In aviation transportation management, flight safety and ground operation safety are widely concerned. Gate assignment optimization is considered an important approach to ensuring airport safety management. The gate assignment problem was analyzed from the perspective of operational safety and efficiency. The minimum number of flight conflicts on the ground was used as the measurement criterion for operational safety, while the maximum docking rate and the shortest passenger walking distance were used for operationalefficiency. A gate assignment model that integrates both aspects was proposed. An improved adaptive particle swarm optimization (IAPSO) algorithm was developed. An adaptive particle update strategy and a dynamic reverse learning mechanism were incorporated to prevent the population from falling into local optima and to enhance convergence accuracy. Simulation experiments of different scales were conducted based on airport flight data. The results show that the proposed method performs well in terms of the number of conflicts and the docking rate, improving both flight ground operation safety and airport operational efficiency.