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Scipediacontent moved page Draft Content 847416902 to Grabbe et al 2009a

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== Abstract ==

The optimization of tra! c flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and e! ciency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air tra! c constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

== Original document ==

The different versions of the original document can be found in:

* [http://www.aviationsystemsdivision.arc.nasa.gov/publications/2009/AF2009178.pdf http://www.aviationsystemsdivision.arc.nasa.gov/publications/2009/AF2009178.pdf]

* [http://arc.aiaa.org/doi/pdf/10.2514/6.2009-5862 http://arc.aiaa.org/doi/pdf/10.2514/6.2009-5862],
: [http://dx.doi.org/10.2514/6.2009-5862 http://dx.doi.org/10.2514/6.2009-5862]

* [https://www.aviationsystemsdivision.arc.nasa.gov/publications/2009/AF2009178.pdf https://www.aviationsystemsdivision.arc.nasa.gov/publications/2009/AF2009178.pdf],
: [https://arc.aiaa.org/doi/pdf/10.2514/6.2009-5862 https://arc.aiaa.org/doi/pdf/10.2514/6.2009-5862],
: [https://ntrs.nasa.gov/search.jsp?R=20100036838 https://ntrs.nasa.gov/search.jsp?R=20100036838],
: [http://www.aviationsystemsdivision.arc.nasa.gov/publications/2009/AF2009178.pdf http://www.aviationsystemsdivision.arc.nasa.gov/publications/2009/AF2009178.pdf],
: [https://repository.exst.jaxa.jp/dspace/handle/a-is/271001 https://repository.exst.jaxa.jp/dspace/handle/a-is/271001],
: [https://academic.microsoft.com/#/detail/2156986695 https://academic.microsoft.com/#/detail/2156986695]

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Grabbe et al 2009a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 847416902 to Grabbe et al 2009a

Scipediacontent: Created page with " == Abstract == The optimization of tra! c flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes b..."