A improved parallel genetic algorithm based on fixed point theory for the optimal design of multi-body model vehicle suspensions

Guangyuan Liu Guangyuan Liu,Yang Sun Yang Sun,Jingjun Zhang Jingjun Zhang,Ruizhen Gao Ruizhen Gao

doi:10.1109/iccsit.2009.5234913

A improved parallel genetic algorithm based on fixed point theory for the optimal design of multi-body model vehicle suspensions

Guangyuan Liu Guangyuan Liu, Yang Sun Yang Sun + Show 2 more

https://doi.org/10.1109/iccsit.2009.5234913

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Publication Date: Jan 1, 2009

Citations: 5

Affiliation: Hebei University of Science and Technology

#Parallel Genetic Algorithm #Genetic Algorithm + Show 8 more

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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.

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