The U.S. national Air Traffic Management (ATM) system is today operating at the edge of its capabilities, handling the real-time planning and coordination of over 50,000 flights per day. This situation will only worsen in the years to come, as it is expected that U.S. air traffic will nearly double by the year 2025. There is a pressing need therefore for increasing capacity to meet future demand, improving safety, enhancing efficiency, providing additional flexibility to airline operators, and equitable consideration of multiple stakeholder needs in this complex dynamic system. In this paper, we present a scalable enterprise framework for multi-stakeholder, multi-objective model-based planning and optimization of air traffic in the national airspace system (NAS). The approach is based on an intelligent evaluation and optimization at the strategic and flight route levels. At the strategic level, we focus on separations between flights to improve airspace system performance. At the flight route level, we focus on identifying an optimal portfolio of flight paths within a planning horizon that trades-off a reduction in miles flown and a reduction in congestion. This framework not only considers system-level objectives, but also regards the impact of decisions on the principal stakeholders within the NAS. It is expected that this system will serve as a key decision-support tool to address future NAS scalability and reliability needs.


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    Titel :

    MONACO - Multi-Objective National Airspace Collaborative Optimization


    Beteiligte:
    Subbu, Raj (Autor:in) / Lizzi, John (Autor:in) / Iyer, Naresh (Autor:in) / Jha, Pratik D. (Autor:in) / Suchkov, Alexander (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.03.2007


    Format / Umfang :

    1118149 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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