LAUTECH

Metaheuristics for air traffic management / Nicolas Durand, David Gianazza, Jean-Baptiste Gotteland, Jean-Marc Alliot.

Contributor(s): Material type: TextPublication details: London : ISTE Ltd, 2016.; Hoboken : John Wiley & Sons, Inc., 2016.Description: xi, 194 p. : illISBN:
  • 1848218109
  • 9781848218109
Subject(s): LOC classification:
  • TL725.3.T7 D87 2016
Summary: 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.
Item type: Books
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Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
OLUSEGUN OKE LIBRARY LAUTECH Non-fiction TL 725.3 .T7D87 2016 (Browse shelf(Opens below)) 1 Available 0039458

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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