Nicolas Barnier

Nicolas Barnier is a Researcher at the National School of Civil Aviation (ENAC) in the AI Axis. His work focuses on Constraint Programming, Combinatorial Optimization, and Air Traffic Management, particularly for Conflict Resolution and Deconfliction in aviation systems.

• Academic Affiliation: ENAC, MAIAA-OPTIM Team
• Key Collaborations: Cyril Allignol, Ruixin Wang, Nicolas Durand

Nicolas Barnier’s research spans decades, integrating Evolutionary Computation, Graph Coloring, and Hybrid Optimization Techniques for air traffic flow and mission planning. He co-developed the FaCiLe Constraint Library and advanced models for 4D Trajectory Deconfliction, Flight Level Allocation, and UAS Detect & Avoid Systems.

His publications highlight applications in Large-Scale 3D Conflict Resolution, Robust Gate Allocation, and Mission Planning for Micro Drones. Though no explicit awards are listed, his sustained contributions to constraint programming and air traffic management through 50+ publications and collaborations with institutions like FAA, Eurocontrol, and IEEE underscore his impact.