Towards strengthening the efficiency of the Air Traffic Departure Manager DMAN using a Genetic Algorithm

Air traffic congestion issue in departure is currently considered to be a huge concern for air navigation service providers (ANSPs). To improve the air traffic flows, and ensure a fluent and minimum possible delay, ANSPs are using technologies and tools such as the departure manager DMAN. Using a variety of constraints and preferences, the DMAN program determines the target take-off times and the target startup approval times. The purpose of this paper is to enhance the efficiency of the DMAN program using a genetic algorithm.