# Stand and Gate Allocation The most studied optimization problem in airport operations. Assign each flight to a parking position (stand) given constraints on aircraft size compatibility, airline terminal preferences, passenger connection times, ground equipment access, and temporal overlap. Two types of stands: contact stands (connected to terminal via jet bridge, premium, limited supply) and remote stands (on the apron, require bus transfer, lower passenger experience). The optimization objective: maximize contact stand usage while minimizing passenger walking distance, towing operations, and ground congestion. This is a combinatorial optimization problem, not a continuous one. The solution space is discrete and the constraints are hard (two wide-bodies cannot physically occupy the same stand). Many airports still solve it manually or with basic rule-based systems. First-come-first-served is common for ground vehicle dispatching, which leaves significant efficiency on the table. The problem gets harder in real time. Flights arrive late, depart early, diversions happen, weather closes runways. A plan that was optimal at 6am may be useless by 9am. This is why static allocation (done the night before) needs to give way to dynamic reallocation (continuous replanning during the day). See [[Disruption Management in Airport Operations]]. Multi-Aircraft Ramp System (MARS) stands add another layer: one large stand can be split to serve two smaller aircraft, or combined for one large aircraft. This doubles the combinatorial complexity. The academic literature uses MILP (Mixed Integer Linear Programming) and [[Constraint Programming]] formulations. In practice, exact solvers work for small instances but heuristic methods (genetic algorithms, local search) are needed for full-scale airport operations. Related: [[Aircraft Turnaround]], [[Ground Support Equipment Scheduling]], [[Simulation-Based Optimization]], [[Constraint Programming]], [[Airport Operations MOC]] --- Tags: #deeptech #firstprinciple