Highlights ► Optimal traffic flow management is achieved by delay control. ► Sector capacities are well respected. ► Parallel computing platform accelerates the computation for traffic flow management. ► Decomposition methods are promising for a real-time traffic flow management platform.

    Abstract An aggregate air traffic flow model based on a multicommodity network is used for traffic flow management in the National Airspace System. The problem of minimizing the total travel time of flights in the National Airspace System of the United States, subject to sector capacity constraints, is formulated as an Integer Program. The resulting solution achieves optimal delay control. The Integer Program implemented for the scenarios investigated has billions of variables and constraints. It is relaxed to a Linear Program for computational efficiency. A dual decomposition method is applied to solve the large scale Linear Program in a computationally tractable manner. A rounding algorithm is developed to map the Linear Program solution to a physically acceptable result, and is implemented for the entire continental United States. A 2-h traffic flow management problem is solved with the method.


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    Titel :

    A dual decomposition method for sector capacity constrained traffic flow optimization


    Beteiligte:
    Sun, D. (Autor:in) / Clinet, A. (Autor:in) / Bayen, A.M. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2011-03-26


    Format / Umfang :

    23 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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