• DocumentCode
    1651030
  • Title

    Application of Improved Genetic Algorithm in Virtual Enterprise Partnership Selection

  • Author

    Jianghong, Han ; Meifang, Wang ; Xuesen, Ma ; Yuefei, Wang

  • Author_Institution
    Hefei Univ. of Technol., Hefei
  • fYear
    2007
  • Firstpage
    771
  • Lastpage
    775
  • Abstract
    Partner selection is a key problem of organizing a virtual enterprise. A multi-objective optimization model, which analyzes these candidate enterprises quantitatively is proposed and accomplished by an improved genetic algorithm. This algorithm sorts several single object fitness using quick-sorting algorithm and selects based on total fitness, crossovers and mutates using the self-adaptive probability, and finds the global optimal solution at last. Through comparison with standard GA and the improved self-adaptive GA, simulation example testifies the latter efficiency.
  • Keywords
    commerce; genetic algorithms; probability; sorting; virtual enterprises; genetic algorithm; multiobjective optimization model; object fitness; quick-sorting algorithm; selfadaptive probability; virtual enterprise partnership selection; Algorithm design and analysis; Application software; Computer science education; Control engineering education; Educational technology; Genetic algorithms; Industrial control; Organizing; Safety; Virtual enterprises; Genetic Algorithm (GA); Multi-Objective Optimization; Partner Selection; Virtual Enterprise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2007. CCC 2007. Chinese
  • Conference_Location
    Hunan
  • Print_ISBN
    978-7-81124-055-9
  • Electronic_ISBN
    978-7-900719-22-5
  • Type

    conf

  • DOI
    10.1109/CHICC.2006.4347326
  • Filename
    4347326