• DocumentCode
    459045
  • Title

    Interactive Genetic Algorithms for Optimization of Problems with Multiple Modes and Implicit Performance Indices

  • Author

    Gong, Dunwei ; Yuan, Jie

  • Author_Institution
    Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou
  • Volume
    2
  • fYear
    2006
  • fDate
    16-18 Oct. 2006
  • Firstpage
    1001
  • Lastpage
    1005
  • Abstract
    Optimization of problems with multiple modes and implicit performance indices is common, but so far there´s still no effective method to solve it. An interactive genetic algorithm (IGA) for optimizing such problems is presented in this paper Firstly, according to the distribution and the fitness of individuals in an evolutionary population, the property in multiple modes and the number of modes of an optimized problem is determined, and the optimal individuals of all modes are conserved. Then a user assigns the fitness to offspring obtained by evolving one generation referring to the phenotypes and the fitness of these reserved optimal individuals. The algorithm is applied to fashion design and the experimental results validate its efficiency. The achievement of the paper provides a feasible approach to looking for several optimal solutions of an optimized problem with multiple modes and implicit performance indices
  • Keywords
    design; genetic algorithms; fashion design; interactive genetic algorithms; phenotypes; problem optimization; Acceleration; Algorithm design and analysis; Convergence; Fatigue; Genetic algorithms; Humans; Investments; Neural networks; Optimization methods; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    0-7695-2528-8
  • Type

    conf

  • DOI
    10.1109/ISDA.2006.253748
  • Filename
    4021800