• DocumentCode
    3373541
  • Title

    GraGA: a graph based genetic algorithm for airline crew scheduling

  • Author

    Ozdemir, H. Timucin ; Mohan, Chilukuri K.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY, USA
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    27
  • Lastpage
    28
  • Abstract
    Crew scheduling is an NP-hard constrained combinatorial optimization problem, which is very important for the airline industry. We propose a genetic algorithm, GraGA, to solve this problem. A new graph based representation utilizes memory effectively, and provides a framework in which we can easily develop various genetic operators
  • Keywords
    aerospace computing; genetic algorithms; scheduling; travel industry; GraGA; NP-hard constrained combinatorial optimization problem; airline crew scheduling; airline industry; graph based genetic algorithm; graph based representation; Biological cells; Constraint optimization; Cost function; Dynamic scheduling; FAA; Fuels; Genetic algorithms; Genetic mutations; Job shop scheduling; Processor scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 1999. Proceedings. 11th IEEE International Conference on
  • Conference_Location
    Chicago, IL
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-0456-6
  • Type

    conf

  • DOI
    10.1109/TAI.1999.809761
  • Filename
    809761
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3373541