Study On Recovery Scheduling Problem Of Delayed Flights Based On Ant Colony Algorithm

With the rapid development of China's economy and civil aviation industry, the traffic congestions in the region of airport is becoming more and more serious and the flight delays is becoming unbearable. How to recover flight delays quickly and meet the growing demand of air transportation with more effective using of existing airport facilities has become an important research topic.The main task of flight delay quick recovery problem is to make the delayed planes depart in the shortest possible time, so that the airline's economic losses are reduced and the normal operation of the airport is restored. Optimizing the recovery scheduling of flight delay involves many factors, such as the type of airlines, the type of aircraft, the purpose airport, the departure time of regular flights, delay cost and so on. Poor recovery decision-making may result in congestions. The service level and the efficiencies of airport and airways would be adversely affected. Furthermore, accidents would happen.Ant colony algorithm is an intelligent algorithm derived from foraging behavior of ants in the nature, with robustness, positive feedback, distributed and parallel computing and other features. It is very suitable for solving complex combination optimization problems. Rapid recovery problem of flight delay is a typical NP-hard problem, ant colony algorithm is applied to solve the problem in this paper. The main work is as follows:Rapid recovery problem of flight delay in the single runway can be seen as TSP and is solved by ant colony algorithm to obtain a good result. Rapid recovery problem of flight delay in many runways can be seen as MTSP and the optimization model based on ant colony algorithm is proposed. At last, MATLAB is used to implement these algorithms.