航空延误外文翻译

1、通过计划的重新分配减少航班延误波及范围(节选) 摘要：在过去的几年中，空中交通拥挤、恶劣天气、机器故障以及其余的各种问题使航班时刻计划形成了大范围的中断，于是客运航班的延误受到了越来越多的关注。而航班延误还会产生的更大问题，即每个航班延误可以影响并阻碍下一航班的正常运行，因为它必须等待延误航班的机组人员直至问题处理好。一个根本性的冲突则更加剧了这种潜在的延误传播：航班计划的时间表通常是有缺陷的，并不能满足人们的需求。这意味着错过了利用昂贵却又易腐的资源的机会，而懈怠的计划是行动中吸取教训的关键点。在这篇文章中，我们研究了如何通过重新分配现有的缺陷计划来减少航班延误的传播，在计划过程中对航班时刻

2、表做出轻微的修改而又不改变原有的机组人员调度决策。在美国主要运营商的数据基础上，我们提出了相应的计算结果，并表明可以在不增加计划成本的情况下取得经营业绩的显著改善。介绍航空公司的计划是由几个昂贵而有限的资源组成的，如飞机和机组人员。这些资源通过在各个航班中的转移将整个网络中的航班都联系起来。然而，使事情变得复杂的是即使每个航班需要各种类型的资源，但是个人资源并不一定非要留在网络中相连。例如，飞机和机组人员可能一起被分配到一个特定点的时间表的飞行中，但随后也可各自分配给不同的航班。这种联系可以衍生出潜在的航班延误传播。例如，如果由于所分配的航班的飞机机械故障，一个航班出现延误，那么随后的飞行也可

3、能被延迟，因为它正在等待那个归航的飞机。事实上，资源是可以“分裂”这种复合结果的。在图一中（3中有详细解释），我们可以看到一个单一的航班延误也可以波及其他航班的延迟。在过去5年中，航班延误的发生频率大幅增加（见图二）。这些航班延误所造成的对成本的影响是非常大的，其中包括多余的燃料成本（怠速飞机），工作人员的加班工资成本、重新等待的顾客服务成本以及由延迟产生的客户的流失。 进一步来说，航空运输协会估计在2006年就有1.165亿分钟的延误，给美国航空业的运营成本直接增加了77亿美元的负担（见表1）。 航班延误的来源有很多，如机械故障、天气延误、地面的方案以及空中交通挤塞。但是，从这些首次延迟而波

4、及到的二次延误也相当多。例如，在2007年11月，在美国各大机场延误超过三分之一结果仅是因为一架迟到的飞机（图3）。此外，从规划的角度来看，疏忽通常被视为消极的（如一种资源的浪费），而由这个事实可能会产生一种自然而然的冲突。但是从运营的角度来看它也可以看成是积极的（如，一个吸取教训的机会而不是让延误波及更广）。因此，我们研究的重点是如何将操作问题与延误传播综合考虑在航空公司的规划过程之中。在这项研究中，一个关键挑战是如何在计划成本（假设航空公司的所有航班都如期运行而无中断的计划成本）和运营成本（由于航班延误而修改后的计划的实际的成本）之间进行取舍。两个不同的计划不同的计划成本，而我们难以确定这

5、两项计划中哪个将得到更好地运作。此外，我们也难以确定运营的改善是否比计划成本的增加更为重要。如果在计划范围内（通常是按天算），每个计划都将要修改很多次，而潜在的延误有可能会在任何一天发生，也有可能不发生。因此，即使我们确定了稳固的指标，并量化这些指标值（即改善这些指标将会需要运营商承担多大的计划成本），这是一个具有挑战性的研究，而且本身并未得到充分解决。事实上，对于大多数运营商来说，规划和操作流程的作用是相互独立的，每个小组的动机都是与不同的目标相对应，只会使问题进一步恶化。因此，我们建议想一个办法作为中间步骤，在不增加计划成本的情况下，仍然可以提高经营业绩。具体来说，我们建议修改航班起飞时间

6、，以便重新分配现有的网络中的资源浪费。通过重新定时航班，浪费的资源可以重新分配到这些最容易延误且易引起延迟传播的航班。我们限制航班的时间窗口来重新制定时间计划，以便保持现有的收入预测。此外，我们限制航班时间计划的同时不改变那些仍然可行的船员配对成本。最后，我们需要保持同一架飞机的飞行。我们的计算结果是根据美国一家主要的运营商的数据而来的，事实证明，这种做法可以使得预期的延迟传播有明显的改善，而又没有任何相关计划成本的增加。 我们研究的主要贡献是所开发的模式可以减少运营过程中的延迟传播，而且没有任何计划成本的增加。我们提出的模型考虑到了引起延迟传播的各种原因，如飞机本身、机组成员、与乘客的联系以

