  We present the mapping of a class of simplified air traffic management (ATM)
problems (strategic conflict resolution) to quadratic unconstrained boolean
optimization (QUBO) problems. The mapping is performed through an original
representation of the conflict-resolution problem in terms of a conflict graph,
where nodes of the graph represent flights and edges represent a potential
conflict between flights. The representation allows a natural decomposition of
a real world instance related to wind-optimal trajectories over the Atlantic
ocean into smaller subproblems, that can be discretized and are amenable to be
programmed in quantum annealers. In the study, we tested the new programming
techniques and we benchmark the hardness of the instances using both classical
solvers and the D-Wave 2X and D-Wave 2000Q quantum chip. The preliminary
results show that for reasonable modeling choices the most challenging
subproblems which are programmable in the current devices are solved to
optimality with 99% of probability within a second of annealing time.
