A dynamic adaptive NSGA-II algorithm for sector network flight flow optimization

In this paper, based on the idea of Civil-Military Integration, a multi-objective optimization model of airspace sector network is proposed to solve the problem of collaborative optimization of global flight flow in airspace sector network. Two objective functions are designed, namely safety and economy of the airspace. The operational safety objective function is defined by the degree of air traffic congestion and the operational economy is the total delay cost of the global flight activities, as well as total delay of the military and the civil aviation flight. Based on the Non-dominated Sorting Genetic Algorithm II(NSGA-II) algorithm. This paper presents a dynamic adaptive NSGA-II algorithm to solve the proposed model, in which a crossover and mutation factor dynamic adjustment mechanism is introduced. The model and algorithm are validated using actual operation data of China's airspace sector network. The results show that the dynamic adaptive NSGA-II algorithm is better than two classical multi-objective evolutionary algorithms.