Metaheuristics for Air Traffic Management

Nonfiction, Computers, Advanced Computing, Engineering, Computer Engineering
Cover of the book Metaheuristics for Air Traffic Management by Nicolas Durand, David Gianazza, Jean-Baptiste Gotteland, Jean-Marc Alliot, Wiley
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Author: Nicolas Durand, David Gianazza, Jean-Baptiste Gotteland, Jean-Marc Alliot ISBN: 9781119261537
Publisher: Wiley Publication: December 14, 2015
Imprint: Wiley-ISTE Language: English
Author: Nicolas Durand, David Gianazza, Jean-Baptiste Gotteland, Jean-Marc Alliot
ISBN: 9781119261537
Publisher: Wiley
Publication: December 14, 2015
Imprint: Wiley-ISTE
Language: English

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, uncertainties. Metaheuristics are often good candidates to solve these problems.

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

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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, uncertainties. Metaheuristics are often good candidates to solve these problems.

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

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