• DocumentCode
    296217
  • Title

    Co-evolution of the fitness function and design solution for design exploration

  • Author

    Maher, Mary Lou ; Poon, Josiah

  • Volume
    1
  • fYear
    1995
  • fDate
    Nov. 29 1995-Dec. 1 1995
  • Firstpage
    240
  • Abstract
    We use a Genetic Algorithm paradigm for modelling design exploration and distinguish this approach from design optimisation. The common assumption in design optimisation is that a fitness function is defined in advance. However, this is hardly the case for any practical design, especially for conceptual design. The fitness function changes and co-evolves with the generation of alternative design solutions. This paper presents an approach to the co-evolution of the fitness function and design solution by representing the fitness as part of the genotype. In this combined gene approach, the design solution part of the genotype is evaluated by the local fitness function part of the genotype. Through a two-phase crossover operation, both the fitness function and the design solution change with each generation. A example of designing a braced frame panel is used to illustrate this approach
  • Keywords
    Algorithm design and analysis; Biological systems; Conference proceedings; Design optimization; Extraterrestrial phenomena; Genetic algorithms; Process design; Space exploration; State-space methods; Tin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1995., IEEE International Conference on
  • Conference_Location
    Perth, WA, Australia
  • Print_ISBN
    0-7803-2759-4
  • Type

    conf

  • DOI
    10.1109/ICEC.1995.489152
  • Filename
    489152