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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.
In view of the serious flight delays caused by the increasing demand for air traffic, adopting the single target to solve the problem of departure time slots, flight paths and assignment of controllers’ work intensity, etc., the factors causing airspace congestion and flight delays are extracted and comprehensively considered Multi-objective and non-linear programming model is established for multi-objective and multi-objective flight planning, departure path flight and work intensity of controller, etc. The multi-objective genetic algorithm is designed to solve the problem and the actual flight data is used to simulate. The results show that: Model and algorithm can not only find a better departure time and better flight path for all flights in airspace within a reasonable time, but also reduce the duration of high-intensity work of controllers and make the traffic more in line with the actual situation, effectively alleviating Airspace congestion.