A new intelligent approach for air traffic control using gravitational search algorithm

Aircraft landing planning (ALP) is one of the most important challenging problems in the domain of air traffic control (ATC). Solving this NP-hard problem is a valuable aid in organizing air traffic in terminal control area (TCA), which itself leads to a decrease in aircraft fuel consumption, costs of airlines, and workload undertaken by air traffic controllers. In the present paper, the ALP problem is dealt with by applying effective rich knowledge to the optimization process (to remove obvious non-optimal solutions), and the first use of Gravitational Search Algorithm (GSA) in resolving such a case. In this regard, while the specific regulations for safe separation have been observed, the optimal landing time, the optimal runway, and the order of consecutive landings have been determined so that the main goal (minimizing total flight delays) would be best met. Results of simulations show that this approach, compared to previous ones, which are based on Genetic and Bionomic algorithms, GLS, and Scatter search method, considerably decreases total flight delays. Attaining zero in the total flight delays in three scenarios with real data shows that the suggested intelligent approach is more decisive than others in finding an optimal solution.