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Improved Genetic Algorithm for Solving Optimal Communication Spanning Tree Problem

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Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 212))

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Abstract

Optimal Communication Spanning Tree (OCST) is a well-known NP-hard problem on the graph that seeks for the spanning tree with the lowest cost. The tree cost depends on the communication volume between each pair of nodes. This paper proposed an improved Genetic Algorithm combining with Ahujia and Murty’s Tree Improvement Procedure. The proposed algorithm was experimented on known benchmark tests which used in many papers related to OCST problem, and random instances from 200 to 500 vertexes. The experimental results show that the proposed algorithm is better than the heuristic and out-performance the most recent evolutionary algorithm approaches.

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Acknowledgment

This work was partially supported by the project “Direction-based Evolutionary Algorithms” funded by the National Foundation of Science and Technology Development.

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Authors and Affiliations

  1. School of Information and Communication Technology, Hanoi University of Science and Technology, Hanoi, Vietnam

    Nguyen Duy Hiep & Huynh Thi Thanh Binh

Authors
  1. Nguyen Duy Hiep
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  2. Huynh Thi Thanh Binh
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Corresponding author

Correspondence to Nguyen Duy Hiep .

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Editors and Affiliations

  1. School of Science, Anhui University of Science & Technology, Huainan, China

    Zhixiang Yin

  2. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  3. Anhui University of Science & Technology, Huainan, China

    Xianwen Fang

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© 2013 Springer-Verlag Berlin Heidelberg

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Hiep, N.D., Binh, H.T.T. (2013). Improved Genetic Algorithm for Solving Optimal Communication Spanning Tree Problem. In: Yin, Z., Pan, L., Fang, X. (eds) Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013. Advances in Intelligent Systems and Computing, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37502-6_49

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  • DOI: https://doi.org/10.1007/978-3-642-37502-6_49

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37501-9

  • Online ISBN: 978-3-642-37502-6

  • eBook Packages: EngineeringEngineering (R0)

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