摘要
针对航班延误问题,提出了从飞机轮挡事件的相关时间具有随机性的角度进行优化,建立了减少航班上轮挡及撤轮挡延误时间的概率约束型模型,并首次使用泰尔指数作为公平性目标函数。根据减少航班上轮挡延误、撤轮挡延误以及双延误的3种要求,可对建立的模型进行层次划分,从而达到不同的优化效果。以杭州萧山国际机场为算例进行算例验证,运用改进的粒子群算法进行求解,最终结果表明:所提模型对高峰期内的延误时间最高可减少26.4%,优化效果显著。
Aiming at the problem of flight delays,optimization was proposed from the perspective of the randomness of the block-related time,and a probabilistic constrained model was established to reduce the delay time of the flight in and out the block.For the first time,the Theil index was used as the fairness objective function.According to the three requirements of reducing the delay of the flight in-block,the delay of out-block and the double delay,the established model can be divided into different levels,so as to achieve different optimization effects.Taking Hangzhou Xiaoshan International Airport as an example to verify the calculation example,the improved particle swarm algorithm was used to solve the problem.The final results show that the proposed model can reduce the delay time in the peak period by up to 26.4%,and the optimization effect is significant.
作者
刘田野
翟文鹏
LIU Tian-ye;ZHAI Wen-peng(School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China)
出处
《科学技术与工程》
北大核心
2021年第36期15661-15668,共8页
Science Technology and Engineering
基金
中央高校基本科研业务费中国民航大学专项(3122017061)。
关键词
航班时刻
轮挡时间
随机性
粒子群算法
flight time
block time
randomness
particle swarm algorithm
