An Improved Neural Network Model for the Two-Page Crossing Number Problem

  • Authors:
  • Hongmei He;O. Sykora;E. Makinen

  • Affiliations:
  • Dept. of Comput. Sci., Loughborough Univ.;-;-

  • Venue:
  • IEEE Transactions on Neural Networks
  • Year:
  • 2006

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Abstract

The simplest graph drawing method is that of putting the vertices of a graph on a line and drawing the edges as half-circles either above or below the line. Such drawings are called two-page book drawings. The smallest number of crossings over all two-page drawings of a graph G is called the two-page crossing number of G. Cimikowski and Shope have solved the two-page crossing number problem for an n-vertex and m-edge graph by using a Hopfield network with 2 m neurons. We present here an improved Hopfield model with m neurons. The new model achieves much better performance in the quality of solutions and is more efficient than the model of Cimikowski and Shope for all graphs tested. The parallel time complexity of the algorithm, without considering the crossing number calculations, is O(m) for the new Hopfield model with m processors clearly outperforming the previous algorithm