• DocumentCode
    3305704
  • Title

    Genetic algorithm for rotating workforce scheduling problem

  • Author

    Morz, M. ; Musliu, Nysret

  • Author_Institution
    Technische Univ. Wien
  • fYear
    2004
  • fDate
    2004
  • Firstpage
    121
  • Lastpage
    126
  • Abstract
    In this paper a genetic algorithm based method for solving the rotating workforce scheduling problem is presented. Rotating workforce scheduling is a typical constraint satisfaction problem which appears in a broad range of workplaces (e.g. industrial plants). Solving this problem is of a high practical relevance. We propose a basic genetic algorithm for solving this problem. One mutation operator and three methods for crossover are presented. Finally we give computational results on benchmark examples from literature
  • Keywords
    constraint theory; genetic algorithms; scheduling; constraint satisfaction problem; genetic algorithm; mutation operator; rotating workforce scheduling problem; Educational institutions; Genetic algorithms; Genetic mutations; Hospitals; Industrial plants; Job shop scheduling; MONOS devices; Processor scheduling; Scheduling algorithm; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Cybernetics, 2004. ICCC 2004. Second IEEE International Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    0-7803-8588-8
  • Type

    conf

  • DOI
    10.1109/ICCCYB.2004.1437685
  • Filename
    1437685
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3305704