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Think Locally, Act Globally: Highly Balanced Graph Partitioning

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Experimental Algorithms (SEA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7933))

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Abstract

We present a novel local improvement scheme for graph partitions that allows to enforce strict balance constraints. Using negative cycle detection algorithms this scheme combines local searches that individually violate the balance constraint into a more global feasible improvement. We combine this technique with an algorithm to balance unbalanced solutions and integrate it into a parallel multi-level evolutionary algorithm, KaFFPaE, to tackle the problem. Overall, we obtain a system that is fast on the one hand and on the other hand is able to improve or reproduce many of the best known perfectly balanced partitioning results reported in the Walshaw benchmark.

This paper is a short version of the TR [14].

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References

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Author information

Authors and Affiliations

  1. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Peter Sanders & Christian Schulz

Authors
  1. Peter Sanders
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  2. Christian Schulz
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Editor information

Editors and Affiliations

  1. Institute for Systems Analysis and Computer Science (IASI), National Research Council (CNR), Viale Manzoni 30, 00185, Rome, Italy

    Vincenzo Bonifaci

  2. Department of Computer and Systems Science, Sapienza University of Rome, Via Ariosto 25, 00185, Rome, Italy

    Camil Demetrescu  & Alberto Marchetti-Spaccamela  & 

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Sanders, P., Schulz, C. (2013). Think Locally, Act Globally: Highly Balanced Graph Partitioning. In: Bonifaci, V., Demetrescu, C., Marchetti-Spaccamela, A. (eds) Experimental Algorithms. SEA 2013. Lecture Notes in Computer Science, vol 7933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38527-8_16

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  • DOI: https://doi.org/10.1007/978-3-642-38527-8_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38526-1

  • Online ISBN: 978-3-642-38527-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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