• DocumentCode
    1794641
  • Title

    Particle swarm optimization algorithm for solving airline crew scheduling problem

  • Author

    Ezzinbi, Omar ; Sarhani, Malek ; El Afia, Abdellatif ; Benadada, Youssef

  • Author_Institution
    ENSIAS, Mohammed-V Univ., Rabat, Morocco
  • fYear
    2014
  • fDate
    5-7 June 2014
  • Firstpage
    52
  • Lastpage
    56
  • Abstract
    In air transport, the cost related to crew members presents one of the most important cost supported by airline companies. The objective of the crew scheduling problem is to determine a minimum-cost set of pairings so that every flight leg is assigned a qualified crew and every pairing satisfies the set of applicable work rules. In this paper, we propose a solution for the crew scheduling problem with Particle Swarm Optimization (PSO) algorithm, this solution approach is compared with the Genetic Algorithm (GA) for both crew pairing and crew assignment problems which are the two part of crew scheduling problem.
  • Keywords
    particle swarm optimisation; scheduling; transportation; travel industry; PSO; air transport; airline companies; airline crew scheduling problem; crew assignment; flight leg; minimum-cost set; particle swarm optimization algorithm; Genetic algorithms; Job shop scheduling; Optimization; Particle swarm optimization; Processor scheduling; Schedules; Aircraft; Crew assignment; Crew pairing; Optimization; Particle Swarm Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Logistics and Operations Management (GOL), 2014 International Conference on
  • Conference_Location
    Rabat
  • Print_ISBN
    978-1-4799-4651-8
  • Type

    conf

  • DOI
    10.1109/GOL.2014.6887447
  • Filename
    6887447