Modeling and Optimization of Air Traffic (ePub)

This book combines the research activities of the authors, both
of whom are researchers at Ecole Nationale de l'Aviation
Civile (French National School of Civil Aviation), and presents
their findings from the last 15 years. Their work uses air
transport as its focal point, within the realm of mathematical
optimization, looking at real life problems and theoretical models
in tandem, and the challenges that accompany studying both
approaches.

The authors' research is linked with the attempt to reduce
air space congestion in Western Europe, USA and, increasingly,
Asia. They do this through studying stochastic optimization
(particularly artificial evolution), the sectorization of airspace,
route distribution and takeoff slots, and by modeling airspace
congestion.

Finally, the authors discuss their short, medium and long term
research goals. They hope that their work, although related to air
transport, will be applied to other fields, such is the
transferable nature of mathematical optimization. At the same time,
they intend to use other areas of research, such as approximation
and statistics to complement their continued inquiry in their own
field.

Contents

1. Introduction.

Part 1. Optimization and Artificial Evolution

2. Optimization: State of the Art.

3. Genetic Algorithms and Improvements.

4. A new concept for Genetic Algorithms based on Order
Statistics.

Part 2. Applications to Air Traffic Control

5. Air Traffic Control.

6. Contributions to Airspace Sectorization.

7. Contribution to Traffic Assignment.

8. Airspace Congestion Metrics.

9. Conclusion and Future Perspectives.

About the Authors

Daniel Delahaye works for Ecole Nationale de l'Aviation
Civile (French National School of Civil Aviation) in France.

Stéphane Puechmorel works for Ecole Nationale de
l'Aviation Civile (French National School of Civil Aviation)
in France.