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International Conference on ICT Innovations

ICT Innovations 2011: ICT Innovations 2011 pp 1–14Cite as

A Jumping Gene Evolutionary Approach for Multiobjective Optimization

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 150))

Abstract

The phenomenon of Jumping genes was initially discovered by Nobel Laureate, Barbara McClintock, in her work on maize chromosome in fifties. The Jumping genes transpose from one position to another in horizontal fashion within the same chromosome or even to other chromosomes. In this paper, it is to present how this genetic transposition, after transforming into a computational method, can enhance the evolutionary multiobjective optimization. The fundamental concept, design of operations, performance justification and applications of the Jumping Gene evolutionary approach will be outlined.

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Author information

Authors and Affiliations

  1. Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China

    Wallace K. S. Tang, Chris S. H. Yeung & K. F. Man

Authors
  1. Wallace K. S. Tang
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  2. Chris S. H. Yeung
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  3. K. F. Man
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Corresponding author

Correspondence to Wallace K. S. Tang .

Editor information

Editors and Affiliations

  1. Macedonian Academy of Sciences and Arts, Skopje, Macedonia

    Ljupco Kocarev

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Tang, W.K.S., Yeung, C.S.H., Man, K.F. (2012). A Jumping Gene Evolutionary Approach for Multiobjective Optimization. In: Kocarev, L. (eds) ICT Innovations 2011. ICT Innovations 2011. Advances in Intelligent and Soft Computing, vol 150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28664-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-28664-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28663-6

  • Online ISBN: 978-3-642-28664-3

  • eBook Packages: EngineeringEngineering (R0)

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