• DocumentCode
    2650131
  • Title

    Cooperative Co-evolution with Weighted Random Grouping for Large-Scale Crossing Waypoints Locating in Air Route Network

  • Author

    Xiao Mingming ; Zhang Jun ; Cai Kaiquan ; Cao Xianbin ; Tang Ke

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Beihang Univ. Beijing, Beijing, China
  • fYear
    2011
  • fDate
    7-9 Nov. 2011
  • Firstpage
    215
  • Lastpage
    222
  • Abstract
    The large-scale Crossing Waypoints Location Problem (CWLP) is a crucial problem in the design of Air Route Network (ARN). CWLP is fully non-separable and non-differentiable, and thus traditional algorithms can hardly deal with it. This paper proposes an algorithm named Cooperative Co-evolution with Weighted Random Grouping (CCWR) to tackle it. CCWR employs the weighted random (WR) grouping strategy, which is specifically designed for CWLP, to divide the large-scale Crossing Waypoints (CWs) into small sub-groups and an Evolutionary Algorithm (EA) to solve the smaller scale CWs location problem in each sub-group. Experiments on the database of the ARN in China have been carried out to evaluate the performance of CCWR. The results showed that CCWR is superior to a number of state-of-the-art algorithms, and the advanced performance of CCWR is mainly due to the WR grouping strategy.
  • Keywords
    air traffic; evolutionary computation; group theory; transportation; ARN; CWLP; China; air route network; air traffic; cooperative co-evolution; evolutionary algorithm; large-scale crossing waypoints location problem; weighted random grouping strategy; Airports; Algorithm design and analysis; Collaboration; Educational institutions; Optimization; Safety; Vectors; Air Route Network; Cooperative Co-evolution; Crossing Waypoints Location;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
  • Conference_Location
    Boca Raton, FL
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4577-2068-0
  • Electronic_ISBN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2011.40
  • Filename
    6103330