ASPaeroFlow: Decomposition Heuristics for Joint Air Traffic Flow & Capacity Management
2026-08-10 • Artificial Intelligence
Artificial Intelligence
AI summaryⓘ
The authors looked at how air traffic flow and airspace design are usually planned separately, which causes some problems because they depend on each other. They created a new approach called ASPaeroFlow that tries to plan both together using a mix of smart shortcuts and precise calculations. Testing showed their method works faster than exact methods but better than simple ones, and planning airspace design carefully has a bigger effect on results than just changing traffic flow. This helps make air traffic management more efficient and realistic.
Air Traffic Flow Management (ATFM)Dynamic Airspace Configuration (DAC)Air Traffic Flow and Capacity Management (ATFCM)Heuristic algorithmsAnswer Set Programming (ASP)OptimizationComputational complexityInstance-space decompositionSequential optimizationAblation study
Authors
Alexander Beiser, Markus Hecher, Nysret Musliu, Georg Trausmuth, Stefan Woltran
Abstract
While mathematical models act as vital decision support systems for operational Air Traffic Flow and Capacity Management (ATFCM), existing approaches isolate Air Traffic Flow Management (ATFM) from Dynamic Airspace Configuration (DAC). This separation introduces an unresolved circular dependency between fixed-demand and fixed-capacity assumptions. Although joint optimization resolves this gap, the enlarged search space renders exact models computationally intractable for medium- to large-scale instances. To bridge this gap, we propose ASPaeroFlow: a heuristic for the joint ATFCM; it combines instance-space decomposition heuristics with a local exact approach using Answer Set Programming. We benchmark ASPaeroFlow from small to industry-sized instances and compare it with exact and alternative approaches. The results indicate that (1) the heuristic provides a computational middle ground between exact methods and operational baselines; (2) simultaneous optimization can outperform sequential optimization on joint ATFCM; and (3) an ablation study indicates that DAC has a larger impact on solution quality than flow measures.