A New Multiobjective A∗ Algorithm With Time Window Applied to Large Airports

Current airport ground operations, relying on single and fixed aircraft taxiing rules, struggle to handle dynamic traffic flow changes during peak flight times at large airports. This leads to inefficient taxiing routes, prolonged taxiing times, and high fuel consumption. This paper addresses these issues by proposing a new adaptive method for dynamic taxiway routing in airport ground operations. This method aims to reduce ground taxiing time and fuel consumption while ensuring the safety of aircraft taxiing. This study proposes a multiobjective A^∗ algorithm with time windows which takes into account the allocation of resources on airport taxiways and introduces factors such as turning angles, dynamic turning speeds, and dynamic characteristics of the ground operations. Experiments conducted over the 10 busiest days in the history of Tianjin Binhai International Airport demonstrate that the algorithm excels in minimizing total taxiing time, differing only by 0.5% from the optimal solution. It also optimizes multiple objectives such as fuel consumption and operates at a solving speed approximately three orders of magnitude faster than the optimal solution algorithm, enabling real-time calculation of aircraft taxiing paths. The results of the study indicate that the proposed multiobjective A^∗ algorithm with time windows can effectively provide decision support for dynamic routing in airport ground operations.