Research On Optimization Algorithm For Arrival And Departure Aircraft Collaborative Scheduling

The airport is an important part of civil aviation transportation system. With the development of the air transport industry, the number of aircraft is increasing and aircraft scheduling becomes more difficult. At present, preset route of aircraft taxiing as a basic model has been used in aircraft taxiway scheduling in airport terminal area. The first come first serve approach can deal with the conflict between aircrafts, but it also becomes the main factor restricting the aircraft scheduling efficiency. Therefore, on the basis of the existing airport layout, it is an important issue for the sustainable development of civil aviation to improve the operational efficiency of the airport by optimizing the scheduling method and adopting new technology.On the basis of domestic and foreign related research,an optimizing strategy for taxiway scheduling is proposed,which can dynamically adjust the priority of aircraft to solve the problem of taxiway scheduling. To carry out this strategy, the genetic algorithm is improved, and double chain chromosomes are encoded to optimize taxiing route and priority sequence of aircraft. The algorithm sets two fitness functions and uses the improved genetic algorithm to find the taxiing route of each aircraft. The priority sequence is dynamic with the changes of taxiing routes. On that basis, the algorithm of conflict resolution can achieve specific scheduling plan. The experiments verify that the algorithm can not only resolve conflicts between aircrafts, but also find optimal scheduling of taxiing route and priority sequence.Because of the limitation of current taxiway scheduling model, runway which is a shared resource for landing aircraft and taxiing aircraft, connects aircraft landing scheduling and taxiway scheduling. Regard landing final approach point as one point of taxiway network to unify the way to describe two issues. On the basis of taxiway scheduling, the collaborative scheduling that takes account of both landing and taxiing aircraft fusions the landing aircraft scheduling. At the same time experiments are made on the collaborative scheduling model using the above improved genetic algorithm. The experimental results show that the collaborative scheduling model has more superiority of global than the separation scheduling model. In order to show the collaborative scheduling model intuitively, a simulation system is designed to display the aircraft operation for the arrival and departure aircraft collaborative scheduling algorithm.