This publication combines the study actions of the authors, either one of whom are researchers at Ecole Nationale de l’Aviation Civile (French nationwide institution of Civil Aviation), and offers their findings from the final 15 years. Their paintings makes use of air shipping as its point of interest, in the realm of mathematical optimization, taking a look at actual lifestyles difficulties and theoretical types in tandem, and the demanding situations that accompany learning either approaches.
The authors’ study is associated with the try to decrease air house congestion in Western Europe, united states and, more and more, Asia. They do that via learning stochastic optimization (particularly synthetic evolution), the sectorization of airspace, path distribution and takeoff slots, and via modeling airspace congestion.
ultimately, the authors speak about their brief, medium and long-term study ambitions. They wish that their paintings, even if with regards to air shipping, should be utilized to different fields, such is the transferable nature of mathematical optimization. while, they intend to exploit different parts of study, comparable to approximation and information to counterpoint their persisted inquiry of their personal field.

Contents

1. Introduction.
half 1. Optimization and synthetic Evolution
2. Optimization: country of the Art.
three. Genetic Algorithms and Improvements.
four. a brand new proposal for Genetic Algorithms according to Order Statistics.
half 2. functions to Air site visitors Control
five. Air site visitors Control.
6. Contributions to Airspace Sectorization.
7. Contribution to site visitors Assignment.
eight. Airspace Congestion Metrics.
nine. end and destiny Perspectives.

About the Authors

Daniel Delahaye works for Ecole Nationale de l’Aviation Civile (French nationwide tuition of Civil Aviation) in France.
Stéphane Puechmorel works for Ecole Nationale de l’Aviation Civile (French nationwide university of Civil Aviation) in France.