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An Improved Heuristic for the Bandwidth Minimization Based on Genetic Programming

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Book cover Hybrid Artificial Intelligent Systems (HAIS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6679))

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Abstract

In this work we develop an improved heuristic based on genetic programming (GP) for the matrix bandwidth minimization problem (MBMP). This problem consists in rearranging the rows and columns of a sparse matrix such that the non-zero elements are in a band as close as possible to the main diagonal. We evaluated our heuristic on a set of 25 benchmark instances from the literature and compared with state-of-the-art algorithms. The obtained results are very encouraging and point out that GP is an appropriate method for solving the MBMP.

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Author information

Authors and Affiliations

  1. Dept. of Mathematics and Informatics, North University of Baia Mare, Romania

    P. C. Pop

  2. Dept. of Electrical Engineering, North University of Baia Mare, Romania

    O. Matei

Authors
  1. P. C. Pop
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  2. O. Matei
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Editor information

Editors and Affiliations

  1. GICAP Research Group, University of Burgos, 09006, Burgos, Spain

    Emilio Corchado

  2. Wroclaw University of Technology, 50-370, Wroclaw, Poland

    Marek Kurzyński  & Michał Woźniak  & 

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© 2011 Springer-Verlag Berlin Heidelberg

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Pop, P.C., Matei, O. (2011). An Improved Heuristic for the Bandwidth Minimization Based on Genetic Programming. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21222-2_9

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  • DOI: https://doi.org/10.1007/978-3-642-21222-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21221-5

  • Online ISBN: 978-3-642-21222-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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