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Using Viruses to Improve GAs

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3612))

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Abstract

In this paper, we will introduce an evolutionary algorithm for finding approximate solutions to the Weighted Minimum Hitting Set Problem. The proposed genetic algorithm, denoted by HEAT-V, makes use of a newly defined concept of virus. We will test its performance against a well known and efficient greedy algorithm, and on several families of sets.

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Author information

Authors and Affiliations

  1. Faculty of Pharmacy and Dept. of Mathematics & Computer Science, University of Catania, Italy

    Francesco Pappalardo

Authors
  1. Francesco Pappalardo
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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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Pappalardo, F. (2005). Using Viruses to Improve GAs. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_19

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  • DOI: https://doi.org/10.1007/11539902_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28320-1

  • Online ISBN: 978-3-540-31863-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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