Collaborative Sequencing Of Arrival Flights In Multi Airport Terminal Area Based On Multi-objective Fusion

In the future,the number of terminal area in China will increase year by year,and the traffic flow is also increasing.According to annual statistics,the airspace resources are not proportional to the growth of flight traffic in the terminal area.In addition,the traffic in the terminal area tends to be saturated in recent years,and there are more common phenomena such as aircraft congestion,conflicts between aircraft,and serious delays in the terminal area.Such phenomena not only seriously affects the safety of aircraft and the interests of airlines,but also causes a great workload to the controllers.Therefore,there are many problems(it is a problem)to be solved at present.To effectively improve the operating efficiency of aircraft in the terminal area,to better ensure the safe flight of aircraft in airspace,and to reduce the load of controllers and the operating costs of the company.The research scenario of this thesis is multi airport terminal area.Firstly,according to the aeronautical chart,the airspace model of domestic multi airport terminal area,the operation mode of the airspace,the operation characteristics and influencing factors in this mode are understood;Secondly,through the research and analysis of the above problems,Factors that affect higher runtime dependencies are identified,and through such factors that the main solution goals and related constraints are found,from the three directions of aircraft delay,controller load and the balance of each airport.A new multi-airport terminal area aircraft arrival collaborative sequencing model is proposed.Finally,after understanding the advantages and disadvantages of traditional genetic algorithms,the improved NSGA-II algorithm is introduced to solve the model by using the Chengdu terminal area as an example.The results show that based on the improved genetic algorithm,compared with the first-come-first-served and unimproved genetic algorithm,the efficiency of aircraft approach sorting is increased by 55.2% and 28.1%,respectively.It can be seen that the proposed model can effectively improve the efficiency of aircraft sorting.The characteristic and innovation of this thesis is that a new model of collaborative sorting is proposed based on actual situation.and the model was solved using an improved genetic algorithm.Aircraft delays and controller load are greatly reduced and airspace resources are allocated fairly.