容量不确定情况下航班时隙分配策略研究
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摘要
针对机场容量不确定性情况下航班时隙调整所带来的成本损失日益严重这一问题,提出了带补偿的两阶段时隙分配多目标优化模型,模型以机场容量遵循某一概率分布为基础,考虑了具有连续航程航班的影响,同时以航班对时间的敏感度为主线,以延误成本为补偿,并利用改进的遗传算法对模型进行了求解,求解过程中多种容量情景下的时隙分配过程并行计算,同时每次迭代都对各种容量情景之间时隙分配的数据进行交换,并采用动态权重系数对目标函数进行优化,使模型能够快速高效地得到最优分配方案。最后对模型进行了仿真验证,并引入具体的量化指标对模型进行了量化分析,结果表明模型在容量不确定情况下所分配的时隙使得延误百分比、确定性综合成本以及不确定性综合成本都有了相应的减少,从而实现了对时隙资源的合理利用。
Due to the uncertainty of airport capacity, the adjustment of cost loss caused by flight time slot becomes more and more serious. In this article, a multi-objective optimization model of two-stage slot allocation with compensation was presented. First of all, the model took it as the basis that the airport capacity followed a certain probability distribution, and then this model considered the influence of flight with continuous voyage. At the same time, the sensitivity of flight to time was used as the main line and the delay cost was taken as compensation. In addition, the improved genetic algorithm was used to solve the model. During the solution, the slot allocation process under multiple capacities was calculated concurrently. In each iteration, the data of slot allocation among various capacity scenarios were exchanged. After that, the objective functions were optimized using dynamic weight coefficients, so that the model can obtain the optimal allocation plan quickly and efficiently. Finally, the model was verified and simulated. Meanwhile, the specific quantitative indicators were introduced to quantitatively analyze the model. The result shows that the time slot allocated by proposed model in the case of uncertain capacity can reduce the delay percentage, the deterministic comprehensive cost and the comprehensive cost of uncertainty respectively. Thus, the rational utilization of time slot resource can be achieved.
Due to the uncertainty of airport capacity, the adjustment of cost loss caused by flight time slot becomes more and more serious. In this article, a multi-objective optimization model of two-stage slot allocation with compensation was presented. First of all, the model took it as the basis that the airport capacity followed a certain probability distribution, and then this model considered the influence of flight with continuous voyage. At the same time, the sensitivity of flight to time was used as the main line and the delay cost was taken as compensation. In addition, the improved genetic algorithm was used to solve the model. During the solution, the slot allocation process under multiple capacities was calculated concurrently. In each iteration, the data of slot allocation among various capacity scenarios were exchanged. After that, the objective functions were optimized using dynamic weight coefficients, so that the model can obtain the optimal allocation plan quickly and efficiently. Finally, the model was verified and simulated. Meanwhile, the specific quantitative indicators were introduced to quantitatively analyze the model. The result shows that the time slot allocated by proposed model in the case of uncertain capacity can reduce the delay percentage, the deterministic comprehensive cost and the comprehensive cost of uncertainty respectively. Thus, the rational utilization of time slot resource can be achieved.
引文
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[2] L Delgado, X Prats. Simulation of airborne ATFM delay and delay recovery by cruise speed reduction[J]. 1st SESAR Innovation days. Toulouse, France, 2011:1-7.
[3] 姜秀山,李习风. 单机场地面等待策略模型及应用[J]. 物流技术, 2011,(19):95-97.
[4] 王世豪,等. 多机场地面等待策略数学模型的研究[J]. 计算机技术与发展, 2014,(2): 6-9.
[5] L Corolli, G Lulli, L Ntaimo. The time slot allocation problem under uncertain capacity[J]. Transportation Research Part C Emerging Technologies, 2014,46(46):16-29.
[6] 许炎,等. 基于实测数据的终端区空中交通流特性分析[J]. 交通运输系统工程与信息, 2015,15(1):205-211.
[7] 徐肖豪,李雄. 航班地面等待模型中的延误成本分析与仿真[J]. 南京航空航天大学学报, 2006,38(1):115-120.