1st Edition
by Daniel Delahaye (Author), Stéphane Puechmorel (Author)
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.
