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A hybrid model for isomorphism identification in mechanism design based on intelligent manufacturing

Author

Listed:
  • Liao Ningbo
  • Yang Ping

Abstract

Isomorphism discernment of graphs is an important and complicate problem. The problem is vital for graph theory based kinematic structures enumeration. To solve the problem, a Genetic Algorithm (GA) model and a Hopfield Neural Networks (HNNs) model are developed respectively, and some operators are improved to prevent premature convergence. By a comparative study, the advantages and limitations of the two approaches for graph isomorphism problem are discussed. Based on above, a hybrid Neural-Genetic algorithm is proposed. Numerical experiments demonstrate the performance of the hybrid algorithm is more successful compared with the approach applying GA or HNN simply.

Suggested Citation

  • Liao Ningbo & Yang Ping, 2009. "A hybrid model for isomorphism identification in mechanism design based on intelligent manufacturing," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 18(3), pages 282-292.
    • Handle: RePEc:ids:ijmtma:v:18:y:2009:i:3:p:282-292
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