• DocumentCode
    3057176
  • Title

    Optimization for aerospace conceptual design through the use of genetic algorithms

  • Author

    Crossley, William A.

  • Author_Institution
    Sch. of Aeronaut. & Astronaut., Purdue Univ., West Lafayette, IN, USA
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    200
  • Lastpage
    207
  • Abstract
    Using a genetic algorithm (GA) as a non-calculus-based global search method allows optimization-like techniques to be applied in the conceptual phase of design, which traditionally has been dominated by qualitative or subjective decision making. Features of the GA provide several advantages for conceptual design including: the ability to combine discrete, integer and continuous variables, the population-based search, no requirement for an initial design, and the ability to address non-convex, multimodal and discontinuous functions. Examples of applications to aerospace system conceptual design include aerospace vehicle design and satellite constellation design. A multiobjective design approach using the GA is also discussed
  • Keywords
    aerospace computing; genetic algorithms; aerospace conceptual design optimisation; aerospace system conceptual design; continuous variables; discontinuous functions; genetic algorithms; multiobjective design approach; non-calculus-based global search method; optimization-like techniques; population-based search; satellite constellation design; Aerospace engineering; Algorithm design and analysis; Biology computing; Design engineering; Design optimization; Evolution (biology); Genetic algorithms; Genetic engineering; Process design; Reactive power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolvable Hardware, 1999. Proceedings of the First NASA/DoD Workshop on
  • Conference_Location
    Pasadena, CA
  • Print_ISBN
    0-7695-0256-3
  • Type

    conf

  • DOI
    10.1109/EH.1999.785454
  • Filename
    785454