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Optimizing Least-Cost Steiner Tree in Graphs via an Encoding-Free Genetic Algorithm

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Advances in Swarm Intelligence (ICSI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10385))

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Abstract

Most bio-inspired algorithms for solving the Steiner tree problem (STP) require the procedures of encoding and decoding. The frequent operations on both encoding and decoding inevitably result in serious time consumption and extra memory overhead, and then reduced the algorithms’ practicability. If a bio-inspired algorithm is encoding-free, its practicability will be improved. Being motivated by this thinking, this article presents an encoding-free genetic algorithm in solving the STP. To verify our proposed algorithm’s validity and investigate its performance, detailed simulations were carried out. Some insights in this article may also have significance for reference when solving the other problems related to the topological optimization.

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Acknowledgements

This research is supported in part by National Science Foundation of China (No. 61502385, No. 61401354, No. 61503299), Key Basic Research Fund of Shaanxi Province (2016JQ6015), and Scientific Research Program Funded by Shaanxi Provincial Education Department (No. 16JK1554).

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Authors and Affiliations

  1. Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an, China

    Qing Liu, Rongjun Tang, Jingyan Kang, Junliang Yao, Wenqing Wang & Yali Wu

  2. Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an, China

    Qing Liu, Junliang Yao, Wenqing Wang & Yali Wu

Authors
  1. Qing Liu
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  2. Rongjun Tang
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  3. Jingyan Kang
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  4. Junliang Yao
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  5. Wenqing Wang
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  6. Yali Wu
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Corresponding author

Correspondence to Qing Liu .

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Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  3. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Liu, Q., Tang, R., Kang, J., Yao, J., Wang, W., Wu, Y. (2017). Optimizing Least-Cost Steiner Tree in Graphs via an Encoding-Free Genetic Algorithm. In: Tan, Y., Takagi, H., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2017. Lecture Notes in Computer Science(), vol 10385. Springer, Cham. https://doi.org/10.1007/978-3-319-61824-1_42

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  • DOI: https://doi.org/10.1007/978-3-319-61824-1_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61823-4

  • Online ISBN: 978-3-319-61824-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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