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## Ant Colony Optimization for Air Traffic Conflict Resolution

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Nicolas Durand
Jean-Marc Alliot
• Fonction : Auteur
• PersonId : 967817

#### Résumé

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.

### Dates et versions

hal-01293554 , version 1 (24-03-2016)

### Identifiants

• HAL Id : hal-01293554 , version 1

### Citer

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⟩

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