Algorithmic Efficiency Comparison of Centralised and Distributed Arrival Management (AMAN) Problem In Terminal Airspace
Résumé
Terminal Maneuvering Area (TMA) is one of the most complex and busiest airspaces where the air traffic is managed with the help of decision support tools such as Arrival Manager (AMAN) in many airports. The objective of AMAN involves regulating the inbound air traffic flow and providingthe expected scheduled time for each flight considering the impact of the enviro nment. As we know, the aircraft scheduling problem is NP-hard and requires the implementation of advanced algorithms. The heuristic algorithms are more likely to provide a quick and satisfying result, in which simulated annealing (SA) has been proven to be efficient and easily adapted to a complex problem that involves large-dimensional state-space. Previously, in our work [1], the problem is considered from a centralized point of view in which the integrated information of all flights is investigated. The optimization process involves population-based and computational consuming evaluation for each simulation. Considering the isolated decisions of each flight, it is evident that the system is naturally distributed. By focusing on the individual performance of each flight, the optimization process can be guided with prioritization and no integration of flight information is required, therefore the efficiency and flexibility of the algorithm will be increased. Since the centralized and distributed AMAN develop different implementations for simulated annealing, the properties of both adapted algorithms are demonstrated. The performances are analyzed in terms of the execution time and quality of result based on a case study on Paris-Charles de Gaulle airport.
Origine : Fichiers produits par l'(les) auteur(s)