A hybrid model for isomorphism identification in mechanism design based on intelligent manufacturing. (10th June 2009)

• Record Type: Journal Article
• Authors: Ningbo, Liao; Ping, Yang
• Is Part Of: International journal of manufacturing technology and management. Volume 18:Number 3(2009)
• Page Start: 282
• Page End: 292
• Publication Date: 2009-06-10
• Subjects: hybrid neural-genetic model -- GAs -- genetic algorithms -- HNNs -- Hopfield neural networks -- graph isomorphism -- kinematic structure enumeration -- mechanism design -- intelligent manufacturing; Manufacturing processes -- Periodicals; Manufacturing processes -- Automation -- Periodicals; Production management -- Periodicals; 670.427068
• Languages: English
• ISSNs: 1368-2148

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.