考虑多机场延误传播的航空公司地下延误计划的航班重新调度

IF 3.3 2区 工程技术 Q2 TRANSPORTATION
Jiyeon Lee, Ilkyeong Moon
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引用次数: 0

摘要

本研究的目的是为航空公司的利润重新安排航班,以对应于机场容量的变化。在地面延误计划(GDP)的情况下,机场可以容纳的航班数量会减少。我们建立了一个混合整数线性规划(MILP)模型来重新安排航班。为了处理未来的不确定性,MILP模型被分为两个版本。在GDP再次变化的情况下,一个最优模型得到了每种情况下的解。随机模型解得到所有情形下期望代价最小的解。所有航班均连接始发机场和目的地机场,一架飞机可用于多个航班。因此,我们不仅考虑同一机场内的延迟传播,而且考虑来自其他机场的延迟传播,将设置扩展到同时包括多个机场。由于本研究的目的是使航空公司的运营成本最小化,我们也考虑了与航空公司资源相关的成本,如飞机和机组人员。进行了相关实验,包括两种建议版本的比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flight rescheduling of an airline underground delay program considering delay propagation in multiple airports
The purpose of this study is to reschedule flights for an airline's profit to correspond to the airport’s changed capacity. In the event of a ground delay program (GDP), the number of flights the airport can accommodate is reduced. We formulated a mixed-integer linear programming (MILP) model to reschedule flights. The MILP models were divided into two versions to handle the uncertainty of the future. In scenarios in which the GDP is changed again, an optimal model obtains solutions for each scenario. The stochastic model solution obtains a minimizing expectation cost of all scenarios. All flights are connected to both the origin and destination airports, and one aircraft may be used for more than one flight. Therefore, we considered delay propagation not only within the same airport but from other airports by extending the setup to include several airports at once. Because the objective of this study is to minimize the operation cost of airline, we also considered costs associated with airline resources such as aircrafts and crews. Related experiments were conducted including comparison between two suggested versions.
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来源期刊
Transportmetrica B-Transport Dynamics
Transportmetrica B-Transport Dynamics TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
5.00
自引率
21.40%
发文量
53
期刊介绍: Transportmetrica B is an international journal that aims to bring together contributions of advanced research in understanding and practical experience in handling the dynamic aspects of transport systems and behavior, and hence the sub-title is set as “Transport Dynamics”. Transport dynamics can be considered from various scales and scopes ranging from dynamics in traffic flow, travel behavior (e.g. learning process), logistics, transport policy, to traffic control. Thus, the journal welcomes research papers that address transport dynamics from a broad perspective, ranging from theoretical studies to empirical analysis of transport systems or behavior based on actual data. The scope of Transportmetrica B includes, but is not limited to, the following: dynamic traffic assignment, dynamic transit assignment, dynamic activity-based modeling, applications of system dynamics in transport planning, logistics planning and optimization, traffic flow analysis, dynamic programming in transport modeling and optimization, traffic control, land-use and transport dynamics, day-to-day learning process (model and behavioral studies), time-series analysis of transport data and demand, traffic emission modeling, time-dependent transport policy analysis, transportation network reliability and vulnerability, simulation of traffic system and travel behavior, longitudinal analysis of traveler behavior, etc.
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