Integrated Scheduling Model for Arrivals and Departures in Metroplex Terminal Area

TL;DR

This paper presents a bi-level optimization model for collaborative flight scheduling in metroplex terminal areas, significantly reducing delays and improving efficiency using genetic algorithms, demonstrated through a Shanghai case study.

Contribution

It introduces a novel adaptive bi-level optimization model for integrated arrival and departure scheduling in metroplexes, solved with genetic algorithms, outperforming traditional methods.

Findings

Reduces arrival delay by 51.52%

Cuts departure delay by 18.05%

Enhances scheduling efficiency over traditional approaches

Abstract

In light of the rapid expansion of civil aviation, addressing the delays and congestion phenomena in the vicinity of metroplex caused by the imbalance between air traffic flow and capacity is crucial. This paper first proposes a bi-level optimization model for the collaborative flight sequencing of arrival and departure flights in the metroplex with multiple airports, considering both the runway systems and TMA (Terminal Control Area) entry/exit fixes. Besides, the model is adaptive to various traffic scenarios. The genetic algorithm is employed to solve the proposed model. The Shanghai TMA, located in China, is used as a case study, and it includes two airports, Shanghai Hongqiao International Airport and Shanghai Pudong International Airport. The results demonstrate that the model can reduce arrival delay by 51.52%, departure delay by 18.05%, and the runway occupation time of departure flights by 23.83%. Furthermore, the model utilized in this study significantly enhances flight scheduling efficiency, providing a more efficient solution than the traditional FCFS (First Come, First Served) approach. Additionally, the algorithm employed offers further improvements over the NSGA II algorithm.