Title :
A Coarse-Grained Genetic Algorithm for the Optimal Design of the Flexible Multi-Body Model Vehicle Suspensions Based on Skeletons Implementing
Author :
Liu, Guangyuan ; Zhang, Jingjun ; Gao, Ruizhen ; Sun, Yang
Author_Institution :
Hebei Univ. of Eng., Handan
Abstract :
A parallel genetic algorithm based coarse-grained module for the optimal design of the flexible multi-body model vehicle suspensions is presented and the skeleton implementing is constituted in this paper. This paper tests the algorithm on the cluster system. The results show that the application of the algorithm presented in this paper outperforms equivalent sequential genetic algorithms for the optimization and also improves the efficiency of the computing time. We also compare the coarse-grained genetic algorithm with the master-slave genetic algorithm, and find the result of the genetic algorithm based coarse-grained is better than the result of the parallel genetic algorithm based master-slave module.
Keywords :
automotive components; genetic algorithms; mechanical engineering computing; suspensions (mechanical components); cluster system; coarse-grained genetic algorithm; flexible multibody model vehicle suspensions; master-slave genetic algorithm; parallel genetic algorithm; sequential genetic algorithms; vehicle suspension system; Algorithm design and analysis; Automotive engineering; Clustering algorithms; Genetic algorithms; Intelligent networks; Master-slave; Skeleton; Suspensions; System testing; Vehicles;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3391-9
Electronic_ISBN :
978-0-7695-3391-9
DOI :
10.1109/ICINIS.2008.172