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A Parallel Pre-schedule Max-Min Ant System

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Cloud Computing and Security (ICCCS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11063))

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Abstract

The parameter sensitivity of MMAS algorithm is analyzed in this paper. And then, we propose a multi-ant colony parallel optimization algorithm based on dynamic parameter adaptation strategy, aiming at the performance lack of traditional ACO algorithm. This algorithm makes use of cloud computing parallelism to design and analyze the MMAS system. The convergence solution comparison results show that this method has certain advantages.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (51409117, 51679105, 61672261), Jilin Province Department of Education Thirteen Five science and technology research projects [2016] No. 432, [2017] No. JJKH20170804KJ.

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Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Ying Zheng, Qianlong Yang & Lili He

  2. Center for Computer Fundamental Education, Jilin University, Changchun, 130012, China

    Ying Zheng & Longhai Jin

Authors
  1. Ying Zheng
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  2. Qianlong Yang
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  3. Longhai Jin
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  4. Lili He
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Corresponding author

Correspondence to Lili He .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Zheng, Y., Yang, Q., Jin, L., He, L. (2018). A Parallel Pre-schedule Max-Min Ant System. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11063. Springer, Cham. https://doi.org/10.1007/978-3-030-00006-6_16

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  • DOI: https://doi.org/10.1007/978-3-030-00006-6_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00005-9

  • Online ISBN: 978-3-030-00006-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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