• DocumentCode
    2759270
  • Title

    Application of Self-Adaptive Genetic Algorithm on Allocating International Demand to Global Production Facilities

  • Author

    Chen, Rong-Chang ; Li, Shiue-Shiun ; Lin, Chih-Chiang ; Chen, Tung-Shou

  • Author_Institution
    Dept. of Logistics Eng. & Manage., Graduate Inst. of Bus. Adm.
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    7152
  • Lastpage
    7156
  • Abstract
    It is very important for managers to make correct producing decisions quickly in enhancing competitiveness capabilities. Besides traditional methods making decisions by humans´ experiences, some scholars provided a way to make decisions by using genetic algorithm for analyzing tools of the decision support system. However, there are some drawbacks in traditional genetic algorithm (or simple genetic algorithm). The results created by traditional genetic algorithm are usually unstable, and it is impossible for managers to adjust calculating parameters. Thus, we used self-adaptive genetic algorithm as the analytic tools of global decision support system, and the result fulfilled the requests of a real global company for garment manufacturing
  • Keywords
    clothing industry; decision support systems; demand forecasting; genetic algorithms; production management; self-adjusting systems; competitiveness capability; decision making; garment manufacturing; global decision support system; global production facility; international demand allocation; self-adaptive genetic algorithm; Algorithm design and analysis; Clothing; Costs; Decision support systems; Engineering management; Genetic algorithms; Information technology; Manufacturing industries; Production facilities; Technology management; decision support system; garment industry; self-adaptive genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1714473
  • Filename
    1714473