• DocumentCode
    391443
  • Title

    A stochastic scheduling method: elementary of relative priority approach

  • Author

    Jianhua, Yang ; Fujimoto, Yasutaka

  • Author_Institution
    Yokohama Nat. Univ., Japan
  • Volume
    3
  • fYear
    2002
  • fDate
    5-8 Nov. 2002
  • Firstpage
    2284
  • Abstract
    The concept of relative priority is introduced in this paper to attempt to minimize job lateness for a class of job shop scheduling, where the throwing time and delivery date are considered. A modelling methodology is proposed to illustrate the class of job shop, including its static and dynamic characteristics. The possible position of a job in a schedule is restrained by its effect on objective function value. Consequently the state space to be searched can be greatly reduced and its quality can also be improved so that it is easier and quicker to step to the minimization point. Detailed definition of relative priority is given in this paper and algorithms are discussed how to get a stable relative priority set. For both static case and dynamic case, it is possible to obtain a solution closer to optimum in the similar way. Finally data experiments show the feasibility and efficiency for proposed relative priority approach.
  • Keywords
    optimisation; scheduling; stochastic processes; delivery date; dynamic characteristics; job lateness minimisation; job shop scheduling; modelling methodology; objective function value; relative priority approach; relative priority set; static characteristics; stochastic scheduling method; throwing time; Availability; Dispatching; Dynamic scheduling; Genetic algorithms; Industrial relations; Job shop scheduling; Linear programming; Production facilities; State-space methods; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IECON 02 [Industrial Electronics Society, IEEE 2002 28th Annual Conference of the]
  • Print_ISBN
    0-7803-7474-6
  • Type

    conf

  • DOI
    10.1109/IECON.2002.1185328
  • Filename
    1185328