• DocumentCode
    2039432
  • Title

    GA with hierarchical evaluation: a framework for solving complex machine scheduling problems in manufacturing

  • Author

    Cao, Heng ; Xi, Haifeng ; Luo, Yupin ; Yang, Suxing ; Peng, Yi

  • Author_Institution
    Dept. of Autom., Tsinghua Univ., Beijing, China
  • fYear
    1997
  • fDate
    2-4 Sep 1997
  • Firstpage
    326
  • Lastpage
    331
  • Abstract
    Machine scheduling is one of the most important issues in the planning and operations of manufacturing systems, which has been proved very difficult to solve with analytical methods because of its inherently complex constraints and objective. There do exist some successful approaches for standard n/m/J/Cmax job-shop problems, but they hardly consider the actual situations in manufacturing and are therefore not easy to extend for practical use. In this paper, we proposed an intuitive yet efficient framework for solving complex machine scheduling problems. First, definitions of complex scheduling problems are given and then the principles and components of our framework are described in detail. Our framework was applied in an electronics corporation and generated high-quality schedules. What is more, experiments on a number of established job-shop problem instances have shown that this same framework has better performance than most of the other known heuristics even in traditional n/m/J/Cmax problems
  • Keywords
    production control; complex machine scheduling; electronics corporation; genetic algorithm; job-shop; manufacturing; production control;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Genetic Algorithms in Engineering Systems: Innovations and Applications, 1997. GALESIA 97. Second International Conference On (Conf. Publ. No. 446)
  • Conference_Location
    Glasgow
  • ISSN
    0537-9989
  • Print_ISBN
    0-85296-693-8
  • Type

    conf

  • DOI
    10.1049/cp:19971201
  • Filename
    681046