中文摘要：

针对管制扇区动态规划与飞行流量时空调配的耦合问题，考虑运行容量、效率等目标，建立了两阶段协同规划模型及求解框架。第一阶段根据自然航路点和流量分布，结合Voronoi图与图论模型构建有限元加权图拓扑抽象，以均衡管制负荷和减少协调移交负荷为目标，基于遗传算法适应性生成扇区结构；第二阶段综合等待和改航策略，以缓解区域总延误和该区域造成的区域外延误为目标，同时兼顾均摊延误和减少延误架次，在区域内容量约束和其他区域对该区域的流控约束下，基于NSGA-II进行流量时空优化。按照优先级顺序实施策略流程，为缓解空中交通拥堵探索综合施策框架。仿真结果表明，所提出的模型算法可为提升空管运行品质提供辅助决策支持。

英文摘要：

Aiming at the coupling interaction of dynamic airspace sectorization and the space-time allocation of air traffic flow, we establish a two-stage collaborative programming model and solution framework to maximize the oper-ational capacity and efficiency. The first stage begins with the construction of a Voronoi cells based weighted graph model combined with Voronoi diagram and graph theory for the topological structure of given airspace and air traffic distribution. Then, the sector re-partitioning problem is solved based on genetic algorithm to balance the sector workloads and minimize the coordination workloads. In the second stage, we built air traffic flow network optimiza-tion model to reduce the total delay fairly, the ground delay out of the area fairly, the total number of delayed fights and the number of ground-delayed fights out of the area, with the airspace capacity constraint in the area and the minutes-in-trail restriction out of the area. Then, the multi-objective optimization problem is solved based on the non-dominated sorting genetic algorithm II （ NSGA-II ） for a combination of flow management actions, including ground holding, airborne holding, and rerouting. We explore the comprehensive framework for alleviating the traffic congestion according to the priority order of strategies described above. Simulation results show that： the proposed model can provide supporting decision-making for improving the operational quality of air traffic management.