610552661, SCI Times Cited 3)

[21]Liu B, Wang L, Jin YH, Huang DX, Tang F. 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 3)

[22]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)

[23]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 9)

[24]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 5)

[25]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 9)

[26]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 14)

2006

[27]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 9)

[28]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 1)

[29]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 4)

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

[31]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 5)

[32]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 2)

[33]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 2)

2005

[34]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 9)

[35]Wang L. Ahybrid genetic algorithm-neural network strategy for simulation optimization. Applied Mathematics and Computation, 2005, 170(2): 1329-1343. (SCI-980YQ, EI-05449448565, SCI Times Cited 6)

[36]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 3)

[37]Tang F, Wang L. An adaptive active control for the modified Chua’s circuit. Physics Letters A, 2005, 346(5-60: 342-346. (SCI-979HD, SCI Times Cited 14)

[38]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 40)

[39]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 1)

[40]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 7)

2004

[41]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)

[42]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 6)

2003

[43]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 16)

[44]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 12)

[45]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 46)

[46]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)

2002

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

[48]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 11)

[49]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 5)

2001

[50]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 55)

INTERNATIONAL CONFERENCE PAPER:

2009

[1]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, Shanghai, GEC’2009.

2008

[2]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.

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

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

[5]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. (EI-084611709838, ISTP-BIW46)

2007

[6]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. (EI-080311036869, ISTP-BGH87)

[7]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. (EI-080311036970, ISTP-BGH87)

2006

[8]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)

[9]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 1)

[10]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)

[11]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)

[12]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)

[13]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.

[14]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. Dynamicsof Continuous Discrete and Impulsive Systems-Series B-Applications & Algorithms, 2006, 13E: 1757-1761. (ISTP-201OS)

2005

[15]Liu B, Wang L, JinYH. 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 1)

[16]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 1)

[17]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 2)

[18]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 6)

2004

[19]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)

[20]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)

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

2003

[22]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)