Flight release sorting method based on air traffic flow management

Abstract

The invention relates to a flight release sorting method, in particular to a flight release sorting method based on air traffic flow management. A flight release sorting method based on air traffic flow management is characterized in that the method comprises the steps: determining the number of flights in a flight sorting pool and planned takeoff time of each flight, and employing a particle swarm algorithm for sorting flight sequences to achieve the purpose that the total flight delay time is minimum. The flight sequencing method provided by the invention has the advantages and effects that the flight sequencing method based on the particle swarm algorithm takes the minimum total flight delay time as the target, comprehensively considers the flow control interval, the take-off interval and other limiting factors, and sequences the flight sequence. Experiments show that the flight release efficiency can be improved, the flight delay time can be shortened, and compared with an existing system, the method has higher robustness and a better flight sorting effect.

Description

technical field [0001] The invention relates to a flight release sorting method, in particular to a flight release sorting method based on air traffic flow management. Background technique [0002] At present, with the continuous change of traffic management business in civil aviation, flight sequencing based on flow management is gradually developing towards globalization, gradually replacing traditional flight sequencing methods. At present, there are two main methods of flight release, one is the manual release sorting method for small and medium airports, and the other is the collaborative decision-making sorting method for civil aviation regional hubs such as Beijing, Shanghai, Guangzhou, and Shenyang. In recent years, the number of flights in my country has been increasing year by year, and the manual sorting method is no longer suitable for the current market situation, and it will also increase the workload of controllers; although the collaborative decision-making s...

AI Technical Summary

Problems solved by technology

For example, the simplex method cannot fully consider the local influence and global influence in a certain situation in terms of solution space optimization, and the calculation times of the global optimal solution are more and the efficiency is lower.

Using the genetic algorithm to calculate the flight release sorting algorithm has many parameters, the calculation is more complicated, and it will increase the burden on the entire flight release sorting application

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