Accéder directement au contenu Accéder directement à la navigation

Ant Colony Optimization for Air Traffic Conflict Resolution

Abstract : The n aircraft conflict resolution problem is highly combinatorial and can be optimally solved using classical mathematical optimisation techniques only for small problems involving less than 5 aircraft. This article applies an Ant Colony Optimization (ACO) algorithm in order to solve large problems involving up to 30 aircraft. In order to limit the number of pheromone trails to update, a $n$ aircraft conflict resolution problem is not modeled by a single ant but by a bunch of $n$ ants choosing their trajectories independantly. A relaxation process is also used in order to be able to handle difficult conflicts for which partial solutions can help finding a path toward the optimal solution. Two different sizes of a toy problem are solved and presented.
Keywords :
Type de document :
Communication dans un congrès

Littérature citée [12 références]

https://hal-enac.archives-ouvertes.fr/hal-01293554
Contributeur : Laurence Porte Connectez-vous pour contacter le contributeur
Soumis le : jeudi 24 mars 2016 - 23:04:31
Dernière modification le : mardi 27 octobre 2020 - 13:14:02
Archivage à long terme le : : lundi 14 novembre 2016 - 05:43:47

Fichier

atm2009_durandalliot.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

• HAL Id : hal-01293554, version 1

Citation

Nicolas Durand, Jean-Marc Alliot. Ant Colony Optimization for Air Traffic Conflict Resolution . ATM Seminar 2009, 8th USA/Europe Air Traffic Management Research and Developpment Seminar, Jun 2009, Napa, California, United States. ⟨hal-01293554⟩

Métriques

Consultations de la notice

261

Téléchargements de fichiers