Welcome to Dr. Ling WANG's Home Page

 
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Professor, Dr. Ling WANG (王凌)
Department of Automation, Tsinghua University, Beijing 100084, P. R. China

Email: wangling@mail.tsinghua.edu.cn
Tel: 86-10-62783125-272, 62785845-272
Fax: 86-10-62786911

Google Citations: http://scholar.google.com.sg/citations?user=lC7bVMwAAAAJ&hl=en

Last Update: 2015/04/16                           中文版

You are the Description: C:\images\counter.php?counter=counter_wanglingvisitor to my homepage since 08/30/2005.


EXPERIENCE & EDUCATION

RESEARCH INTEREST

CURRICULUM

STUDENT

PROJECT

AWARD

DISSERTATION

PUBLICATIONS

ACADEMIC

 


 

 

l        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

 

l        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, estimation of distribution algorithm, harmony search, artificial bee colony, shuffled frog leaping, neural networks, immune algorithm, quantum computing, teaching-learning-based optimization, etc

[3]      Simulation optimization, ordinal optimization

 

l        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]      Literature retrieving and paper writing. (for engineering graduate students)

 

l        STUDENT

Ph.D. STUDENT

Ling-Lai LI (’2001)

Yi-Nan GUO (’2001)

Bo LIU (’2001)

Bin QIAN (’2004) [Excellent Ph.D. Thesis of Tsinghua University]

Chen FANG (’2008)

Ye XU (’2009)

Sheng-Yao WANG (’2010)

Xiao-Long ZHENG (’2011)

Jing-Nan SHEN (’2012)

Chu-Ge WU (’2015)

 

MS STUDENT

Liang ZHANG (’2002) [Excellent M.S. Thesis of Tsinghua University]

Hui PAN (’2003)

Bin-Bin LI (’2004) [Excellent M.S. Thesis of Tsinghua University]

Qie HE (’2005) [Excellent M.S. Thesis of Tsinghua University]

Fu-Zhuo HUANG (’2006)

Ling-PO LI (’2007) [Excellent M.S. Thesis of Tsinghua University]

Gang ZHOU (’2009) [Excellent M.S. Thesis of Tsinghua University]

Peng ZHANG (’2010)

Huan-Yu ZHENG (’2012)

Jin DENG (’2013)

Jing-Jing WANG (’2015)

 

ENGINEERING MS STUDENT

Yi LU (’2003)

Liang MA (’2006)

 

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) [Excellent B.S. Thesis of Tsinghua University]

Fu-Zhuo HUANG, Yu ZHOU (’2006)

Bin ZOU (’2008)

Ye XU (’2009)

Sheng-Yao WANG (’2010) [Excellent B.S. Thesis of Tsinghua University]

Xue-Ting FAN (’2010)

Xiao-Long ZHENG, Xiang ZHONG (’2011)

Jing-Nan SHEN (’2012)

Huan-Yu ZHENG (’2012) [Excellent B.S. Thesis of Tsinghua University]

Chu-Ge WU, Jing-Jing WANG (’2015)

l        PROJECT

[1]      NSFC Project (61174189): Study on complex resource constrained project scheduling problems and memetic algorithms. (590,000RMB, PI) (2012.1~2015.12)

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

[3]     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)

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

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

[6]     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)

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

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

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

[10] Program for New Century Excellent Talents in University (NCET-10-0505). (500,000RMB, PI) (2010.1~2012.12)

[11] Doctoral Program Foundation of Institutions of Higher Education of China (20130002110057): Study on distributed shop scheduling based on cooperative estimation of distribution algorithms. (120,000RMB, PI) (2014.1~2016.12)

[12] Doctoral Program Foundation of Institutions of Higher Education of China (20100002110014): Study on resource constrained project scheduling based on novel hybrid swarm intelligence. (60,000RMB, PI) (2011.1~2013.12)

[13] Young Talent of Science and Technology of Beijing City ( 2004A 41). (70,000RMB, PI) (2004.7~2007.7)

[14] 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)

[15] National Science and Technology Major Project of China (2011ZX02504-008)Study on intelligent scheduling and quality optimization techniques for integrated circuits manufacturing line. (5,200,000RMB, Investigator) (2011.1~2013.12)

[16] 973 Sub-project (2013CB329503)Brain information based encoding and decoding oriented machine learning approaches. (2,360,000RMB, Investigator) (2013.01~2017.12)

[17] 973 Sub-Project (2009CB320602)Study on real time intelligent operation optimization theory and methods based on data and knowledge for complex manufacturing total process. (3,080,000RMB, Investigator) (2011.01~2013.08)

[18] 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)

[19] 973 Sub-Project (G1998020310): Hybrid electrical systems. (Personal funding 20,000RMB, Investigator) (1998.12~2003.5)

