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ACO with Fuzzy Pheromone Laying Mechanism

  • Conference paper
Emerging Intelligent Computing Technology and Applications (ICIC 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 304))

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Abstract

Pheromone laying mechanism is an important aspect to affect performance of ant colony optimization (ACO) algorithms. In most existing ACO algorithms, either only one best ant is allowed to release pheromone, or all the ants are allowed to lay pheromone in the same way. To make full use of ants to explore high quality routes, a fuzzy pheromone laying mechanism is proposed in the paper. The amount of ants that are allowed to lay pheromone varies at each iteration to differentiate different contributions of the ants. The experimental results show that the proposed algorithm possesses high searching ability and excellent convergence performance in comparison with the classic ACO algorithm.

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Author information

Authors and Affiliations

  1. School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191, China

    Liu Yu, Guang-Rong Yan & Lei Yi

  2. School of Computer Science & Technology, Soochow University, Soochow, 215006, China

    Jian-Feng Yan

Authors
  1. Liu Yu
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  2. Jian-Feng Yan
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  3. Guang-Rong Yan
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  4. Lei Yi
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Editor information

Editors and Affiliations

  1. Machine Learning and Systems Biology Laboratory, School of Electronics and Information Engineering, Tongji University, Shanghai, China

    De-Shuang Huang

  2. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  3. Department of Chemistry, University of Louisville, 2320 South Brook Street, 40292, Louisville, Kentucky, USA

    Xiang Zhang

  4. School of Electrical, Computer & Telecommunications Engineering, The University of Wollongong,, 2522, North Wollongong, NSW, Australia

    Prashan Premaratne

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© 2012 Springer-Verlag Berlin Heidelberg

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Yu, L., Yan, JF., Yan, GR., Yi, L. (2012). ACO with Fuzzy Pheromone Laying Mechanism. In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_16

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  • DOI: https://doi.org/10.1007/978-3-642-31837-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31836-8

  • Online ISBN: 978-3-642-31837-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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