• DocumentCode
    2039309
  • Title

    Approach by localization and genetic manipulation algorithm for flexible job-shop scheduling problem

  • Author

    Kacem, Imed ; Hammadi, Slim ; Borne, Pierre

  • Author_Institution
    Lab. d´´Autom. et Inf. de Lille, Ecole Centrale de Lille, Villeneuve d´´Ascq, France
  • Volume
    4
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2599
  • Abstract
    Traditionally, assignment and scheduling decisions are separately made at different levels of the production management framework. The combining of these decisions presents additional complexity and new problems. We present two approaches to solve the assignment and job-shop scheduling problems (with total or partial flexibility). The first one is the approach by localization : it makes it possible to solve the problem of resources allocation and build an ideal assignments model (assignments scheme). The second one is an evolutionary approach controlled by the assignments model (generated by the first approach). In this approach, we apply advanced genetic manipulations in order to enhanced solutions quality. We Also explain some of the practical and theoretical considerations to the construction of a more robust encoding that will allow us to consider the sequencing and the assignment problems jointly
  • Keywords
    computational complexity; genetic algorithms; minimisation; production control; complexity; evolutionary approach; flexible job-shop scheduling problem; genetic manipulation algorithm; ideal assignments model; localization; partial flexibility; production management; resources allocation; sequencing; total flexibility; Encoding; Genetics; Processor scheduling; Production management; Resource management; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2001 IEEE International Conference on
  • Conference_Location
    Tucson, AZ
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7087-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2001.972955
  • Filename
    972955