A scenario-based optimization approach to robust estimation of airport apron capacity

Apron capacity is critical to airport ground operation, which is defined as its capability to accommodate aircraft in a unit of time. With precise estimation of apron capacity, airport operators can utilize gate resource more efficiently and optimize airport daily operation, thus reducing flight delays and guaranteeing operation safety. However, uncertainties such as weather and taxiing time would affect the robustness of the estimation result. To address this problem, a scenario-based optimization approach to robust estimation of apron capacity is proposed. Firstly, an envelope model is established to demonstrate dynamic apron capacity based on arrival-departure shares. Then, the envelope is formulated as a chance-constrained optimization program(C-COP), while a predefined probabilistic guarantee is adopted to ensure the robustness of the envelope. Furthermore, the C-COP is converted to standard convex optimization problem via scenario approach and solved approximately. Case study, which uses the real data provided by the Beijing Capital International Airport(BCIA), suggests the practicability of the proposed method and the robustness of the estimated envelope.