In the current domain of air traffic, frequent flight conflicts and departure flight delays within airport systems are increasingly becoming key factors that affect the efficiency of flight operations and passenger satisfaction. By considering the resource constraints of airport systems, the concept of“airport satisfaction”is introduced. The objectives of optimization include minimizing the total delay of departure flights, maximizing the sum of satisfaction across all airports, and maximizing the overall measure of fairness within the airport system. A collaborative sequencing model for departure flights in the terminal area of airport clusters is established, and an elitist strategy-based non-dominated sorting genetic algorithm is designed to solve the Pareto optimal solution for the collaborative sequencing problem of departure flights in the terminal area of airport clusters. An empirical analysis was conducted using the terminal areas of three airports in the Beijing-Tianjin region as examples. The experimental results show that compared to the first-come-first-served scheme, the total flight delay was reduced from 7 796 seconds to 5 029 seconds, a decrease of 35.5%, with the average delay per flight dropping from 159 seconds to 103 seconds. The average satisfaction of flights reached 0.786 7, and the overall measure of fairness among airports in the cluster was 0.004 4. The proposed optimization method can significantly reduce the total delay of departure flights in airport systems, improve overall flight satisfaction, and achieve the fair and efficient use of resources.