Impact Analysis of Demand Management on Runway Configuration in Metroplex Airports

Abstract

Congestion in airports and metroplexes is increasingly becoming a key bottleneck in the global air transport system. It is largely due to inefficient utilization of runway resources and its consequences of imbalance between demand and capacity. Existing studies mainly focus on runway configuration in a single airport system, and little consideration is given to the impact of demand management on runway configuration in metroplexes. Therefore, this paper proposes a methodology and assessment framework for runway configuration with a focus on the exploitation of multiple active runways in metroplex airports. The primary innovation is an integrated runway configuration management formulation with air traffic demand management options. The first is static and dynamic runway configuration management models featuring three optimization objectives, four cases of demand-capacity imbalance, three air traffic demand management options and three assessment scenarios, for eleven priority settings. The second is an efficient multi-objective evolutionary algorithm with a mechanism of objective-guided individual selection, which can obtain close-to optimal solutions with a very low computational cost within 6 seconds. Computational experiments for the real-world case of the Shanghai metroplex airports show that, the inducing strategy of minimizing the total number of adjusted flights is the best mechanism for making satisfactory tradeoffs among multiple objectives in dynamic runway configuration. The proposed model reduces the total number of adjusted flights by an average of 36% compared with the baseline static runway configuration management. Furthermore, unlike the conventional approach of giving priority to arriving aircraft, a higher priority for departures is more effective in enhancing the performance of runway systems and reducing the number of adjusted flights. The proposed framework can be applied at pre-tactical (e.g., one-day planning) as well as tactical (e.g., several-hours rolling horizon) levels.

Optimal Sequencing of Arrival Flights at Metroplex Airports: A Study on Shared Waypoints Based on Path Selection and Rolling Horizon Control

“…This strategy was formulated to address the challenges associated with airport group flight delays and air traffic congestion. In 2020, Yin et al [15] proposed a runway allocation and ranking method focusing on the utilization of multiple airports and multiple runways in an airport group based on the impact of runway configurations of airports in an airport group on traffic flow management. Liu Jixin et al [16] designed an elite retention genetic algorithm and a fast non-dominated sorting genetic algorithm with elite strategy, and established a collaborative approach flight sorting model based on air traffic density.…”