Metaheuristics for Air Traffic Management

Description

Air Traffic Management involves many different services such as Airspace Management, Air Traffic Flow Management and Air Traffic Control. Many optimization problems arise from these topics and they generally involve different kinds of variables, constraints and uncertainties. Metaheuristics are often good candidates to solve these problems.

This book bridges academic sciences and a rapidly expanding application field. Due to the lack of competition in Air Navigation System Providers (ANSPs), research in this area has for a long time been neglected. On the other hand, academics sometimes have a hard time understanding the complexity of the problems encountered in Air Traffic Management and tend to simplify models in a way that makes their solutions useless in a real context. This book gives the necessary background to scientists to understand the complexity of Air Traffic Management problems and to help ANSPs find new solutions to improve the system efficiency.

To do so, the authors model various complex Air Traffic Management problems such as airport taxiing, departure slot allocation, en-route conflict resolution, airspace and route design, and detail the operational context and state of the art for each problem. They introduce different approaches using metaheuristics to solve these problems and, when possible, compare their performances to existing approaches.

Contents

1. The Context of Air Traffic Management.
2. Air Route Optimization.
3. Airspace Management.
4. Departure Slot Allocation.
5. Airport Traffic Management.
6. Conflict Detection and Resolution.

About the authors/editors

Nicolas Durand is Professor at ENAC in France.
David Gianazza is Assistant Professor at ENAC in France.
Jean-Baptiste Gotteland is Assistant Professor at ENAC in France.
Jean-Marc Alliot is Research Director at the IRIT in France.

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Related subject

• Computer Engineering