• DocumentCode
    1775381
  • Title

    Design of an evolutionary multi-objective optimization scheduling system for a screw manufacturer

  • Author

    Tung-kuan Liu ; Yeh-Peng Chen ; Po-Han Lai ; Jyh-Hong Chou

  • Author_Institution
    Inst. of Eng. Sci. & Technol., Nat. Kaohsiung First Univ. of Sci. & Technol., Kaohsiung, Taiwan
  • fYear
    2014
  • fDate
    18-20 June 2014
  • Firstpage
    600
  • Lastpage
    603
  • Abstract
    The intelligent scheduling system has been proposed in this study and successfully applied to the scheduling of a screw manufacturer located at Taiwan, we aim added a concept of multi-objective optimization into practical scheduling system to promote the efficient of schedule and production. In order to meet user´s requirement, an improved genetic algorithm (GA) with a multi-objective design was adopted as a core technique of this intelligent system. It differs from traditional GA scheduling solution, our model capable of avoided incorrectly assigned a job to infeasible machine; thus, special designs in evolution process of GA are not required. A real case study was introduced in this paper, and the proposed model has been tested with 100 work orders, the empirical results were indicated that the proposed approach outperforms manual scheduling, regardless of the total orders completed time, machine retooling times, and the average load rate of machine.
  • Keywords
    fasteners; genetic algorithms; scheduling; GA scheduling solution; average load rate; evolution process; evolutionary multiobjective optimization scheduling system; genetic algorithm; intelligent scheduling system; machine retooling times; multiobjective design; screw manufacturer; Biological cells; Fasteners; Genetic algorithms; Job shop scheduling; Manuals; Optimization; encode; evolutionary; flexible job scheduling; genetic algorithms; multi-objective optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control & Automation (ICCA), 11th IEEE International Conference on
  • Conference_Location
    Taichung
  • Type

    conf

  • DOI
    10.1109/ICCA.2014.6870987
  • Filename
    6870987