Published Paper Details:

The airport stand assignment problem (ASAP) involves the allocation of arriving and departing aircraft to available parking stands (gates) while respecting operational and spatial constraints. An effective stand assignment significantly influences airport efficiency, passenger comfort, and airline performance. This research develops a mixed-integer programming (MIP) model to minimize total passenger walking distance, thereby improving transfer efficiency and traveler experience. The paper reviews recent studies (2020-2024) on gate and stand assignment problems, emphasizing passenger-centric optimization objectives. The proposed model uses binary decision variables representing flight-stand allocations, subject to exclusivity and non-overlapping temporal constraints. The optimization is implemented using Python's PuLP library with the CBC solver on synthetic datasets that simulate flight schedules and passenger volumes. Results demonstrate that minimizing walking distances yields considerable improvements over random or naive assignment strategies. Finally, scalability, trade-offs, and future research directions--such as multi-objective formulations and robust optimization--are discussed.