针对日益增长的空中交通需求所带来的严重航班延误现象,采用单目标难以解决离场时隙、飞行路径和管制员工作强度分配等问题,提取了造成空域拥挤和航班延误的要素,综合考虑离场时隙飞,行路径和管制员工作强度等目标,建立了多目标、非线性规划模型.设计了多目标遗传算法对其进行求解,并利用实际航班数据进行仿真,结果表明:所建立的模型和算法不仅能在合理的时间内为空域内全部航班找到较优离场时间和较优飞行路径,还能降低管制员高强度工作的持续时间,使流量更符合实际情况,有效缓解了空域拥挤现象.%Because of the increase of air traffic demands, the flight delays are more and more serious. Merely depending on the mono-objective programming can not solve the problems such as the assignments of departure slots, flight routes and ATC (air traffic control) workload. Thorough considering the above problems comprehensively, the factors causing airspace congestion and flight delays are picked up. Then, a multi-objective non-linear model is developed in this paper. For solving the model, a multi-objective genetic algorithm is designed and a simulation is performed based on the real flight data. The simulation results shows that the optimized departure time and routes for each flight are obtained within reasonable time-horizon and the ATC overload working time is also reduced. Finally, the air traffic flow is kept to be more coincident with the actual operation, and the airspace congestion is reduced effectively.
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