• DocumentCode
    482161
  • Title

    A Genetic Algorithm Approach for Optimum Operator Assignment in CMS

  • Author

    Azadeh, Ali ; Kor, Hamrah ; Hatefi, Seyed-Morteza

  • Author_Institution
    Dept. of Ind. Eng., Univ. of Tehran, Tehran
  • Volume
    1
  • fYear
    2009
  • fDate
    22-24 Jan. 2009
  • Firstpage
    42
  • Lastpage
    46
  • Abstract
    This paper presents a decision making approach based on a hybrid GA for determining the most efficient number of operators and the efficient measurement of operator assignment in cellular manufacturing system (CMS).The objective is to determine the labor assignment in CMS environment with the optimum performance. We use The GA for getting near optimum ranking of the alternative with accordance to fitness function. Also, the GA approach is performed by employing the number of operator, average lead time of demand, average waiting time of demand, number of completed parts, operator utilization and average machine utilization as attributes, and Entropy method for determining the weight of attributes. Furthermore, values of the attributes procured by means of simulation.
  • Keywords
    cellular manufacturing; decision making; genetic algorithms; average machine utilization; cellular manufacturing system; decision making; entropy method; hybrid genetic algorithm; labor assignment; near optimum ranking; optimum operator assignment; Cellular manufacturing; Collision mitigation; Computer aided manufacturing; Decision making; Entropy; Genetic algorithms; Genetic engineering; Paper technology; Simultaneous localization and mapping; Uncertainty; CMS; Entropy method; Genetic Algorithm; Visual SLAM; decision making; simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Engineering and Technology, 2009. ICCET '09. International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-3334-6
  • Type

    conf

  • DOI
    10.1109/ICCET.2009.211
  • Filename
    4769423