Stochastic Simulation Optimization for Route Selection Strategy Based on Flight Delay Cost

Yong Tian, Bojia Ye, Marc Sáez Estupiñá () and Lili Wan
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Yong Tian: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, P. R. China2National Key Laboratory of Air Traffic Flow Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, P. R. China
Bojia Ye: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, P. R. China2National Key Laboratory of Air Traffic Flow Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, P. R. China
Marc Sáez Estupiñá: The School of Industrial, Aerospace and Audiovisual Engineering of Terrassa, Polytechnic University of Catalonia, Terrassa, Barcelona 08222, Spain
Lili Wan: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, P. R. China2National Key Laboratory of Air Traffic Flow Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2018, vol. 35, issue 06, 1-24

Abstract: The continuous and strong growth of the civil aviation in the world combined with the severe adverse weather problem have made necessary the collaboration between the different civil aviation agents to improve the management of the capacity-demand imbalances in the airspace. In this paper, we consider a stochastic simulation optimization problem for air route selection strategy based on flight delay cost. The problem takes consideration of airspace capacity and demand uncertainty, three strategies, including collaborative reroute strategy (CRS), full information reroute strategy (FIRS) and hybrid stated route preference strategy (HSR), are employed to mitigate the flight delay cost. To find the best strategy, a discrete event simulation model is built by Arena Software, and the Monte Carlo method combined with the OCBA simulation optimization technique is employed for assessing a common severe convective weather scenario in the Central and Southern China airspace. Simulation results imply that HSR schemes show better system-wide performance than CRS and FIRS, these benefits are supposed to come from the batch allocations method. Although the airline can receive full information in advance, FIRS does not show obvious advantage in reducing the total airborne waiting time than CRS. For the system-wide performance FIRS is better than CRS, but not as good as HSR.

Keywords: Stochastic simulation optimization; air traffic flow management; route selection strategy; OCBA (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S0217595918500458

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