基于利用率和跑道占用时间的军用机场快速出口滑行道位置优化模型

现行快速出口滑行道位置确定模型常以最小跑道占用时间为唯一目标，主要应用对象为民用机场，未能有效解决多机种、多运行模式下的军用机场快速出口滑行道位置确定问题。针对这个缺陷，基于综合利用率和综合跑道占用时间这2个指标，建立了综合考虑双指标的军用机场快速出口滑行道位置优化模型。以某军用机场飞行区构型为背景，以4种飞机为对象，结合该机场2种年架次比，在不同飞机着陆滑跑距离分布概率密度函数基础上，计算了不同位置快速滑行道出口对应的利用率，在此基础上得到了快速出口滑行道综合利用率。针对利用率大于90%的快速出口滑行道，应用贪心算法迭代不同快速出口滑行道的跑道占用时间，并通过加权计算得到综合跑道占用时间。基于综合利用率和综合跑道占用时间，确定出了快速出口滑行道数量和位置，给出了建议的方案，并进一步分析了年架次比改变对快速出口滑行道位置的影响。结果表明:与仅以利用率或最小跑道占用时间为优化目标的2种传统模型相比，应用优化模型提出的快速出口滑行道设计方案，在2种年架次比下使跑道占用时间分别缩短18.42，34.82 s，效率分别提高34.2%，40.6%。 

A Location Optimization Model for Rapid Exit Taxiway of Military Airports Based on Utilization Rate and Runway Occupancy Time

Current location models for designing rapid exit taxiways (RETs) mostly use the minimum runway occupancy time as their objective functions. These models are only applicable to civil airports, but not suitable for military airports with multiple aircrafts and multiple operation modes. In order to address this limitation, a location optimization model is developed by considering the comprehensive utilization rate (CUR) of RETs and comprehensive runway occupancy time (CROT). This paper uses a military airport with four types of aircraft and two different types of annual sortie ratios as the case study to prove the effectiveness of the proposed model. According to the probability density function of the landing distance required by aircrafts, the CUR is estimated for different RETs. At the same time, the CROT is estimated by a greedy algorithm. In addition, when the CUR is greater than 90% and the CROT is the minimum, the number and location of the rapid exit taxiways are determined. Then, this paper further analyzes the effect of different annual sortie ratios on the location of the rapid exit taxiway. Study results show that the new location optimization model has a better performance under the two types of annual sortie ratios. Finally, compared with the two traditional location models that only consider the utilization rate or the minimum runway occupancy time as design parameter, the proposed optimization model reduces the runway occupancy time by 18.42 s and 34.82 s, and enhances the runway efficiency by 34.2% and 40.6% respectively.