提升航空器运行效率，获取航空运输利益最大化，是中国民航一直以来追求的目标。研究表明，EoR进近（Established on RNP AR）在提升近距平行跑道运行效率方面具有不可替代的优势，因此受到业界广泛关注。将EoR进近与排序策略结合，以航班延误时间最小为目标函数，建立基于EoR的排序模型。对比分析基于EoR的独立运行与相关运行对航班延误时间的影响。针对大规模航班排序计算时解空间较大且要求时效性的特点，提出一种基于S形函数的自适应粒子群优化算法（S-shaped function based adaptive particle swarm optimization, SA-PSO）对模型进行求解。以昆明长水国际机场终端区为例进行实例验证，尾流安全间隔上，采用中国民航航空器尾流重新分类（RECAT-CN）运行标准。结果表明：EoR独立运行较相关运行减少总延误约38%、EoR独立运行模式下，本文算法较先到先服务（first come first served, FCFS）算法减少总延误约15.3%。

The operational efficiency of aircraft and maximization of aviation transportation benefits have consistantly been pursued by CAAC. It has been indicated by research that the Established on RNP AR (EoR) approach plays an irreplaceable role in improving efficiency, especially for short-distance parallel runway operations, thus, it has received widespread attention in the industry. The integration of EoR approach with sorting strategies was undertaken, with the aim of minimizing flight delay time serving as the objective function, leading to the establishment of a sorting model based on EoR. The impact of EoR-based independent operation versus correlated operation on flight delay time had been compared and analyzed. Addressing the large solution space and the time-sensitive nature of large-scale flight sequencing calculations, The S-shaped function based adaptive particle swarm optimization (SA-PSO) algorithm was proposed to solve the model. Taking the Kunming Changshui International Airport terminal area as an example for case verification, the RECAT-CN operational standard was adopted for wake turbulence safety separation. The results show that, compared to correlated operations, independent EoR operations result in an approximately 38% reduction in total delays. Additionally, the algorithm proposed in the study, when operated independently under the EoR mode results in a reduction of total delays by approximately 15.3%, compared to the first come first served (FCFS) algorithm.