This paper applies the genetic algorithm with hybrid encoding to optimize airspace sectorization. First, an airspace weighted-graph model is established based on controller workload and by the analysis of airspace static structure data and airspace complexity. Then, based on the established model, a hybrid encoding method, i.e., integer code and float code, is presented to optimize the airspace sectorization and its boundary. Combined with constraints on sector, the population is initialized and the mutation operator is constructed so that only valid individuals are generated, which, accordingly, can improve the convergence speed of algorithm. Finally, the proposed method is applied to the North China airspace, and the simulation results further validate the useableness of our method.


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    Titel :

    Optimization of Airspace Sectorization Based on Weighted Graph and Hybrid Encoding Genetic Algorithm


    Beteiligte:
    Bi, Hong (Autor:in) / Chen, Yangzhou (Autor:in) / Zhang, Defu (Autor:in) / Song, Zhuoxi (Autor:in)

    Kongress:

    The Twelfth COTA International Conference of Transportation Professionals ; 2012 ; Beijing, China


    Erschienen in:

    CICTP 2012 ; 1891-1902


    Erscheinungsdatum :

    23.07.2012




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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