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Increasing the Antibandwidth of Sparse Matrices by a Genetic Algorithm

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Recent Trends in Applied Artificial Intelligence (IEA/AIE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7906))

Abstract

The antibandwidth problem consists in finding a labeling of the vertices of a given undirected graph such that among all adjacent node pairs, the minimum difference between the node labels is maximized. In this paper, we formulate the antibandwidth problem in terms of matrices and propose an efficient genetic algorithm based heuristic approach for increasing the corresponding antibandwidth. We report computational results for a set of 30 benchmark instances. The preliminary results point out that our approach is an attractive and appropriate method to explore the solution space of this complex problem and leads to good solutions in reasonable computational times.

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Author information

Authors and Affiliations

  1. Dept. of Mathematics and Informatics, Technical Univ. of Cluj-Napoca, Romania

    Petrica C. Pop

  2. Dept. of Electrical Engineering, Technical University of Cluj-Napoca, Romania

    Oliviu Matei

Authors
  1. Petrica C. Pop
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  2. Oliviu Matei
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Texas State University, 78666, San Marcos, TX, USA

    Moonis Ali

  2. Agent Systems Research Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081, Amsterdam, HV, The Netherlands

    Tibor Bosse

  3. Interactive Intelligence Group, Department of Intelligent Systems, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands

    Koen V. Hindriks  & Catholijn M. Jonker  & 

  4. Computational Intelligence Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands

    Mark Hoogendoorn

  5. Agent Systems Research Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands

    Jan Treur

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© 2013 Springer-Verlag Berlin Heidelberg

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Pop, P.C., Matei, O. (2013). Increasing the Antibandwidth of Sparse Matrices by a Genetic Algorithm. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_25

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  • DOI: https://doi.org/10.1007/978-3-642-38577-3_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38576-6

  • Online ISBN: 978-3-642-38577-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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