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Application of ACO in Continuous Domain

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Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4222))

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Abstract

The Ant Colony Optimization has gained great success in applications to combinatorial optimization problems, but few of them are proposed in the continuous domain. This paper proposes an ant algorithm, called Direct Ant Colony Optimization (DACO), for the function optimization problem in continuous domain. In DACO, artificial ants generate solutions according to a set of normal distribution, of which the characteristics are represented by pheromone modified by ants according to the previous search experience. Experimental results show the advantage of DACO over other ACO based algorithms for the function optimization problems of different characteristics.

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Author information

Authors and Affiliations

  1. Shanghai Jiaotong University, Shanghai, 200052, China

    Min Kong & Peng Tian

Authors
  1. Min Kong
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  2. Peng Tian
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Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

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

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., P.O. Box, 710071, Xi’an, P.R. China

    Xinbo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

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© 2006 Springer-Verlag Berlin Heidelberg

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Kong, M., Tian, P. (2006). Application of ACO in Continuous Domain. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_17

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  • DOI: https://doi.org/10.1007/11881223_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45907-1

  • Online ISBN: 978-3-540-45909-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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