The problem of assigning gates to aircraft that are due to arrive at an airport is one that involves a dynamic task environment. Airport gates can only be assigned if they are currently available, but deciding which gate to assign to which flight also involves satisfying multiple additional constraints. Once a solution has been found, new incoming flights will have approached the airspace of the airport in question, and these will require arrival gates to be assigned to them, so the entire process must be repeated. We have come up with a combined knowledge-based and evolutionary approach for performing the airport gate scheduling task. In this paper we present our model from a theoretical point of view, and then discuss a particular implementation of it for the scheduling of arrival gates in a specific airport and show some experimental results.
