The application of a large-scale mixed Integer Linear Programming algorithm for optimizing integrated arrival-departure-surface-enroute traffic flow management is presented. The optimization approach is based on the Bertsimas-Lulli-Odoni model, which is used model flights with multiple possible routes in a given volume of airspace. A novel method is advanced to enforce the separation constraints between aircraft in the optimization framework. By leveraging the strong linear programming relaxation and by using the Dantzig-Wolfe decomposition technique, the large-scale linear program is decomposed into a large number of sub-problems and a master problem. The number of sub-problems is equal to the number of flights and can be solved independently of each other, whereas the master problem consists of a significantly smaller number of constraints than the original optimization problem. This decomposition decreases the computation effort in solving the problem. The proposed algorithm is implemented to schedule traffic in the New York N90 Terminal Radar Approach Control. The results obtained from the optimizer are compared with that obtained from a first-come-first-served scheduler. It is found that the proposed algorithm provides reduced aircraft delays when compared with the baseline scheduler.
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