• DocumentCode
    3572802
  • Title

    Study on the rolling schedule optimization of five tandem cold rolling mills

  • Author

    Lixin Wei ; Bai Lv ; Ying Li ; Jingming Yang

  • Author_Institution
    Key Lab. of Ind. Comput. Control Eng., Yanshan Univ., Qinhuangdao, China
  • fYear
    2014
  • Firstpage
    1830
  • Lastpage
    1835
  • Abstract
    Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm based on the working mechanism of honeybee swarms. It has advantages of less control parameters, easily programming and simple calculation, but there are still many problems to be improved and solved. Firstly, the logistic sequence to contro1 the mutation size is applied to improve the diversity of the population. Secondly several selection strategies are analyzed and compared through simulation. Results indicate that the improved algorithm performance was superior to the basic artificial bee colony algorithm. Finally, a modified artificial bee colony algorithm for rolling schedule was to code and operate the reduction rates by the targets of load equalization and rolling force equilibrium on certain constraint conditions. The practice on 5 stands tandem cold rolling mills shows that the rolling schedule makes the distribution of power and roll force reasonable, and increase economic benefit.
  • Keywords
    cold rolling; logistics; optimisation; rolling mills; scheduling; swarm intelligence; ABC algorithm; artificial bee colony algorithm performance; constraint conditions; control parameters; economic benefit; honeybee swarms; load equalization; logistic sequence; mutation size; rolling force equilibrium; rolling schedule optimization; swarm intelligence optimization algorithm; tandem cold rolling mills; Automation; Force; Intelligent control; Logistics; Optimization; Schedules; Tin; artificial bee colony algorithm; chaos sequence; self-adapting search space; tandem cold rolling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2014 11th World Congress on
  • Type

    conf

  • DOI
    10.1109/WCICA.2014.7052998
  • Filename
    7052998