调度(生产过程)
运筹学
国际机场
地铁列车时刻表
排队论
计算机科学
工程类
运输工程
运营管理
计算机网络
操作系统
作者
Nikolas Pyrgiotis,Amedeo R. Odoni
出处
期刊:Transportation Science
[Institute for Operations Research and the Management Sciences]
日期:2015-01-12
卷期号:50 (1): 150-165
被引量:67
标识
DOI:10.1287/trsc.2014.0564
摘要
Scheduling limits have become commonplace at congested airports throughout the world. This paper describes, first, a demand smoothing (DS) optimization model that generates a new flight schedule at busy U.S. airports in response to the introduction of scheduling limits. Given an existing schedule that has been created through the airlines’ scheduling choices, the model produces a feasible modified schedule that obeys the scheduling limits specified for an airport without canceling any flights. At the same time, the model respects all aircraft itineraries, so that aircraft fly their original daily routes through the airport network. In addition, it preserves all passenger connections, in the sense that any connecting passenger will be able to connect between exactly the same two flights under the modified schedule as under the existing one. We then demonstrate, through a detailed example based on operations at the hub airport of Newark Liberty International (EWR), an approach that combines the DS model with a new special-purpose network queuing model to estimate both the local and nationwide effects of alternative scheduling limits at a major airport. We examine the relationship between the scheduled demand and the capacity at EWR to identify plausible scheduling limits that may have a significant impact on delays. The DS model shows that, with a small schedule displacement of 30 minutes or less for any flight during the day, it is possible to obtain a feasible schedule that obeys slot limits as low as the airport’s capacity under Instrument Flight Rules. We find that the local delay savings that would result from introducing such scheduling limits at EWR can be of the order of 20% for arrivals and 50% for departures on busy days; we may also expect a reduction of 20% in delays propagated from EWR to the rest of the U.S. network of airports.
科研通智能强力驱动
Strongly Powered by AbleSci AI