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SDE 2011 : 2011 IEEE Symposium on Differential Evolution | |||||||||||||||
Link: http://www.ieee-ssci.org/2011/sde-2011 | |||||||||||||||
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Call For Papers | |||||||||||||||
Part of IEEE Symposium Series on Computational Intelligence 2011
Differential Evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE is a very simple algorithm, requiring only a few lines of code in most of the existing programming languages. Additionally, it has very few control parameters, which makes it easy to use. Nonetheless, DE exhibits remarkable performance in optimizing a wide variety of optimization problems in terms of final accuracy, convergence speed, and robustness as evidenced by the consistently excellent performance in all of the CEC competitions (http://www.ntu.edu.sg/home/epnsugan). The last decade has witnessed a rapidly growing research interest in DE as demonstrated by the significant increase in the number of research publications on DE in the forms of monographs, edited volumes and archival articles. Although research on and with DE has reached an impressive state, there are still many open problems and new application areas are continually emerging for the algorithm. This Symposium aims at bringing researchers and users from academia and industry together to report, interact and review the latest progresses in this field, to explore future directions of research and to publicize DE to a wider audience from diverse fields joining the SSCI 2011 in France and beyond. Topics Authors are invited to submit their original and unpublished work in the areas including (but not limited to) the following: * Theoretical analysis of the search mechanism, convergence analysis, and complexity of DE. * Adaptation and tuning of the control parameters of DE. * Development of new vector perturbation techniques for DE. * Adaptive mixing of the perturbation techniques. * Balancing explorative and exploitative tendencies in DE and memetic DE. * DE for finding multiple global optima. * DE for optimization in uncertain environments. * DE for multi-objective and many-objective optimization. * Constraints handling with DE. * DE for high-dimensional and expensive optimization. * DE for multi-modal optimization * DE-variants for handling mixed-integer, discrete, and binary optimization problems. * Hybridization of DE with other search methods. * Applications of DE in any domain. Symposium Co-Chairs Dr. Janez Brest, Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ul. 17, 2000 Maribor, Slovenia Dr. Swagatam Das, Department of Electronics and Telecommunications Engineering, Jadavpur University, Calcutta – 700 032, India Dr. P.N. Suganthan, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798 Program Committee (tentative) M. M. Ali (South Africa) J. Arabas (Poland) B. V. Babu (India) B. Boskovic (Slovenia) L. T. Bui (Australia) Z. X. Cai (China) N. Chakraborti (India) U. Chakraborty (USA) L. d. S. Coelho (Brazil) C. A. Coello Coello (Mexico) D. Davendra (Czech Republic) A. P. Engelbrecht (South Africa) V. Feoktistov (France) H. Iba (Japan) J. Lampinen (Finland) X. D. Li (Australia) J. J. Liang (China) R. Mallipeddi (Singapore) E. Mezura Montes (Mexico) F. Neri (Finland) G. Onwubolu (Canada) Q. K. Pan (China) B. K. Panigrahi (India) K. V. Price (USA) A. K. Qin (China) A. Y. Qing (Singapore) S. Rahnamayan (Canada) T. Ray (Australia) J. Silc (Slovenia) R. Storn (Germany) K. Tang (China) F. M. Tasgetiren (Turkey), D. K. Tasoulis (UK) J. Tvrdik (Czech Republic) G. K. Venayagamoorthy (USA) L. Wang (China) S. X. Yang (UK) D. Zaharie (Romania) A. Zamuda (Slovenia) J. Zhang (USA) Q. Zhang (UK) |
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