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
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