Title :
A parallel genetic algorithm for the optimal design of multi-body model vehicle suspensions
Author :
Jingjun, Zhang ; Guangyuan, Liu ; Ruizhe, Gao ; Kanghua, Lou
Author_Institution :
Sci. Res. Office, Hebei Univ. of Eng., China
Abstract :
Based on an improved genetic algorithm, a parallel genetic algorithm is presented and the running environment is constituted in this paper. The parallel genetic algorithm of multi-body model vehicle suspension optimization is implemented establishing an interface between ADAMS software and the genetic algorithm. The results show that the parallel genetic algorithm developed in this paper is efficient.
Keywords :
genetic algorithms; mechanical engineering computing; parallel algorithms; suspensions (mechanical components); vehicles; ADAMS software; multibody model vehicle suspensions; optimal design; optimization; parallel genetic algorithm; Acceleration; Algorithm design and analysis; Concurrent computing; Genetic algorithms; Genetic mutations; Optimization methods; Power system modeling; Road vehicles; Robustness; Suspensions;
Conference_Titel :
Cluster Computing and the Grid, 2006. CCGRID 06. Sixth IEEE International Symposium on
Conference_Location :
Singapore
Print_ISBN :
0-7695-2585-7
DOI :
10.1109/CCGRID.2006.6
