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A Parallel Tabu Search Algorithm with Solution Space Partition for Cohesive Clustering Problems

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Algorithms and Architectures for Parallel Processing (ICA3PP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9532))

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Abstract

Clustering analysis plays an important role in a wide range of fields including data mining, pattern recognition, machine learning and many other areas. In this paper, we present a parallel tabu search algorithm for clustering problems. A permanent tabu list is proposed to partition the solution space for parallelization. Moreover, this permanent tabu list can also reduce the neighborhood space and constrain the election of candidates. The proposed approach is evaluated by clustering some specific dataset. And experimental results and speedups obtained show the efficiency of the parallel algorithm.

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Acknowledgments

This research is partially supported by China Intelligent Urbanization Co-Creation Center for High Density Region (CIUC) under grant (No. 20140004).

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Authors and Affiliations

  1. School of Software Engineering, Tongji University, Shanghai, 201804, China

    Zheng Xu & Buyang Cao

  2. China Intelligent Urbanization Co-Creation Center for High Density Region, Tongji University, Shanghai, 200092, China

    Buyang Cao

Authors
  1. Zheng Xu
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  2. Buyang Cao
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Corresponding author

Correspondence to Zheng Xu .

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Editors and Affiliations

  1. Central South University, Changsha, China

    Guojin Wang

  2. Sch of Information Technologies, Sydney University, Sydney, New South Wales, Australia

    Albert Zomaya

  3. Department of Information and Commu, University of Murcia, Murcia, Murcia, Spain

    Gregorio Martinez

  4. Changsha, China

    Kenli Li

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Xu, Z., Cao, B. (2015). A Parallel Tabu Search Algorithm with Solution Space Partition for Cohesive Clustering Problems. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9532. Springer, Cham. https://doi.org/10.1007/978-3-319-27161-3_29

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  • DOI: https://doi.org/10.1007/978-3-319-27161-3_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27160-6

  • Online ISBN: 978-3-319-27161-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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