Airport Operations Simulation using Particle Swarm Optimization

The optimization of airport operations is recognized as a challenge that aims at finding the best trade-off solution in order to maximize the airport capacity and minimize both pollution and noise. In a previous study we presented the processing, by Dijkstra algorithm, of airport data in order to find the shortest path between two assigned waypoints. However this approach did not provide the best solution in terms of computational time, that become of major importance in a decision making process such as airport operation optimization. In this paper a new approach to the optimum path search is undertaken through the metaheuristic Particle Swarm Optimization (PSO). PSO simulates the behaviors of bird flocking. Each single solution is a "bird" in the search space and it is called "particle". The best solution is reached by following the bird which is nearest to the objective