• DocumentCode
    2163547
  • Title

    Fuzzy optimization of plain linkage applying hybrid genetic algorithm

  • Author

    Xi, Pingyuan ; Yang, Chunsheng

  • Author_Institution
    Sch. of Mech. Eng., Huaihai Inst. of Technol., Lianyungang, China
  • Volume
    2
  • fYear
    2010
  • fDate
    26-28 Feb. 2010
  • Firstpage
    726
  • Lastpage
    728
  • Abstract
    In view of the design sample of crank-rocker linkage, considering the uncertainty of the design variable value and load-bearing capacity, and satisfying the Grashof condition and the transmission performances, the fuzzy optimization mathematic model is established to minimize the deviation between the desired and the calculated path law of motion. The method of second-class comprehensive evaluation was used by the optimal level cut set, thus the fuzzy optimization is transformed into the usual optimization. Considering the problem of low efficiency and local optimum caused by traditional optimal methods, the hybrid genetic algorithm are adopted to solve the optimization model. The results demonstrate that the fuzzy approach is an effective tool to deal with the uncertainties present in design optimization and can provide more realistic solutions. So that the optimization process is simplified and global optimum is acquired reliably.
  • Keywords
    couplings; crankcases; fuzzy set theory; genetic algorithms; power transmission (mechanical); Grashof condition; crank-rocker linkage; fuzzy optimization; hybrid genetic algorithm; load-bearing capacity; plain linkage; transmission performances; Algorithm design and analysis; Couplings; Design optimization; Educational institutions; Electronic mail; Genetic algorithms; Mathematical model; Mechanical engineering; Optimization methods; Uncertainty; Fuzzy optimization; hybrid genetic algorithm; plain linkage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5585-0
  • Electronic_ISBN
    978-1-4244-5586-7
  • Type

    conf

  • DOI
    10.1109/ICCAE.2010.5451748
  • Filename
    5451748