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A Theoretical Model and Convergence Analysis of Memetic Evolutionary Algorithms

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3611))

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Abstract

Memetic evolutionary algorithms (MEAs) combine the global search of evolutionary learning methods and the fine-tune ability of local search methods so that they are orders of magnitude more accurate than traditional evolutionary algorithms in many problem domains. However, little work has been done on the mathematical model and convergence analysis of MEAs. In this paper, a theoretical model as well as the convergence analysis of a class of gradient-based MEAs is presented. The results of this paper are extensions of the research work on the abstract model and convergence analysis of general evolutionary algorithms. By modeling the local search of gradient methods as an abstract strong evolution operator, the theoretical framework for abstract memetic evolutionary algorithms is derived. Moreover, the global convergence theorems and the convergence rate estimations of gradient-based MEAs are also established.

Supported by the National Natural Science Foundation of China Under Grant 60303012, 60234030, Chinese Post-Doctor Science Foundation under Grant 200403500202, and A Project Supported by Scientific Research Fund of Hunan Provincial Education Department.

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Author information

Authors and Affiliations

  1. Institute of Automation, National University of Defense Technology, 410073, Changsha, P.R. China

    Xin Xu & Han-gen He

  2. School of Computer, National University of Defense Technology, 410073, Changsha, P.R. China

    Xin Xu

Authors
  1. Xin Xu
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  2. Han-gen He
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Xu, X., He, Hg. (2005). A Theoretical Model and Convergence Analysis of Memetic Evolutionary Algorithms. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_142

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  • DOI: https://doi.org/10.1007/11539117_142

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28325-6

  • Online ISBN: 978-3-540-31858-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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