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Adaptive Parallel Ant Colony Algorithm

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3611))

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Abstract

An adaptive parallel ant colony optimization is presented by improving the critical factor influencing the performance of the parallel algorithm. We propose two different strategies for information exchange between processors: selection based on sorting and on difference, which make each processor choose another processor to communicate and update the pheromone adaptively. In order to increase the ability of search and avoid early convergence, we also propose a method of adjusting the time interval of information exchange adaptively according to the diversity of the solutions. These techniques are applied to the traveling salesman problem on the massive parallel processors (MPP) Dawn 2000. Experimental results show that our algorithm has high convergence speed, high speedup and efficiency.

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Author information

Authors and Affiliations

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

    Ling Chen & Chunfang Zhang

  2. National Key Lab of Novel Software Tech, Nanjing University, 210093, Nanjing, China

    Ling Chen

Authors
  1. Ling Chen
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  2. Chunfang Zhang
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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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Chen, L., Zhang, C. (2005). Adaptive Parallel Ant Colony Algorithm. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_165

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  • DOI: https://doi.org/10.1007/11539117_165

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28325-6

  • Online ISBN: 978-3-540-31858-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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