Airspace Capacity Management Based on Control Workload and Coupling Constraints between Airspaces

Motivated by the need for coordinated multi-Airspace flow management for the National Airspace System because of  flux coupling existing in airspaces, we  present  coupling-capacity of airspace through quantifying the impact of downstream air route flow on upstream flows. First, we present a multi-objective integral optimization model for coupling-capacity of airspace. Secondly, according to the topology structure of airspace, we set up a directed acyclic Graph (DAG). Through the DAG we can analyze the coupling-relationship between airspace sectors. Furthermore, according to the topological inverse sort of the DAG-net, we confirm the order of solving the coupling-capacity of every airspace unit in the airspace system. Finally, we present a hybrid Multi-Objective Genetic Algorithm (MOGA) to solve the multi-objective optimization problem. Simulation results demonstrate that MOGA can approach the satisfying solution about the coupling–capacity model. Through analyzing the solution, the coupling-capacity model of airspace could systemically balance and optimize airspace resources according to the distribution of flow requirements in each airspace element, and eliminate the ripple effect of congestion in the airspace system because of coupling between the airspaces.