MATEC Web Conf.
Volume 105, 2017International Workshop on Transportation and Supply Chain Engineering (IWTSCE’16)
|Number of page(s)||5|
|Published online||14 April 2017|
Multi-objective optimization approach for air traffic flow management
1 LIMSAD Lab, Faculty of Science Ain Chock - Casablanca, Morocco
2 Air Navigation Department, Mohammed V International Airport, Casablanca, Morocco
3 STRS Lab, National Institute of Posts and Telecommunication, Rabat, Morocco
4 Electrical Engineering Department, University of North Dakota, Grand Forks, United States
Air traffic has long been a generally high growth sector and all forecasts indicate that this trend will continue at a similar pace for the next twenty years. The regular traffic demand growth has led to congestionat airports and in space.
In this paper, we will create in first a probabilistic model which describes the uncertainty of the aircraft’s trajectory,and its presence in a sector during a time interval. We define as result, amulti-objective optimization problem whose objective functions are the expected cost of delay and the expected cost of congestion.Then we use the Non-dominated Sorting Genetic Algorithm (NSGA-II) to solve an instance included 21 flights and 1 sector, and is able to provide a good approximation of the Pareto front.
The decision-making stage was then performed with the aid of data clustering techniques to reduce the sizeof the Pareto-optimal set and obtain a smaller representation of the multi-objective design space, there by making it easier for the decision-maker to find satisfactory and meaningful trade-offs, and to select a preferred final design solution.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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