• DocumentCode
    3364087
  • Title

    Research on coating production scheduling based on improved ant colony algorithm

  • Author

    Zhuo, Chen ; Jie, Zhang ; You-xin, Meng

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Qingdao Univ. of Sci. & Technol., Qingdao, China
  • fYear
    2010
  • fDate
    26-28 June 2010
  • Firstpage
    2955
  • Lastpage
    2958
  • Abstract
    The production of small and medium-sized coating enterprises has the characteristics of small batch, multi-type and higher flexibility, and its scheduling problem has great complexity, so traditional methods are hard to achieve the ideal effect. How to establish the reasonable production scheduling model, find out efficient scheduling algorithm, to raise the production efficiency and the utilization rate of resources, becomes a burning question. This paper considers the general constraints of production scheduling and the characteristic of coating production-the placed time of semi-finished can not be too long. The paper puts the placed time of semi-finished into probability selection formula, and uses the improved Ant Colony Algorithm to solve coating production scheduling problem. In simulation test, the machines have higher utilization rate, and it indicates that the algorithm is effective.
  • Keywords
    chemical industry; coatings; optimisation; production control; scheduling; small-to-medium enterprises; coating production scheduling problem; improved ant colony algorithm; medium-sized coating enterprises; probability selection formula; small sized coating enterprises; Application software; Coatings; Computer aided manufacturing; Educational institutions; Information science; Job shop scheduling; Paper technology; Processor scheduling; Production; Scheduling algorithm; ant colony algorithm; batch chemical process; coating production scheduling; the placed time of semi-finished;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-7737-1
  • Type

    conf

  • DOI
    10.1109/MACE.2010.5536497
  • Filename
    5536497