Mathematical programming formulations for robust airside terminal traffic flow optimisation problem. (April 2021)

• Record Type: Journal Article
• Authors: Ng, Kam K.H.; Chen, Chun-Hsien; Lee, C.K.M.
• Is Part Of: Computers & industrial engineering. Volume 154(2021)
• Publication Date: 2021-04
• Subjects: Decomposition methods -- Robust optimisation -- Min–max approach -- Airside terminal traffic flow problem; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2021.107119
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Min-max approach in TTFP model considered a set of worst-case scenarios. Two decomposition algorithms for robust TTFP model are proposed. The proposed method tackles infeasible subsystems in two-stage optimization problem. The algorithm is computational achievable to solve a traffic scenario of one hour. Abstract: The robust traffic flow modelling approach offers a perspicacious and holistic surveillance for flight activities in a nearby terminal manoeuvring area. The real time flight information expedites the streaming control of terminal operations using computational intelligence. Hence, in order to reduce the adverse effect of severe uncertainty and the impact of delay propagation, the amplified disruption along with the terminal traffic flow network can be leveraged by using robust optimisation. The transit time from entry waypoint to actual landing time is uncertain since the true airspeed is affected by the wind direction and hazardous aviation weather in the terminal manoeuvring area. Robust optimisation for TTFP is to generate a solution against the uncertain outcomes, which implies that less effort by the ATC to perform re-scheduling is required. In addition, two decomposition methods are presented and proposed in this work. The computational performance of traditional Benders Decomposition will largely be affected by the infeasibility in the subsystem and resolution of infeasible solution in the second-stage optimisation problem resulting in a long iterative process. Therefore, we presented an enhanced Benders Decomposition method to tackle the infeasibility in the subsystem. As shown in the numerical experiments, the proposed method outperforms the traditional Benders Decomposition algorithm using Wilcoxon-signed ranks test and achieved a 58.52% improvement of solution quality in terms of solving one-hour flight traffic scenarios with an hour computation time limit.