[20] 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)

[21] 863 Project (2001AA411220): Overall plan and key technology for Chinese petrochemical automatic systems. (Personal funding 39,000RMB, Investigator) (2001.12~2002.11)

[22] 863 Project (863-511-930): Management mode and integration technology for process CIMS industries. (Personal funding 70,000RMB, Investigator) (2001.1~2001.12)

[23] 863 Project: CIMS for Dalian petrochemical company. (Personal funding 20,000RMB, Investigator) (1999.10~2000.3)

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

[25] 985 Project: Theory, methods and technologies of system integration for 21 century oriented process industries. (Personal funding 10,000RMB, Investigator) (2001~2002)

[26] Academic Young Talent of Tsinghua University and Teaching & Paper Foundation. (250,000RMB, PI) (2002~2011)

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

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

     AWARD

[1]     2009’ Program for New Century Excellent Talents in University.

[2]     2009’ Academic Young Talent of Tsinghua University .

[3]     2004’ Young Talent of Science and Technology of Beijing City .

[4]     2010’ SCOPUS Young Researcher New Star Scientist Award .

[5]     2014’ National Natural Science Award ( 2nd Place Prize) .

[6]     2011’ Electronics and Information Science and Technology Award ( 2nd Place Prize) by Chinese Institute of Electronics.

[7]     2008’ Science and Technology Award ( 3rd Place Prize) by Beijing City .

[8]     2007’ Natural Science Award ( 2nd Place Prize) by MOE of China .

[9]     2003’ National Natural Science Award ( 1st Place Prize) nominated by Ministry of Education of China .

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

[11] 2005-2010 Engineering Applications of Artificial Intelligence Top Cited Article Awarded by Elsevier.

[12] 2010-2012 Computers & Chemical Engineering Most Cited Articles Awarded by Elsevier.

[13] 2008-2012 Computers & Operations Research Most Cited Articles by Elsevier.

[14] 2009-2013 Computers & Operations Research Most Cited Articles by Elsevier.

[15] 2014’ Best Paper Award of ACTA Automatica Sinica.

[16] 2013’ Best Paper Award of The 3rd International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII’2013.

[17] 2011’ Best Paper Award of the Seventh International Conference on Intelligent Computing, ICIC’2011.

[18] 2006’ Excellent Paper of IET International Conference on Informatics and Control Technologies, IET-ICT’2006.

[19] 2002’ Outstanding Paper Award of IEEE International Conference on Machine Learning and Cybernetics, IEEE-ICMLC’2002.

[20] 2014’ Poster Paper Award of The 25th Chinese Process Control Conference, CPCC’2014.

[21] 2010’ Finalist for Zhang Si-Ying Outstanding Youth Paper Award, CCDC’2010.

[22] 2004’ Excellent Paper of Chinese Control and Decision Conference, CCDC’2004.

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

[24] 2012’ Excellent Textbook of Tsinghua University ( 2nd Place Prize).

[25] 2008’ Excellent Textbook of Tsinghua University ( 2nd Place Prize).

[26] 2004’ Excellent Textbook of Tsinghua University ( 2nd Place Prize).

[27] 2002’ Excellent Textbook in 11th Textbook Festival of Tsinghua University Press ( 1st Place Prize).

[28] 2014’ Outstanding Professor and Mentor of Tsinghua University .

[29] 2005’ Outstanding Mentor Award of Tsinghua University ( 1st Place Prize).

[30] 2004’ Outstanding Mentor Award of Tsinghua University ( 1st Place Prize).

l        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 2015-01-01 , SCI Times Cited 2324, h index=28, Google Scholar Times Cited > 15000, Google-h index=45, CNKI Times Cited > 6000]

BOOK:

[1]     Wang L, Qian B. Hybrid differential evolution and scheduling algorithms. Beijing: Tsinghua University Press, 2012. (SCI Times Cited 1)

[2]     Wang L, Liu B. Particle swarm optimization and scheduling algorithms. Beijing: Tsinghua University Press, 2008(First), 2011(Second). (SCI Times Cited 10)

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

[4]     Wang L. Shop scheduling with genetic algorithms. Beijing: Tsinghua University & Springer Press, 2003. (SCI Times Cited 45, Google Scholar Times Cited > 300, CNKI Times Cited > 800)

[5]     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 75, Google Scholar Times Cited > 1000, CNKI Times Cited > 2800)

[6]     Huang DS, Jo KH, Wang L. (Eds.) Intelligent computing methodologies. Lecture Notes in Artificial Intelligence, LNAI 8589, Springer, 2014. (EI-20143117998828)

