Abstract
Airport congestion and delay are subject to many
sources of uncertainty including daily variations of airport
capacity and demand. Taking advantage of interconnections
among airports serving the same metropolitan region help
alleviate airport congestion by utilizing excess resources in other
airports. This study proposes to shift flights between airports in
the same Multiple Airport Region (MAR) to improve regional
operational performance. We consider such flight shifting at
strategic level. If one airport is consistently congested and another
has excess capacity, flights can be reassigned to less congested
airport to reduce delay. We identify US MARs based on temporal
distance between airports, and characterize spatial-temporal
patterns of airport capacity variation within MAR. Then the
stochastic flight shift model is formulated as a Mixed Integer
Linear Programming (MILP) model to optimize the average total
delay and reassignment cost of the flight schedule in the MAR
among all possible capacity scenarios. Since the stochastic flight
shift model is computationally expensive with high flight traffic
intensity, we solve the model in decomposed flight batches. The
proposed methodology is applied to New York MAR. Results show
that by reassigning flight landing airport and time, the flight delay
in the New York MAR could be significantly reduced.
sources of uncertainty including daily variations of airport
capacity and demand. Taking advantage of interconnections
among airports serving the same metropolitan region help
alleviate airport congestion by utilizing excess resources in other
airports. This study proposes to shift flights between airports in
the same Multiple Airport Region (MAR) to improve regional
operational performance. We consider such flight shifting at
strategic level. If one airport is consistently congested and another
has excess capacity, flights can be reassigned to less congested
airport to reduce delay. We identify US MARs based on temporal
distance between airports, and characterize spatial-temporal
patterns of airport capacity variation within MAR. Then the
stochastic flight shift model is formulated as a Mixed Integer
Linear Programming (MILP) model to optimize the average total
delay and reassignment cost of the flight schedule in the MAR
among all possible capacity scenarios. Since the stochastic flight
shift model is computationally expensive with high flight traffic
intensity, we solve the model in decomposed flight batches. The
proposed methodology is applied to New York MAR. Results show
that by reassigning flight landing airport and time, the flight delay
in the New York MAR could be significantly reduced.
| Original language | English |
|---|---|
| Publication status | Published - 2022 |
| Event | International Conference on Research in Air Transportation 2022 - Tampa, Florida, USA, Tampa, United States Duration: 19 Jun 2022 → … https://www.icrat.org/previous-conferences/10th-international-conference/ |
Conference
| Conference | International Conference on Research in Air Transportation 2022 |
|---|---|
| Country/Territory | United States |
| City | Tampa |
| Period | 19/06/22 → … |
| Internet address |
Keywords
- flight diversion
- Multiple Airport Region (MAR)
- capacity scenarios
- scenario-based stochastic programming
- flight rescheduling
- multimodal scheduling