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An integrated scenario-based approach for robust aircraft routing, crew pairing and re-timing

机译:基于方案的集成方法,可实现可靠的飞机路线安排,机组配对和重新定时

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For reasons of tractability, the airline scheduling problem has traditionally been sequentially decomposed into various stages (e.g. schedule generation, fleet assignment, aircraft routing, and crew pairing), with the decisions from one stage imposed upon the decision-making process in subsequent stages. Whilst this approach greatly simplifies the solution process, it unfortunately fails to capture many dependencies between the various stages, most notably between those of aircraft routing and crew pairing, and how these dependencies affect the propagation of delays through the flight network. In Dunbar et al. (2012) [9] we introduced a new algorithm to accurately calculate and minimize the cost of propagated delay, in a framework that integrates aircraft routing and crew pairing. In this paper we extend the approach of Dunbar et al. (2012) [9] by proposing two new algorithms that achieve further improvements in delay propagation reduction via the incorporation of stochastic delay information. We additionally propose a heuristic, used in conjunction with these two approaches, capable of re-timing an incumbent aircraft and crew schedule to further minimize the cost of delay propagation. These algorithms provide promising results when applied to a real-world airline network and motivate our final integrated aircraft routing, crew pairing and re-timing approach which provides a substantially significant reduction in delay propagation.
机译:出于可处理性的原因,传统上将航空公司的调度问题依次分解为多个阶段(例如,调度表生成,机队分配,飞机路线选择和机组人员配对),其中一个阶段的决策会强加于后续阶段的决策过程中。尽管此方法大大简化了解决过程,但不幸的是,它未能捕获各个阶段之间的许多依赖关系,最显着的是飞机路线选择和机组人员配对之间的依赖关系,以及这些依赖关系如何影响通过飞行网络传播延迟。在邓巴等人。 (2012)[9],我们引入了一种新算法,可以在集成了飞机路线和机组配对的框架中准确计算并最小化传播延迟的成本。在本文中,我们扩展了Dunbar等人的方法。 (2012)[9]通过提出两种新算法,通过结合随机延迟信息实现了延迟传播减少的进一步改进。我们还提出了一种启发式方法,与这两种方法结合使用,能够重新调整现有飞机和机组人员的时间安排,以进一步最小化延迟传播的成本。当将这些算法应用于现实世界的航空公司网络时,它们提供了令人鼓舞的结果,并激发了我们最终集成的飞机路线,机组配对和重新计时方法,从而大大减少了延迟传播。

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