Optimal Scheduling Based On Particle Swarm Optimization Flights

Along with the rapid development of the aerial transport, the air traffic volume carried out by both the civil aviation and the air force increase dramatically. When the national airspace resources and the management of the air traffic control units cannot meet the increasing requirements, the air traffic congestions come up, which not only threat the flight safety, but also bring in the flight delay. The air traffic flow management is the most efficient and economical method to ensure the air traffic congestion when we cannot improve the airport capacity through extending or updating the air traffic management facility. So it is the urgent problem that finds the efficient method to solve the air traffic flow management. At present, the Ground Holding Policy is the main method in the air traffic flow management. The Ground Holding Policy is to decide which aircraft should be delayed on the ground before take-off whenever it is foreseen it will not land in time because of congestion and by how much, in order to increase the safety of aircraft and minimize the cost of delays. From essentially said that this is one active management.Foreign men researched the ground holding policy earlier; they extracted it on century 80's. US had used ground holding policy in practical air traffic flow management and received good results. Chinese is in the primary stage because we research it later.The Single Airport Ground Holding problem in air traffic flow management and the aircraft departure sequencing problem are discussed in this paper. The main content of the paper could be described as follow:1. General knowledge of the air traffic flow management is introduced at first, including the conceptions and composition of air traffic management and air traffic flow management, discussed the conception, significance and the existing state of the ground holding policy.2. Introduced the classification of the single airport ground holding problem. Then give the models for the definitive demand and definitive capability single airport ground holding problem and the definitive demand and random capability single airport ground holding problem. After that make emulator experiments for these models adopt the particle swarm optimization algorithm and its improved algorithm. At the same time give the comparisons of the experimental results and the quality of the algorithms.3. Introduced the conception and significance of the aircraft departure scheduling, then give one model and make emulator experiment for this problem adopt chaotic particle swarm optimization algorithm. At the same time compare the experimental results with genetic algorithm that predecessor adopted solving same model and obtains the feasibility of the algorithm that this paper choose.4. Finally, summarized the work and deficiency which this paper does, and has given the forecast to the air traffic flow management and the development of the single airport ground holding problem, and then give the following work plan for this paper.