A slot allocation optimization method for regional multi-airport integrating airport fairness and airline fairness

Slot allocation in Multi-Airport Systems (MAS) is traditionally viewed as a two-dimensional trade-off between operational efficiency and inter-airline fairness. This perspective, however, is inadequate for managing complex regional airport networks, often leading to structural imbalances where core hubs are overburdened while regional airports remain underutilized. This paper introduces a critical third dimension: strategic airport fairness. An innovative tri-objective integer programming model is proposed, incorporating the strategic fairness among heterogeneous airports as an objective alongside minimizing total displacement and maximizing airline fairness. The framework is defined through two novel metrics: airline tolerance to capture micro-level flight satisfaction, and airport heterogeneity weights to quantify macro-level strategic priorities. Additionally, a base airline priority factor is introduced to address the influence of airline dominance. A customized bi-iterative ε-constraint algorithm is designed to generate the Pareto optimal frontier and identify the balanced solution. Through a case study on China’s Pearl River Delta airport system, results demonstrate that the proposed framework improves both airline and airport fairness with limited efficiency loss. Moreover, sensitivity analyses on airline tolerance and base airline priority provide operational guidelines, and adjusting airport heterogeneity weights can significantly mitigate congestion at hubs to foster balanced regional development. This work provides a novel decision-making framework and practical policy insights for achieving more sustainable and collaborative air traffic management in multi-airport regions.