As the demand for air traffic increases, in order to optimize the operational efficiency and enhance safety of arriving flights, a priority model for the point merge system(PMS) was proposed. The determination of each flight's priority was based on its importance, taking into account factors such as the continuity of the flight, passenger load, and flight type. The objective function aimed to minimize the total delay cost and the total sorting edge flying time of arriving flights. Constraints encompassed unique sorting edges, wake turbulence separation, entry time window for the point merge system, sorting edge length, and the number of position transitions. Guangzhou Baiyun Airport's arrival procedures were exemplified, and the final sequence of landing flights was obtained using an improved non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). The results show that the improved NSGA-Ⅱ algorithm, compared to first-come-first-served and unimproved genetic algorithms, respectively decreased the total delay cost by 4.1% and 1.9%, and the total flight time by 32.5% and 21.6%. It is concluded that this model effectively reduces delay costs, decreases flying time, thereby alleviating airport airspace pressure, and enhancing flight efficiency.