DocumentCode :
3318370
Title :
A improved parallel genetic algorithm based on fixed point theory for the optimal design of multi-body model vehicle suspensions
Author :
Liu, Guangyuan ; Zhang, Jingjun ; Gao, Ruizhen ; Sun, Yang
Author_Institution :
Sci. Res. Office, Hebei Univ. of Eng., Handan, China
fYear :
2009
fDate :
8-11 Aug. 2009
Firstpage :
430
Lastpage :
433
Abstract :
Based on an improved genetic algorithm, a parallel genetic algorithm is presented and the skeleton implementing is constituted in this paper. The van der Laan-Talman Algorithm is introduced to the genetic algorithm to design convergence criteria objectively and to solve the convergence problem in the later period. The parallel genetic algorithm of multi-body model vehicle suspension optimization is implemented through establishing the interface between ADAMS software and the genetic algorithm. The results show that the parallel genetic algorithm developed in this paper is efficient.
Keywords :
CAD; automotive components; genetic algorithms; road vehicles; suspensions (mechanical components); virtual prototyping; ADAMS software; fixed point theory; multibody model vehicle suspensions; optimal design; parallel genetic algorithm; road vehicle; van der Laan-Talman algorithm; virtual prototyping software; Algorithm design and analysis; Automotive engineering; Concurrent computing; Convergence; Design engineering; Genetic algorithms; Genetic engineering; Optimization methods; Suspensions; Vehicles; Cluster system; Fixed Point Theory; Genetic Algorithm; Parallel Genetic Algorithm; Vehicle suspension;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
Type :
conf
DOI :
10.1109/ICCSIT.2009.5234913
Filename :
5234913
Link To Document :
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