Aircraft deconfliction with speed regulation: new models from mixed-integer optimization

Sonia Cafieri, Nicolas Durand

Journal of Global Optimization 58(4):613-629

2014/04/01

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Abstract:

Detecting and solving aircraft conflicts, which occur when aircraft sharing the same airspace are too close to each other according to their predicted trajectories, is a crucial problem in Air Traffic Management. We focus on mixed-integer optimization models based on speed regulation. We first solve the problem to global optimality by means of an exact solver. The problem being very difficult to solve, we also propose a heuristic procedure where the problem is decomposed and it is locally exactly solved. Computational results show that the proposed approach provides satisfactory results.

Keywords: air traffic management, conflict avoidance, MINLP, modeling, heuristic Aircraft trajectory prediction, mass estimation, BADA, Machine Learning

BibTeX entry:

@InProceedings{jogo2014,
 title = {Aircraft deconfliction with speed regulation: new models from mixed-integer optimization},
 author = {Sonia Cafieri and Nicolas Durand},
 BookTitle = {Journal of Global Optimization 58(4):613-629},
 year = {2014}
}

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