Two-stage scheduling optimization model for taxiways on the basis of time slot derivation
Jiyu Tang, Qigui Zhang, Guan Lian, Tao Wen
TL;DR
This paper introduces a two-stage scheduling model to optimize taxiway operations at airports, reducing costs and improving efficiency.
Contribution
A novel two-stage optimization framework with an improved ant colony algorithm for taxiway scheduling is proposed.
Findings
The framework reduces taxiing costs by 17.8% compared to no departure control.
The improved ant colony algorithm saves an average of USD 1,412.71 over traditional methods.
The model enhances both economic benefits and operational safety.
Abstract
The continuous growth in air traffic at civil airports has placed significant economic pressure on surface operations. Consequently, strategic adjustments to departure schedules and optimization of taxiing routes have become essential to reduce operational costs. This study proposes a two-stage optimization framework aimed at minimizing surface operation expenditures. In the first stage, a dynamic pushback slot control (DPSC) strategy is employed to regulate departure sequences. The second stage enables preplanning of taxi routes for both arriving and departing aircraft by optimizing the taxiway control threshold, thereby refining the pushback slots for departing flights. To support route planning, multiple taxiing configurations are generated for different departure intervals. To improve solution quality and mitigate ground conflicts, an improved ant colony algorithm (IACA)…
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Taxonomy
TopicsAir Traffic Management and Optimization · Aviation Industry Analysis and Trends · Advanced Aircraft Design and Technologies