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Solving air-traffic conflict problems via local continuous optimization

Authors :
Andrew R. Conn
Clément Peyronne
Marcel Mongeau
Daniel Delahaye
Capgemini [Toulouse]
Capgemini
IBM [Yorktown] (IBM)
IBM
ENAC Equipe MAIAA-OPTIM (MAIA-OPTIM)
ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l'Aérien (MAIAA)
Ecole Nationale de l'Aviation Civile (ENAC)-Ecole Nationale de l'Aviation Civile (ENAC)
Ecole Nationale de l'Aviation Civile (ENAC)
ANR-12-JS02-0009,ATOMIC,Optimisation du trafic aérien via des méthodes mixtes (discretes-continus)(2012)
Source :
European Journal of Operational Research, European Journal of Operational Research, Elsevier, 2015, 241 (2), pp.502-512. ⟨10.1016/j.ejor.2014.08.045⟩
Publication Year :
2015
Publisher :
HAL CCSD, 2015.

Abstract

International audience; This paper first introduces an original trajectory model using B-splines and a new semi-infinite programming formulation of the separation constraint involved in air traffic conflict problems. A new continuous optimization formulation of the tactical conflict-resolution problem is then proposed. It involves very few optimization variables in that one needs only one optimization variable to determine each aircraft trajectory. Encouraging numerical experiments show that this approach is viable on realistic test problems. Not only does one not need to rely on the traditional, discretized, combinatorial optimization approaches to this problem, but, moreover, local continuous optimization methods, which require relatively fewer iterations and thereby fewer costly function evaluations, are shown to improve the performance of the overall global optimization of this non-convex problem.

Details

Language :
English
ISSN :
03772217
Database :
OpenAIRE
Journal :
European Journal of Operational Research, European Journal of Operational Research, Elsevier, 2015, 241 (2), pp.502-512. ⟨10.1016/j.ejor.2014.08.045⟩
Accession number :
edsair.doi.dedup.....748f7b818f4b842eeb7294419ecec4cf