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A New Optimization Algorithm Based on Ant Colony System with Density Control Strategy

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3971))

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Abstract

A new optimization algorithm based on the ant colony system is presented by adopting the density control strategy to guarantee the performance of the algorithm. In each iteration of the algorithm, the solutions are selected to have mutation operations according to the quality and distribution of the solution. Experimental results on the traveling salesman problem show that our algorithm can not only get diversified solutions and higher convergence speed than the Neural Network Model and traditional ant colony algorithm, but also avoid the stagnation and premature problem.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, Nanjing University of Aeronautics and Astronautics, 210093, Nanjing, China

    Ling Qin, Ling Chen & Yuan Yao

  2. Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, 63130-4899, USA

    Yixin Chen

  3. Department of Computer Science, Yangzhou University, 225009, Yangzhou, China

    Ling Qin & Ling Chen

Authors
  1. Ling Qin
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  2. Yixin Chen
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  3. Ling Chen
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  4. Yuan Yao
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Qin, L., Chen, Y., Chen, L., Yao, Y. (2006). A New Optimization Algorithm Based on Ant Colony System with Density Control Strategy. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759966_58

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  • DOI: https://doi.org/10.1007/11759966_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34439-1

  • Online ISBN: 978-3-540-34440-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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