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International Conference on Numerical Methods and Applications

NMA 2018: Numerical Methods and Applications pp 125–132Cite as

Application of Parallel and Hybrid Metaheuristics for Graph Partitioning Problem

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11189))

Abstract

In this paper parallel and hybrid metaheuristics for graph partitioning are compared taking into account their efficiency in terms of a cost function and computation time. Seventeen methods developed on the basis of evolutionary algorithm, simulated annealing and tabu search are implemented and tested against graph instances computed on the basis of queen graphs from DIMACS repository and a class of random R–MAT graphs. These graphs are supposed to model a class of digital circuits being subject of decomposition into a given number of modules. In partitioning process several additional constraints have to be satisfied in order to enable composition of original circuits from subcircuits by means of VLSI/FPGA modules.

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Acknowledgements

This work was supported by the research grant No. E–3/611/2017/DS from Cracow University Technology.

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, Cracow University of Technology, ul. Warszawska 24, 31-155, Kraków, Poland

    Zbigniew Kokosiński & Marcin Pijanowski

Authors
  1. Zbigniew Kokosiński
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  2. Marcin Pijanowski
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Correspondence to Zbigniew Kokosiński .

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Editors and Affiliations

  1. Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria

    Geno Nikolov

  2. Bulgarian Academy of Sciences, Sofia, Bulgaria

    Natalia Kolkovska

  3. Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir Georgiev

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Kokosiński, Z., Pijanowski, M. (2019). Application of Parallel and Hybrid Metaheuristics for Graph Partitioning Problem. In: Nikolov, G., Kolkovska, N., Georgiev, K. (eds) Numerical Methods and Applications. NMA 2018. Lecture Notes in Computer Science(), vol 11189. Springer, Cham. https://doi.org/10.1007/978-3-030-10692-8_14

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  • DOI: https://doi.org/10.1007/978-3-030-10692-8_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-10691-1

  • Online ISBN: 978-3-030-10692-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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