Abstract
Motivated by the challenges encountered in airport passenger terminal planning, we study a multistage stochastic programming model based on a multi commodity flow network representation of the whole airport terminal. As delays in passageways and processing stations of airport terminal different uncertain natures, they are modeled separately and then integrated. In this study, we consider the airport terminal capacity planning problem as a whole. In this regard, we first derive time functions to approximate maximum delays in passageways and processing stations of an airport terminal. Demand uncertainty is considered as a dynamic stochastic data process during the planning horizon which is modeled as a scenario tree. Based on available data for the Imam Khomeini International Airport like passenger demands, a multi-stage stochastic programming model is proposed which is full recourse for demand scenarios. Numerical results indicate that the solution to the multi-stage model is far superior to the optimal solution to the mean-value deterministic and the three-stage stochastic models.
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