7、及其他共享资源。通过演示这些模型的完整性是可以放宽尺度的（即该模型可以得到线性解决，而不是从整体和程序上解决），我们可以在不牺牲别的资源的情况下考虑到所有的后续影响。本文概述如下：在第2节中，我们将回顾相关文献，并提出了一些重新分配浪费的模式。在第3节中，我们展示了一个仿真模型以帮助验证结果。具体的计算实验和分析则在第4节中讲述。最后，第5节则得出文章的结论并为今后的研究提供了相应的建议。译自：杂志或书籍: Shervin AhmadBeygi, Amy Cohn and Marcial Lapp. Decreasing Airline Delay Propagation By Re-Allo

8、cating ScheduledSlackJ. Alfred P. Sloan基金会行业研究年度会议，2008年4月。原文：Decreasing Airline Delay Propagation By Re-Allocating Scheduled SlackShervin AhmadBeygi, Amy Cohn and Marcial LappUniversity of MichiganApril 4, 2008AbstractPassenger airline delays have received increasing attention over the past several

9、 years as airspace congestion, severe weather, mechanical problems, and other sources cause substantial disruptions to a planned flight schedule. Adding to this challenge is the fact that each flight delay can propagate to disrupt subsequent downstream flights that await the delayed flights aircraft

10、 and crew. This potential for delays to propagate is exacerbated by a fundamental conflict: slack in the planned schedule is often viewed as undesirable, as it implies missed opportunities to utilize costly perishable resources, whereas slack is critical in operations as a means for absorbing disrup

11、tion. In this paper, we show how delay propagation can be reduced by redistributing existing slack in the planning process, making minor modifications to the flight schedule while leaving the original fleeting and crew scheduling decisions unchanged. We present computational results based on data fr

12、om a major U.S. carrier, showing that significant improvements in operational performance can be achieved without increasing planned costs.1 IntroductionAirline plans are made up of several costly and constrained resources such as aircraft and crews. These resources link flights across the network,

13、with each resource flowing from one flight to another. Adding to this complexity is the fact that although each flight needs each type of resource, individual resources do not necessarily stay linked throughout the network. For example, an aircraft and crew might be assigned to a common flight at a

14、particular point in the schedule, but assigned to separate flights at a later point.One ramification of this linkage is the potential for delays to propagate. If one flight is delayed (for example, because of a mechanical problem with the aircraft assigned to that flight), then a subsequent flight m

15、ight also be delayed because it is awaiting that inbound aircraft. The fact that resources can “split” compounds this. In Figure 1(explained in detail in 3) we see how a single flight delay can spread to delay several other flights as well.Airline delays have increased substantially in the past 5 ye

16、ars (see Figure 2). The cost impact of these delays is substantial, including excess fuel costs (from idling aircraft), overtime pay for crew members, costs associated with re-accommodating misconnecting passengers, as well as the lost productivity of delayed passengers.Furthermore, the Air Transpor

17、t Association has estimated that there were a total of 116.5 million delay minutes in 2006, resulting in a $7.7 billion increase in direct operating costs to the U.S. airline industry (see Table 1).There are many sources for flight delays, such as mechanical problems, weather delays, ground-hold pro

18、grams, and air traffic congestion. But the secondary delays that propagate from such root delays are also quite substantial. For example, in November 2007, more than one-third of the delays at major U.S. airports were the result of a late-arriving aircraft (Figure 3). Furthermore, there is a natural

19、 conflict stemming from the fact that slack is typically viewed as negative from the planning perspective (i.e. a waste of resources), but as positive from the operational perspective (i.e. an opportunity to absorb disruption rather than allowing it to propagate). The focus of our research is theref

20、ore on determining how to incorporate the operational issues associated with delay propagation into the airline planning process.A key challenge in this research is the difficulty in trading off between planned costs (the cost of an airline plan under the assumption that all flights occur as schedul

21、ed and without disruption) and operational costs (the realized cost associated with the modified plan that is implemented in response to disruptions). Given two different plans with varying planned costs, it is difficult to determine which of the two plans will perform better operationally. Furtherm

22、ore, it is also difficult to determine whether improvements in operational performance outweigh increases in planned costs, given that the plan will be operated several times (often, daily) over the planning horizon, and that potential disruptions may or may not occur during any given day. Thus, eve

23、n determining metrics for “robustness”, and then quantifying the value of these metrics (i.e. how much planned cost a carrier should be willing to incur to improve these metrics), are challenging research topics themselves that have yet to be adequately solved. The fact that the planning and operati

24、ons processes are functionally separate within most carriers, with each groups incentives aligned with different objectives, only serves to exacerbate the problem.We therefore propose, as an interim step, to develop an approach that does not increase planned costs, but can nonetheless improve operat

25、ional performance. Specifically, we propose to modify flight departure times so as to re-allocate the existing slack in the network. By re-timing flights, slack can be re-distributed to those flight connections that are most sensitive to disruption and thus delay propagation. We limit the time windo

26、ws in which flights can be re-timed, so as to maintain existing revenue projections. Furthermore, we restrict flight re-timings such that crew pairings remain feasible and do not change in cost. Finally, we require that the same aircraft rotations be maintained. Our computational results, based on data from a major U.S. carrier, demonstrate that this approach leads to significant improvements in expected delay propagation without any associated increase in planned c