This paper tackles the challenge of joint sequencing and merging optimization for airplanes and helicopters by proposing an optimized control algorithm aimed at minimizing flight delays. The algorithm comprehensively takes account of various factors such as trajectory conflicts, aircraft priority, speed limitations, and minimum separation constraints to construct the cost function. Simulated annealing is employed to determine the global optimal solution. To evaluate the algorithm, we conducted experiments using radar data from a randomly selected day at Nice Cote d’Azur Airport in France. The results showed that the algorithm could reduce total flight delay time by 50% and save an average of 1.8 L of fuel consumption per helicopter landing, thereby demonstrating its practicality and effectiveness in real-world scenarios.