Mathematical programming formulations for robust airside terminal traffic flow optimisation problem
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...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/160346 |
| _version_ | 1826127765716336640 |
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| author | Ng, Kam K.H. Chen, Chun-Hsien Lee, C. K. M. |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Ng, Kam K.H. Chen, Chun-Hsien Lee, C. K. M. |
| author_sort | Ng, Kam K.H. |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T07:13:52Z |
| format | Journal Article |
| id | ntu-10356/160346 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:13:52Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1603462022-07-19T08:12:46Z Mathematical programming formulations for robust airside terminal traffic flow optimisation problem Ng, Kam K.H. Chen, Chun-Hsien Lee, C. K. M. School of Mechanical and Aerospace Engineering Engineering::Aeronautical engineering Decomposition Methods Robust Optimisation 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. 2022-07-19T08:12:46Z 2022-07-19T08:12:46Z 2021 Journal Article Ng, K. K., Chen, C. & Lee, C. K. M. (2021). Mathematical programming formulations for robust airside terminal traffic flow optimisation problem. Computers and Industrial Engineering, 154, 107119-. https://dx.doi.org/10.1016/j.cie.2021.107119 0360-8352 https://hdl.handle.net/10356/160346 10.1016/j.cie.2021.107119 2-s2.0-85099778488 154 107119 en Computers and Industrial Engineering © 2021 Elsevier Ltd. All rights reserved. |
| spellingShingle | Engineering::Aeronautical engineering Decomposition Methods Robust Optimisation Ng, Kam K.H. Chen, Chun-Hsien Lee, C. K. M. Mathematical programming formulations for robust airside terminal traffic flow optimisation problem |
| title | Mathematical programming formulations for robust airside terminal traffic flow optimisation problem |
| title_full | Mathematical programming formulations for robust airside terminal traffic flow optimisation problem |
| title_fullStr | Mathematical programming formulations for robust airside terminal traffic flow optimisation problem |
| title_full_unstemmed | Mathematical programming formulations for robust airside terminal traffic flow optimisation problem |
| title_short | Mathematical programming formulations for robust airside terminal traffic flow optimisation problem |
| title_sort | mathematical programming formulations for robust airside terminal traffic flow optimisation problem |
| topic | Engineering::Aeronautical engineering Decomposition Methods Robust Optimisation |
| url | https://hdl.handle.net/10356/160346 |
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