[7]     Huang DS, Gupta P, Wang L, Gromiha M. (Eds.) Emerging intelligent computing technology and applications. Communications in Computer and Information Science, CCIS 375, Springer, 2013. (EI-20142317788122)

[8]     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. (SCI Times Cited 2)

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

 

INTERNATIONAL JOURNAL PAPER:

Ø  Forthcoming

[1]     Wang SY, Wang L, Liu M, Xu Y. 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. (Regular Paper). (SCI, EI)

[2]     Zheng HY, Wang L. Reduction of carbon emissions and project makespan by a Pareto-based estimation of distribution algorithm. International Journal of Production Economics. (SCI, EI)

[3]     Zheng XL, Wang L. A multi-agent optimization algorithm for resource constrained project scheduling problem. Expert Systems with Applications. (SCI, EI)

[4]     Fang C, Kolisch R, Wang L, Mu CD. An estimation of distribution algorithm and new computational results for the stochastic resource-constrained project scheduling problem. Flexible Services and Manufacturing Journal. (SCI, EI-20150400453608)

[5]     Wang SY, Wang L, Liu M, Xu Y. A hybrid estimation of distribution algorithm for the semiconductor final testing scheduling problem. Journal of Intelligent Manufacturing. (SCI, EI-IP52728671)

[6]     Wang SY, Wang L. A knowledge-based multi-agent evolutionary algorithm for semiconductor final testing scheduling problem. Knowledge-Based Systems. (SCI, EI)

[7]     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. (SCI-CA1LP, EI-201446180283)

[8]     Shen JN, Wang L, Wang SY. A bi-population EDA for solving the no-idle permutation flow-shop scheduling problem with the total tardiness criterion. Knowledge-Based Systems, 2015, 74: 167-175. (SCI-AZ9UE, EI)

[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. (SCI-AU4HI, EI-201436032760)

[10]     Xu Y, Wang L, Wang SY, Liu M. An effective teaching-learning-based optimization algorithm for the flexible job-shop scheduling problem with fuzzy processing time. Neurocomputing, 2015, 148: 260-268. (SCI-AR8QP, EI-201436023900, SCI Times Cited 1)

[11]     Li K, McLoone S, Wang L. Intelligent computing for sustainable energy and environment (ICSEE 2012). Neurocomputing, 2015, 148: 198-199. (SCI-AR8QP, EI-201436020034)

[12]     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. (SCI-AW7GI, EI-20145100351565)

 

Ø  2014

[13]     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. (SCI-AH4EB, EI-20142117747646)

[14]     Xu Y, Wang L, Wang SY, Liu M. An effective hybrid immune algorithm for solving the distributed permutation flow-shop scheduling problem. Engineering Optimization, 2014, 46(9): 1269-1283. (SCI-AH1AL, EI-20142117747906)

[15]     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. (SCI-AD4PF, SCI Times Cited 3, ESI Highly Cited Article)

[16]     Zheng XL, Wang L, Wang SY. A novel fruit fly optimization algorithm for the semiconductor final testing scheduling problem. Knowledge-Based Systems, 2014, 57: 95-103. (SCI-AB4SX, EI-20140617277481, SCI Times Cited 2)

[17]     Wang L, Fang C, Suganthan PN, Liu M. Solving system-level synthesis problem by a multi-objective estimation of distribution algorithm. Expert Systems with Applications, 2014, 41(5): 2496-2513. (SCI-302JM, EI-20135117098362)

 

Ø  2013

[18]     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). (SCI-186EY, EI-20133216578775)

[19] Xu Y, Wang L, Wang SY, Liu M. An effective shuffled frog-leaping algorithm for solving the hybrid flow-shop scheduling problem with identical parallel machines. Engineering Optimization, 2013, 45(12): 1409-1430. (SCI-233XJ, EI-20134416908346)

[20] Wang SY, Wang L, Liu M, Xu Y. An enhanced estimation of distribution algorithm for solving hybrid flow-shop scheduling problem with identical parallel machines. International Journal of Advanced Manufacturing Technology, 2013, 68(9-12): 2043-2056. (SCI-229KD, EI-20134717007366, SCI Times Cited 1)

[21] Xu Y, Wang L, Liu M, Wang SY. An effective shuffled frog-leaping algorithm for hybrid flow-shop scheduling with multiprocessor tasks. International Journal of Advanced Manufacturing Technology, 2013, 68(5-8): 1529-1537. (SCI-216IU, EI-20134917041493)

[22] 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. (SCI-205UO, EI-20133216578924, SCI Times Cited 2)

[23] 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). (SCI-176XD, EI-20140417226823)

[24] Wang SY, Wang L, Xu Y, Liu M. An effective estimation of distribution algorithm for the flexible job-shop scheduling problem with fuzzy processing time. International Journal of Production Research, 2013, 51(12): 3778-3793. (SCI-171II, EI-20133016525433, SCI Times Cited 2)

