A multi-stage heuristic model with different objective functions for air traffic flow in airport movement areas

Air travel is a transportation system operating in global scale, adapting rapidly to technological innovation and change. Every year, increasing demand for air transportation within a certain rate brings congestions, delays and disruption of services for this transportation system. For this reason, effective and efficient use of parking positions at airports, determination of routes to relieve maneuvering traffic density on taxiways and shortening of passenger walking times at the terminal building play an important role in air transportation. The main purpose of this thesis is to reduce traffic delays and congestions on taxiways and parking positions at busy airports, speed up traffic flow by shortening the taxi times of incoming and outgoing airplanes, provide more balanced distribution of open and terminal connected parking positions and improve the number of operating aircraft number using an heuristic algorithm with dynamic criteria for allocation of parking and taxi routes. This algorithm can be used in coordination with air traffic control (ATC) and ramp towers in order to minimize the effects of human factors experienced in conventional systems and produce solutions for the last-minute changes. In the first stage, a heuristic elimination algorithm was developed to reduce the appropriate set of solutions for an aircraft, and objective functions are modelled to reduce the standard deviation time of parking use, aircraft taxi and passenger walking time. This heuristic model is compared with GAMS model in terms of accuracy and computation times of results. Finally, the proposed model is compared with the current situation. It is observed that the heuristic algorithm with dynamic criteria benefits both the taxi and the passenger walking time according to the current situation model against the last minute changes.