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为了对航班延误进行有效的事前控制,挖掘后继航班独立延误对飞机路径整体延误的影响,建立了更加精确的独立延误和波及延误算法流程,侧重研究与航班计划变更无关的独立延误的统计分布。在拟合出航班独立延误服从对数正态分布的基础上,建立了以波及延误最小为目标函数的飞机路径随机优化模型。求解过程中通过已知分布将随机模型转化为确定性模型,降低了模型的求解难度。最后将该模型应用于国内某一航空公司运行数据,优化后的波及延误降低了28%,成本降低17.37%。结果表明,基于统计分析基础上的飞机路径优化模型可以提高航班计划的先行鲁棒性。
In order to effectively control the delay of flight and find out the impact of independent delay of subsequent flight on the overall flight path delay, we established a more accurate independent delay and delay-delay algorithm flow, focusing on studying the statistical distribution of independent delays unrelated to flight plan change. On the basis of fitting the logarithmic normal distribution of independent delay obey flight, a stochastic optimization model of aircraft path with the minimum delay as the objective function is established. In the process of solving, the stochastic model is transformed into the deterministic model through the known distribution, which reduces the difficulty of solving the model. Finally, the model is applied to the operating data of a domestic airline. The optimized delay is reduced by 28% and the cost is reduced by 17.37%. The results show that the flight path optimization model based on statistical analysis can improve flight planning robustness.