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A Genetic Programming Approach for Solving the Linear Ordering Problem

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Book cover Hybrid Artificial Intelligent Systems (HAIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7209))

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Abstract

The linear ordering problem (LOP) consists in rearranging the rows and columns of a given square matrix such that the sum of the super-diagonal entries is as large as possible. The LOP has a significant number of important practical applications. In this paper we describe an efficient genetic programming based algorithm, designed to find high quality solutions for LOP. The computational results obtained for two sets of benchmark instances indicate that our proposed heuristic is competitive to previous methods for solving the LOP.

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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. Universidad de Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Emilio Corchado

  2. VŠB-TU Ostrava 17, Listopadu 15, 70833, Ostrava, Czech Republic

    Václav Snášel

  3. Machine Intelligence Research Labs Machine Intelligence Research Labs(MIR Labs),, Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071, Auburn, Washington, USA

    Ajith Abraham

  4. Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Michał Woźniak

  5. University of the Basque Country, Pº Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Manuel Graña

  6. Yonsei University, 134 Shinchon-dong, 120-749, Sudaemoon-ku, Seoul, Korea

    Sung-Bae Cho

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© 2012 Springer-Verlag Berlin Heidelberg

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Pop, P.C., Matei, O. (2012). A Genetic Programming Approach for Solving the Linear Ordering Problem. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28931-6_32

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  • DOI: https://doi.org/10.1007/978-3-642-28931-6_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28930-9

  • Online ISBN: 978-3-642-28931-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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