A GA-ANN for the Eulerian Cycle Problem

  • T. Tambouratzis
Conference paper


A novel approach for solving the Eulerian cycle problem is proposed. The approach constitutes a combination of genetic algorithms and artificial neural networks and accomplishes the consistent production of optimal solutions: on one hand, the existence of a Eulerian cycle of a given graph is determined; on the other hand, either a Eulerian cycle (if it exists) or a path encompassing the greatest possible number of edges is constructed.


Active Element Open Path Oriented Edge Average Connectivity Binary Element 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Ebert J.: Computing Eulerian trails. Information Processing Letters 28, 93 (1988).Google Scholar
  2. [2]
    Even S.: Graph Algorithms. Rockville, MD: Computer Science Press 1979.MATHGoogle Scholar
  3. [3]
    Holland J.H.: Adaptation in Natural and Artificial Systems. Ann Arbor, Michigan: University of Michigan Press 1975.Google Scholar
  4. [4]
    Lucas E.: Récréations Mathématiques. Paris: Gauthier-Villares 1891.Google Scholar
  5. [5]
    Manber U.: Introduction to Algorithms. Reading MA: Addison-Wesley 1989.MATHGoogle Scholar
  6. [6]
    Smolensky P.: Information processing in dynamical systems: foundations of harrnony theory. Parallel Distributed Processing: Foundations (Rumelhart D.E., McClelland J.L.). Cambridge MA: MIT Press 1986.Google Scholar
  7. [7]
    RJ. Wilson RJ., Watkins J.J.: Graphs: An Introductory Approach. New York: John Wiley & Sons 1990.Google Scholar

Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • T. Tambouratzis
    • 1
  1. 1.Institute of Nuclear Technology — Radiation ProtectionNCSR “Demokritos”AthensGreece

Personalised recommendations