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Managing severe airspace flow programs: The Airlines' side of the problem

机译:管理严格的空域流动计划:航空公司的问题所在

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摘要

This paper presents a heuristic-based approach for minimizing airlines' schedule disruptions and operation costs associated with severe airspace flow programs. It considers primary decisions made by flight dispatchers such as flight slot substitution and rerouting outside the boundaries of the flow-constrained area. A two-stage heuristic is developed. In the first, a linear approximation of the problem is used to screen inefficient routing and slot substitution alternatives. The second stage examines possible solution improvements through trading flight assignments for every pair of conflicting routes. A genetic algorithm is developed and used to benchmark the performance of the two-stage heuristic. In the algorithm, flight route and slot allocation schemes are modeled as chromosomes. The fitness of these chromosomes measures the magnitude of schedule disruption and overall operating cost. A set of experiments that compare the performance of the two heuristics considering airspace flow programs with different levels of severity is presented.
机译:本文提出了一种基于启发式的方法,以最大程度地减少航空公司与严重空域流量计划相关的航班时刻表中断和运营成本。它考虑了由飞行调度员做出的主要决定,例如航班位置的替换和在流量受限区域边界之外的重新路由。开发了两阶段启发式方法。首先,使用问题的线性近似来筛选效率低下的路由和时隙替换方案。第二阶段研究通过对每对冲突的航线进行航班分配交易来解决可能的解决方案改进。开发了一种遗传算法,并将其用于对两阶段启发式算法的性能进行基准测试。在该算法中,将飞行路线和时隙分配方案建模为染色体。这些染色体的适合度可衡量计划中断的程度和总体运营成本。提出了一组比较两种启发式算法性能的实验,这些算法考虑了不同严重程度的空域流动程序。

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