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Recent Advances in Evolutionary Computation

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Abstract

Evolutionary computation has experienced a tremendous growth in the last decade in both theoretical analyses and industrial applications. Its scope has evolved beyond its original meaning of “biological evolution” toward a wide variety of nature inspired computational algorithms and techniques, including evolutionary, neural, ecological, social and economical computation, etc., in a unified framework. Many research topics in evolutionary computation nowadays are not necessarily “evolutionary”. This paper provides an overview of some recent advances in evolutionary computation that have been made in CERCIA at the University of Birmingham, UK. It covers a wide range of topics in optimization, learning and design using evolutionary approaches and techniques, and theoretical results in the computational time complexity of evolutionary algorithms. Some issues related to future development of evolutionary computation are also discussed.

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Authors and Affiliations

  1. Nature Inspired Computation and Applications Laboratory, The University of Science and Technology of China, Hefei, 230027, P.R. China

    Xin Yao

  2. The Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA) School of Computer Science, The University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

    Xin Yao & Yong Xu

Authors
  1. Xin Yao
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  2. Yong Xu
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Correspondence to Xin Yao.

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This work is partially supported by the National Natural Science Foundation of China (Grant No. 60428202), and the Advantage West Midlands, UK.

Xin Yao obtained his B.Sc. degree in 1982 from the University of Science and Technology of China (USTC) in Hefei, M.Sc. degree in 1985 from the North China Institute of Computing Technologies (NCI) in Beijing and Ph.D. degree in 1990 from USTC, all in computer science. He joined the University of Birmingham from Australia as a professor of computer science in 1999. He is a fellow of IEEE, the editor-in-chief of IEEE Transactions on Evolutionary Computation, an associate editor of several other international journals, and the editor of the book series on “Advances in Natural Computation” from World Scientific Publishing Co. He has been an invited keynote or plenary speaker of more than 35 international conferences in 11 different countries and a chair/co-chair of 27 international conferences. He is an IEEE Computational Intelligence Society Distinguished Lecturer. He won the prestigious IEEE Donald G. Fink Prize Paper Award (2001). He is currently the Director of The Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA) at the University of Birmingham, UK. He is also a Distinguished Visiting Professor and Cheung Kong Scholar at USTC and a visiting professor at three other universities. He has more than 200 research publications, including 80 refereed journal papers. His major research interests include evolutionary computation and neural network ensembles.

Yong Xu received the M.Sc. degree in applied optics and lasers from Fujian Normal University in 1987 and the Ph.D. degree in physics specializing in nature-inspired approaches to optical network design from Xiamen University in 2002. He is a member of IEEE and now a professor with Fujian Normal University and a research fellow with the University of Birmingham. From 2001 to 2002 he was a research assistant with the City University of Hong Kong. He is a reviewer for a number of leading international journals and international conferences and serves as a program committee member for many international conferences. He is an organizer of a workshop in PPSN04 and a guest editor of a special issue in International Journal of Computational Intelligence and Applications. He has published more than 50 papers and undertaken many research projects. His research interests include evolutionary computation, e.g., neural networks, genetic algorithms and tabu search etc., global optimization, and the optimal design of telecommunication networks.

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Yao, X., Xu, Y. Recent Advances in Evolutionary Computation. J Comput Sci Technol 21, 1–18 (2006). https://doi.org/10.1007/s11390-006-0001-4

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