• DocumentCode
    593918
  • Title

    Pure and Hybrid Optimizers Applicable to Large-Scale Design Problem

  • Author

    Chiba, Kazuya

  • Author_Institution
    Dept. of Mech. Syst. Eng., Hokkaido Inst. of Technol., Sapporo, Japan
  • fYear
    2012
  • fDate
    25-28 Aug. 2012
  • Firstpage
    409
  • Lastpage
    412
  • Abstract
    Design-Informatics has three points of view. One of these points is the investigation of efficient optimization to generate hypothetical database for a large-scale design problem. the results of the present study indicates the hybrid method between differential evolution and genetic algorithm is better performance for efficient exploration in design space under the condition for large-scale engineering design problem within 102 order evolution at most.
  • Keywords
    design engineering; genetic algorithms; particle swarm optimisation; design-informatics; differential evolution; genetic algorithm; hybrid optimizers; large-scale engineering design problem; particle swarm optimization; pure optimizers; Evolutionary computation; Genetic algorithms; History; Measurement; Noise; Optimization; Sociology; design-informatics; differential evolution; evolutionary computation; genetic algorithm; hybrid optimizer; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
  • Conference_Location
    Kitakushu
  • Print_ISBN
    978-1-4673-2138-9
  • Type

    conf

  • DOI
    10.1109/ICGEC.2012.123
  • Filename
    6457132