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Short-term En route Air Traffic Flow Management Under Departure and Wind Uncertainties with a Heuristic and Greedy Solution Approach

机译:启发式和贪婪求解方法在起飞和风不确定性下的短期途中空中交通流量管理

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The importance of short-term air traffic flow management can never be depreciated due to the associated demand uncertainty which is caused by the dynamicity in the air transportation systems. Ideally, the flight plans require frequent fine-tuning depending on the dynamic network changes such as flight time deviations, weather conditions, etc.. Motivated by this, the paper incorporates the effect of departure time uncertainty and wind uncertainty in short-term flight routing and scheduling. The en route capacities are utilized while ensuring safety in terms of maintaining required in-trail-separation between aircraft, avoiding capacity violations as well as merging conflicts due to uncertainty of demand. The proposed model effectively manages the uncertainty in the network by utilizing short-term planning horizons and further, more accurate real-time wind forecast data are incorporated in optimizing the flight schedules. To generate flight schedules with a less time-complexity, we use a heuristic approach with parallel computation while decomposing the problem into maximum independent sets. The proposed model is experimentally validated for the applicability via realistic air traffic data.
机译:由于空中运输系统的动态性导致相关的需求不确定性,因此短期空中交通流量管理的重要性永远不会降低。理想情况下,根据动态网络的变化(例如飞行时间偏差,天气状况等),需要对飞行计划进行频繁的微调。出于此目的,本文将出发时间不确定性和风不确定性的影响纳入了短期飞行路线中和调度。在确保飞机之间所需的轨内间隔安全性的同时,在使用途中容量的同时确保了安全性,避免了容量违规以及由于需求不确定性导致的合并冲突。所提出的模型通过利用短期计划范围有效地管理了网络中的不确定性,此外,在优化飞行计划中还结合了更准确的实时风能预测数据。为了生成时间复杂度较小的航班时刻表,我们使用启发式方法进行并行计算,同时将问题分解为最大的独立集合。通过实际的空中交通数据,对所提出的模型进行了实验验证,以验证其适用性。

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