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International Conference on Computational and Information Science

CIS 2005: Computational Intelligence and Security pp 230–237Cite as

Model and Convergence for the Combination of Genetic Algorithm and Ant Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

Abstract

Although genetic algorithm (GA) has the ability to do quick and stochastic global search, it can’t efficiently use the output information for systems. Ant algorithm (AA), on the other hand, is a parallel-proceed and distributive-forward system with a relatively slow speed for carrying out its solution. Incorporating GA and AA can improve their merits one for another. In this paper, the model and the method from the combination of GA and AA are proposed. The convergence of the method based on the Markov theory is analyzed. The experiment and analysis are conducted on the NP-hard problems for the cases of TSP30 (Travel Salesman Problem 30 cities) and CHN144 (China 144 cities). This work proves that the satisfactory solution sequence is monotonically decreasing and convergent. The results of simulations show that not only this combined algorithm is a step-by-step convergent process, but also its speed and effect of solving are quite satisfactory.

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References

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Author information

Authors and Affiliations

  1. Institute of Systems Engineering, Tianjin University, Tianjin, 300072, China

    Jianli Ding, Wansheng Tang & Yufu Ning

  2. Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin, 300300, China

    Jianli Ding

  3. Department of Computer Science, Dezhou University, Dezhou, 253023, China

    Yufu Ning

Authors
  1. Jianli Ding
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  2. Wansheng Tang
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  3. Yufu Ning
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Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yuping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

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

    Hujun Yin

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

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security (Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Ding, J., Tang, W., Ning, Y. (2005). Model and Convergence for the Combination of Genetic Algorithm and Ant Algorithm. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_33

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  • DOI: https://doi.org/10.1007/11596448_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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