Abstract
Air traffic is growing, putting increasing stress to airports and air traffic control. The introduction of optimized approaches, based on mathematical optimization paradigms for planning and real time control, can be a possible solution to this issues. We investigate the practical setting of an advanced optimization algorithm in a real-life setting of a major airport where traffic is diverse, belonging to multiple companies. We compare to the incumbent practice (based on First Come First Served) in order to determine a gap with optimized solutions computed by advanced algorithms. Those are based on a job shop scheduling model and solved by a commercial solver.
This paper analyses the benefit for the involved operators of such approaches by associating a monetary cost/benefit to operations. Cooperative game theory tools have been used in the analysis. In particular, we use the Shapley value to determine the fair distribution of the costs based on the marginal improvement that the optimization of the traffic belonging to any airline brought to the system. The main conclusions of this study are the determination of the superior performance in terms of minimising the delay experienced by the whole airport, which reaches more than 25 %. The benefit allocation gives share of benefits more insightful than a simple proportional approaches based on share of traffic, or share of delay. The practical implications of the analysis with regard to variety in benefits as well as possible implementations by the different operators and companies are also analysed.
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Tripathy, M., Samà, M., Corman, F., Lodewijks, G. (2016). Impact of Collaborative Decision Making in Optimized Air Traffic Control: A Game Theoretical Approach. In: Paias, A., Ruthmair, M., Voß, S. (eds) Computational Logistics. ICCL 2016. Lecture Notes in Computer Science(), vol 9855. Springer, Cham. https://doi.org/10.1007/978-3-319-44896-1_26
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DOI: https://doi.org/10.1007/978-3-319-44896-1_26
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