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The use of models as decision-support tools for the development of airport infrastructure has been steadily growing. However, existing models still suffer from lack of integration and from severe limitations in their flexibility and usability. In this paper we propose two models for airport strategic planning on airside and landside, and discuss their connectivity. The models proposed are macroscopic in nature, and provide estimates of the capacity and performance of the airport quickly and with little effort. With the use of a common database, these models can be integrated and share the same set of data. It has been illustrated that in this way the, sometimes significant, interactions between airside and landside operations can be captured.

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One of the effects of the development of air traffic during recent years is the increase of congestion on major airports and their aprons, where ground handling operations take place. Efficiency and safety issues become important on the aprons. The\ud “Integrated Airport Apron Safety Fleet Management – AAS” project aims at setting\ud a decision support system for an efficient and safe management of apron traffic,\ud taking advantage of information gathered by “intelligent” vehicles equipped with on-\ud board positioning and monitoring systems. In this project, we optimize the\ud assignment of vehicles to apron operations. We present a mathematical formulation\ud of the problem and sketch a fast sequential heuristic, which provides efficient\ud assignments based on real-time data on position and status of vehicles and\ud operations. We then discuss how the procedure can reach good trade-offs between efficiency and robustness against unpredicted, but frequent, delays occurring in real-\ud time at airports. The proposed approach has been applied to a major European\ud airport (Berlin’s Tegel), leading to efficiency improvements and reduction of\ud expected delays due to handling operations