Air trips keep increasing as the world population and its needs keep growing. In order to keep up with the increasing number of flights, airports must ensure that their operations efficiently respond to the arising needs considering both the passenger experience and their economic viability. One way to achieve this is by optimizing the airport operations through revenue maximization under passenger comfort restrictions inside the airport. This study presents an original mixed-integer linear programming model (MILP) which combines the gate assignment problem with passenger behavior modeling. A survey was performed to collect relevant information for the modelling of passenger money spending behavior , leading to the estimation of passenger probability (through Discrete Choice Modelling) to making purchases of certain levels at the terminal according to their flight type (departure, arrival, transfer). The proposed gate assignment solution increases airport non-aeronautical revenues at Lisbon Airport by matching flights and passenger gate categories to the most profitable gates, considering the proximity to the retail area, the walking distance needed to get to a gate in a specified time-horizon and the operational constraints of the airport. The case study results showed an 8% and 12.2% increase in revenues corresponding to 1732.7€ and 2967.3€ in half-an-hour time slots from 5pm to 6pm, respectively.

Gate Assignment Problem (GAP), Discrete Choice Modelling (DCM), airport management, Mixed-integer Linear Programming (MILP)