[25] 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. (SCI-171II, EI-20133016525421)

[26] 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. (SCI-171II, EI-20133016525420, SCI Times Cited 5)

[27] Xu Y, Wang L, Wang SY, Liu M. An effective immune algorithm based on novel dispatching rules for the flexible flow-shop scheduling problem with multiprocessor tasks. International Journal of Advanced Manufacturing Technology, 2013, 67(1-4): 121-135. (SCI-173XX, EI-20134917041668)

[28] 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. (SCI-170ZF, EI-20132316401595, SCI Times Cited 2)

[29] 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). (SCI-172IF, EI-20131616210165, SCI Times Cited 4)

[30] Wang L, Li LP. An effective differential harmony search algorithm for solving non-convex economic load dispatch problems. International Journal of Electrical Power and Energy Systems, 2013, 44(1): 832-843. (SCI-047TQ, EI-20124615670357, SCI Times Cited 8)

 

Ø  2012

[31] 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-929UZ, EI-20121314895267, SCI Times Cited 11)

[32] 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, 2012, 60(9-12): 1111-1123. (SCI-949YI, EI-20122315091899, SCI Times Cited 6)

[33] 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, 2012, 60(1-4): 303-315. (SCI-920LX, EI-20121514942599, SCI Times Cited 12)

[34] 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, 2012, 59(9-12): 1113-1125. (SCI-916KV, EI-20124015502257, SCI Times Cited 4)

[35] 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-911TV, EI-20120514733885)

[36] 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-903XF, EI-20120314701282, SCI Times Cited 5)

[37] 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-903XF, EI-20120314701225, SCI Times Cited 6)

[38] 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-903XF, EI-20120314701182, SCI Times Cited 6)

[39] 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, SCI Times Cited 2)

[40] 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, SCI Times Cited 2)

[41] 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, SCI Times Cited 9)

[42] 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, SCI Times Cited 9)

[43] 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, SCI Times Cited 15, ESI Highly Cited Article)

 

Ø  2011

[44] Wang L, Li LP. Fixed-structure H8 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 7)

[45] 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 6)

[46] 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, SCI Times Cited 3)

[47] 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, SCI Times Cited 8)

[48] 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, SCI Times Cited 7)

[49] 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)

[50] 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 9)

[51] 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, SCI Times Cited 2)

[52] 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 6)

[53] 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 5)

[54] 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 11)

[55] 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, SCI Times Cited 11)

[56] 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 20, 2009-2013 COR Most Cited Articles by Elsevier)

 

Ø  2010

[57] 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 15)

[58] 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 6)

[59] 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, SCI Times Cited 10)

[60] 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 10, CACE Most Cited Articles 2010-2012 Awarded by Elsevier)

[61] 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 5)

[62] 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 31, 2008-2012 & 2009-2013 COR Most Cited Articles by Elsevier)

 

Ø  2009

[63] 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 15)

[64] 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 24)

[65] 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 5)

[66] 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 28, 2008-2012 & 2009-2013 COR Most Cited Articles by Elsevier)

[67] 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 14)

[68] 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 34, 2009-2013 COR Most Cited Articles by Elsevier)

 

Ø  2008

[69] 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 18)

[70] 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 13)

[71] 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 15)

[72] 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 18)

[73] 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 14)

[74] 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, SCI Times Cited 3)

[75] 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 38, 2008-2012 COR Most Cited Articles by Elsevier)

[76] 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 16)

[77] 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 23)

[78] 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 11)

 

Ø  2007

[79] 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 43)

[80] 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 74, ESI Highly Cited Article)

[81] 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 42)

[82] 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 17)

[83] 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)

[84] 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 59, ESI Highly Cited Article)

[85] 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 55, ESI Highly Cited Article)

[86] 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 41)

[87] 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 99, ESI Highly Cited Article, EAAI Top Cited Article 2005-2010 Awarded by Elsevier)

 

Ø  2006

[88] 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 47)

[89] 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 20)

[90] 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 18)

[91] 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)

[92] 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 19)

[93] 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)

[94] 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)

 

Ø  2005

[95] 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 28)

[96] 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 25)

[97] 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)

[98] 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 25)

[99] 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 177, ESI Highly Cited Article)

[100] 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 3)

[101]  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 13)

 

Ø  2004

[102] 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)

[103] 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 10)

 

Ø  2003

[104] 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)

[105] 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 13)

[106] 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 79)

[107] 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)

 

Ø  2002

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

[109] 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 22)

[110] 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)

 

Ø  2001

[111] 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 96)

 

 

INTERNATIONAL CONFERENCE PAPER:

Ø  2014