Dynamic Demand-Capacity Balancing for Air Traffic Management Using Constraint-Based Local Search: First Results

TL;DR

This paper presents a constraint-based local search approach to balance air traffic demand and capacity in European airspace, demonstrating feasibility and improvements with projected 2030 flight plans.

Contribution

It introduces a novel application of constraint-based local search for demand-capacity balancing in air traffic management, focusing on ground holding as a demand adjustment method.

Findings

Feasible demand-capacity balancing with minimal delays.

Significant improvement in demand-capacity alignment.

Effective modeling of air traffic constraints.

Abstract

Using constraint-based local search, we effectively model and efficiently solve the problem of balancing the traffic demands on portions of the European airspace while ensuring that their capacity constraints are satisfied. The traffic demand of a portion of airspace is the hourly number of flights planned to enter it, and its capacity is the upper bound on this number under which air-traffic controllers can work. Currently, the only form of demand-capacity balancing we allow is ground holding, that is the changing of the take-off times of not yet airborne flights. Experiments with projected European flight plans of the year 2030 show that already this first form of demand-capacity balancing is feasible without incurring too much total delay and that it can lead to a significantly better demand-capacity balance.