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A high-performance approach on mechanism isomorphism identification based on an adaptive hybrid genetic algorithm for digital intelligent manufacturing

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Abstract

The graph theory is an important method to achieve conceptual design for mechanism. During the process of kinematic structures enumeration using graph theory, isomorphism identification of graphs is an NP complete problem. It is important to improve the isomorphism identification efficiency and reliability. To solve the problem, an adaptive hybrid genetic algorithm is presented by mixing the improved genetic algorithm and local search algorithm. The crossover rate and mutation rate can be designed as adaptive parameters. Hence, the crossover rate and mutation rate can sustain the variety of the population and adjust the evolution. In the meantime, the pseudo-crossover operator is introduced to improve the search efficiency. In the last, some examples are illustrated to show the high efficiency of the algorithm by comparing with the results in other literatures.

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Acknowledgments

The authors would like to acknowledge the support of Natural Science Foundation of Gangxi Advanced Manufacturing Key Laboratory (GuiKeNeng 07109008_028_K), the support of Special Science Foundation for Middle-Young academic leader of Jiangsu high education in China (Qinglan Gongcheng Project), the Natural Science Foundation for Qualified Personnel of Jiangsu University(04JDG027)and the Science Foundation of Jiangsu Higher Education Institution(06KJD460044), the Special Natural Science Foundation for Innovative Group of Jiangsu University, Special Science Foundation for Middle-Young academic leader of Guangxi high education in China during the course of this work.

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Authors and Affiliations

  1. School of Mechanical Engineering, Jiangsu University, 212013, Zhenjiang, People’s Republic of China

    Ping Yang

  2. Computer Science Department, Huizhou University, 516007, Huizhou, People’s Republic of China

    Kehan Zeng

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  1. Ping Yang
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  2. Kehan Zeng
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Correspondence to Ping Yang.

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Yang, P., Zeng, K. A high-performance approach on mechanism isomorphism identification based on an adaptive hybrid genetic algorithm for digital intelligent manufacturing. Engineering with Computers 25, 397–403 (2009). https://doi.org/10.1007/s00366-009-0132-7

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  • DOI: https://doi.org/10.1007/s00366-009-0132-7

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