• DocumentCode
    2038833
  • Title

    A genetic algorithm for realistic resource scheduling

  • Author

    Beck, Felipe Luis ; Thomalla, Christoph S.

  • Author_Institution
    Departamento de Automacao e Sistemas, Univ. Fed. de Santa Catarina, Florianopolis, Brazil
  • Volume
    4
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2522
  • Abstract
    Optimal resource scheduling is a hard problem, the best known of which is the classical job shop scheduling problem. But it lacks various characteristics of real-world scheduling problems, limiting the use of tools used to solve it. We include some of these characteristics and present the development and implementation of an optimization methodology for scheduling jobs based on a genetic algorithm (GA). The results for some known test examples are shown
  • Keywords
    genetic algorithms; production control; classical job shop scheduling problem; genetic algorithm; hard problem; optimization methodology; realistic resource scheduling; Annealing; Dispatching; Genetic algorithms; Job shop scheduling; Lagrangian functions; Neural networks; Optimization methods; Polynomials; Processor scheduling; Testing;
  • 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.2001.972937
  • Filename
    972937