An approximate solution method based on tabu search for k-minimum spanning tree problems

  • Authors:

  • Hideki Katagiri;Tomohiro Hayashida;Ichiro Nishizaki;Jun Ishimatsu

  • Affiliations:

  • Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan.;Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan.;Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan.;Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan

  • Venue:
  • International Journal of Knowledge Engineering and Soft Data Paradigms
  • Year:
  • 2010

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Abstract

This paper considers a new tabu search-based approximate solution algorithm for k-minimum spanning tree problems. One of the features of the proposed algorithm is that it efficiently obtains local optimal solutions without applying minimum spanning tree algorithms. Numerical experimental results show that the proposed method provides a good performance especially for dense graphs in terms of solution accuracy over existing algorithms.