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
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;
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
DOI :
10.1109/IITA.2009.9