Adaptive immune genetic algorithm for tire tread pattern pitch parameters optimization

Authors:
Xia Chen;Lijun Chen;Yiqing Chen;Wangxin Xiao
Affiliations:
Institute of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China;Institute of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China;Institute of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China;Engineering Research Center of Transportation Safety, Minisrty of Eductation, Wuhan University of Technology, Wuhan, China
Venue:
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Year:
2009

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Abstract

In order to reduce tire tread pattern noise, an adaptive immune genetic algorithm (AIGA) is presented to optimize tire pitch parameters in this paper. According to character of tire pattern, the algorithm defines crossover, mutation and reverse order operation to improve searching ability. The multiple parameters optimization is discussed in this paper. The simulation results indicate that compared with genetic algorithm (GA) and immune genetic algorithm (IGA), the convergence and the efficiency of AIGA are distinctly improved. The optimized results can reduce tread patterns noise level, which has been applicable to development of tire thread pattern.