Multi-Objective Air Traffic Flow Management Through Lexicographic Optimisation

Air transportation is challenged by rising air traffic demand and limited capacity in airspace and airports. This demand-capacity balance problem is inherently multi-objective, with sometimes conflicting goals. These objectives include minimising air traffic flow management delays, mitigating the operational impacts of reactionary delays, reducing environmental impact, etc. Additionally, specific regions of the network at particular times, referred to as “spots” in this paper, must be considered when they exhibit specific characteristics. This paper introduces a comprehensive mixed-integer programming model for the demand-capacity balance problem, addressing its multi-objective nature through a lexicographic approach. In this approach, the multiple objectives are ranked by importance, and the problem is solved sequentially to minimise each objective without exceeding the optimal value of the previous objectives. The versatility and effectiveness of the lexicographic approach in air traffic flow management are demonstrated using historical air traffic data over France and Spain.