Improvement of the Aircraft Traffic Management Advisor Optimization Using a Hybrid Genetic Algorithm

Abstract

During the last decade, problems regarding the Traffic Management Advisor(TMA) has become a concerning matter. A novel hybrid Genetic Algorithm(GA) for the goal of seeking best possible alignment has been presented in this paper. This simple and yet very thorough method benefits from low computational burden, higher convergence rate and lower overall delays. Comprehensive simulations and implementation of the imbedded specially designed rearrangement operator, have shown the effectiveness of the proposed method in comparison with previous literatures and classic GA.

Review on meta-heuristics approaches for airside operation research

“…the squared deviation of the scheduled and actual landing time; min. the total penalties (earliness and lateness) [92] Physics-based algorithm Mass 2016 GSA GA [88]; GA with uniform crossover [93]; SS [71]; GLS [8] Min. the deviation of scheduled and actual landing time [94] Swarm intelligence Inefficiencies in surface traffic operations cause significant financial loss and impact to other airport operations and customer satisfaction.…”