• DocumentCode
    2122138
  • Title

    Scheduling Aircraft Landing Based on Clonal Selection Algorithm and Receding Horizon Control

  • Author

    Jia, Xiaolan ; Cao, Xianbin ; Guo, Yuanping ; Qiao, Hong ; Zhang, Jun

  • Author_Institution
    Anhui Province Key Lab. of Software in Comput. & Commun., Univ. of Sci. & Technol. of China, Hefei
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    357
  • Lastpage
    362
  • Abstract
    The task of aircraft landing scheduling (ALS) is to give a landing sequence and landing times for a given set of aircrafts where many constraints must be satisfied. ALS is an NP-hard problem with large-scale and multi-constraint characteristics, thus it is hard to find optimal solution efficiently. In this paper, a hybrid algorithm of Clonal Selection Algorithm (CSA) and Receding Horizon Control (RHC) was proposed for ALS problem. In details, constrained CSA based on infeasibility degree (IFD) schedules aircrafts in current receding horizon, and then RHC repeats that optimization procedure using excellent gene segment spread (EGSS) until all aircrafts have landed. Comparative experiments show that the CSA-RHC hybrid algorithm is able to obtain an optimal landing sequence and landing times rapidly and effectively.
  • Keywords
    air traffic control; predictive control; scheduling; NP-hard problem; aircraft landing scheduling; clonal selection algorithm; gene segment spread; infeasibility degree; landing sequence; landing times; receding horizon control; Aerospace control; Air traffic control; Aircraft; Computational intelligence; Constraint optimization; Intelligent transportation systems; Linear programming; Processor scheduling; Scheduling algorithm; Sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems, 2008. ITSC 2008. 11th International IEEE Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2111-4
  • Electronic_ISBN
    978-1-4244-2112-1
  • Type

    conf

  • DOI
    10.1109/ITSC.2008.4732662
  • Filename
    4732662