2017/11/13 by Tobias Stollenwerk, Bryan O'Gorman, Davide Venturelli +6 · 1 voice · 1 citation
Computer Science · Physics and Astronomy · #cs.DS #quant-ph
paper · pdf · doi:10.1109/tits.2019.2891235
Paper accepted for publication on: IEEE Transactions on Intelligent Transportation Systems
arxiv published 2017/11/13 · arxiv created 2019/02/21 · arxiv updated 2019/02/22
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.