• 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