Using Markov Decision Processes to Solve Stochastic Gate Assignment Problem

Airport traffic often undergoes some random disruptions, which have to be considered to ensure operational flight-gate assignments. Inadequate assignment of gates may result in flight delays that happen in airport operations and must be taken into account. Here, we are using the original algorithm, based on Markov decision process (MDP) to solve the gate assignment problem (GAP) under uncertainty; we include stochastic parameters that depend on probabilities to express fluctuations in flight operations. The use of MDP for modeling will provide for airport controllers a robust solution for the GAP that takes in consideration possible flight delays. This paper gives the corresponding model, which includes strict constraints of the GAP and other soft constraints like choice preferences of gates. We give experimental results on a sample of real data to demonstrate the feasibility and efficiency of our approach.