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

Liao Ningbo and Yang Ping

International Journal of Manufacturing Technology and Management, 2009, vol. 18, issue 3, 282-292

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.

Keywords: hybrid neural-genetic model; GAs; genetic algorithms; HNNs; Hopfield neural networks; graph isomorphism; kinematic structure enumeration; mechanism design; intelligent manufacturing. (search for similar items in EconPapers)
Date: 2009
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