DocumentCode
2903156
Title
Adaptive Immune Genetic Algorithm for Tire Tread Pattern Pitch Parameters Optimization
Author
Chen, Xia ; Chen, Lijun ; Chen, Yiqing ; Xiao, Wangxin
Author_Institution
Inst. of Mech. & Electron. Eng., Wuhan Univ. of Technol., Wuhan, China
Volume
1
fYear
2009
fDate
21-22 Nov. 2009
Firstpage
52
Lastpage
55
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.
Keywords
genetic algorithms; interference suppression; tyres; adaptive immune genetic algorithm; immune genetic algorithm; reverse order operation; searching ability; thread pattern; tire pitch parameters; tread pattern pitch parameters optimization; Constraint optimization; Genetic algorithms; Genetic engineering; Genetic mutations; Immune system; Noise level; Noise reduction; Optimization methods; Tires; Yarn; adaptive immune genetic algorithm; mutiple parameters; optimization; pitch parameter; tire tread pattern;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location
Nanchang
Print_ISBN
978-0-7695-3859-4
Type
conf
DOI
10.1109/IITA.2009.9
Filename
5368623
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