• DocumentCode
    130853
  • Title

    Research on optimization of flight scheduling problem based on the combination of ant colony optimization and genetic algorithm

  • Author

    Wenkuai Liang ; Yi Li

  • Author_Institution
    Coll. of Comput. Sci., Sichuan Univ., Chengdu, China
  • fYear
    2014
  • fDate
    27-29 June 2014
  • Firstpage
    296
  • Lastpage
    299
  • Abstract
    As the flight scheduling has always been a key technology which reduces flight delays and costs. Rational and efficient flight sorting method not only can effectively improve the utilization of the airport, reduce flight delay, but also ensure flight safety and reduce the incidence of sudden accidents. Firstly, we studied the application of ant colony algorithm in flight sorting, and proposed a new flight sorting method which is combined with ant colony algorithm and genetic algorithm depending on the mutation characteristic of genetic algorithm; Secondly, the minimization objective model that the flight total delay was minimum was established based on the sorting method; Finally, the simulation experiment was done based on the model. The simulation results show that the proposed method can effectively reduce flight delay. Comparing with ant colony algorithm, the global optimal flight sequence can be found in a shorter time.
  • Keywords
    air traffic; ant colony optimisation; genetic algorithms; minimisation; scheduling; airport utilization; ant colony optimization; flight cost; flight delay; flight scheduling problem; flight sorting method; genetic algorithm; global optimal flight sequence; minimization objective model; Algorithm design and analysis; Delays; Educational institutions; Genetic algorithms; Optimal scheduling; Sorting; ant colony optimization; flight scheduling; genetic algorithm; global optimal;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2327-0586
  • Print_ISBN
    978-1-4799-3278-8
  • Type

    conf

  • DOI
    10.1109/ICSESS.2014.6933567
  • Filename
    6933567