• DocumentCode
    2488249
  • Title

    A Coevolutionary Genetic Based Scheduling Algorithm for stochastic flexible scheduling problem

  • Author

    Gu, Jinwei ; Gu, Xingsheng ; Jiao, Bin

  • Author_Institution
    Dept. of Inf. Sci. & Eng., East China Univ. of Sci. & Technol., Shanghai
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    4160
  • Lastpage
    4165
  • Abstract
    Because traditional genetic algorithm has many limitations on solutions for the combined optimization problems, a coevolutionary genetic based scheduling algorithm (CGBSA) is proposed for solving the stochastic flexible scheduling problem. In CGBSA, the number of sub-population is divided by the number of working procedure. The interaction of all sub-populations is reflected by means of the definition of fitness function. Based on stochastic programming theory and stochastic simulation, a model is presented object to minimize the maximum completion time, in which the processing time is uncertainty. Compared with GA, the simulation results validate the efficiency of the proposed stochastic schedule model and algorithm.
  • Keywords
    evolutionary computation; scheduling; stochastic programming; coevolutionary genetic based scheduling algorithm; stochastic flexible scheduling problem; stochastic programming theory; stochastic simulation; Computational modeling; Evolution (biology); Genetic algorithms; Job shop scheduling; Probability distribution; Processor scheduling; Robustness; Scheduling algorithm; Stochastic processes; Uncertainty; Stochastic flexible scheduling; coevolutionary Genetic Algorithm; stochastic programming; stochastic simulation; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4593591
  • Filename
    4593591