An optimal data-splitting algorithm for aircraft sequencing on a single runway
During peak-hour busy airports have the challenge of turning aircraft around as quickly as possible, which includes sequencing their landings and take-offs with maximum efficiency, without sacrificing safety. This problem, termed aircraft sequencing problem (ASP) has traditionally been hard to solve...
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sg-ntu-dr.10356-1600512022-07-12T03:10:45Z An optimal data-splitting algorithm for aircraft sequencing on a single runway Prakash, Rakesh Desai, Jitamitra Piplani, Rajesh School of Mechanical and Aerospace Engineering Air Traffic Management Research Institute Engineering::Aeronautical engineering Aircraft Sequencing Constrained Position Shifting During peak-hour busy airports have the challenge of turning aircraft around as quickly as possible, which includes sequencing their landings and take-offs with maximum efficiency, without sacrificing safety. This problem, termed aircraft sequencing problem (ASP) has traditionally been hard to solve optimally in real-time, even for flights over a one-hour planning window. In this article, we present a novel data-splitting algorithm to solve the ASP on a single runway with the objective to minimize the total delay in the system both under segregated and mixed mode of operation. The problem is formulated as a 0–1 mixed integer program, taking into account several realistic constraints, including safety separation standards, wide time-windows, and constrained position shifting. Following divide-and-conquer paradigm, the algorithm divides the given set of flights into several disjoint subsets, each of which is optimized using 0–1 MIP while ensuring the optimality of the entire set. One hour peak-traffic instances of this problem, which is NP-hard in general, are computationally difficult to solve with direct application of the commercial solver, as well as existing state-of-the-art dynamic programming method. Using our data-splitting algorithm, various randomly generated instances of the problem can be solved optimally in near real-time, with time savings of over 90%. Civil Aviation Authority of Singapore (CAAS) Nanyang Technological University This research has been partially supported under ATMRI (NTU-CAAS) Grant No. M4061216. 2022-07-12T03:10:45Z 2022-07-12T03:10:45Z 2022 Journal Article Prakash, R., Desai, J. & Piplani, R. (2022). An optimal data-splitting algorithm for aircraft sequencing on a single runway. Annals of Operations Research, 309(2), 587-610. https://dx.doi.org/10.1007/s10479-021-04351-2 0254-5330 https://hdl.handle.net/10356/160051 10.1007/s10479-021-04351-2 2-s2.0-85119330874 2 309 587 610 en M4061216 Annals of Operations Research © 2021 The Authors, under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. All rights reserved. |
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Engineering::Aeronautical engineering Aircraft Sequencing Constrained Position Shifting Prakash, Rakesh Desai, Jitamitra Piplani, Rajesh An optimal data-splitting algorithm for aircraft sequencing on a single runway |
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During peak-hour busy airports have the challenge of turning aircraft around as quickly as possible, which includes sequencing their landings and take-offs with maximum efficiency, without sacrificing safety. This problem, termed aircraft sequencing problem (ASP) has traditionally been hard to solve optimally in real-time, even for flights over a one-hour planning window. In this article, we present a novel data-splitting algorithm to solve the ASP on a single runway with the objective to minimize the total delay in the system both under segregated and mixed mode of operation. The problem is formulated as a 0–1 mixed integer program, taking into account several realistic constraints, including safety separation standards, wide time-windows, and constrained position shifting. Following divide-and-conquer paradigm, the algorithm divides the given set of flights into several disjoint subsets, each of which is optimized using 0–1 MIP while ensuring the optimality of the entire set. One hour peak-traffic instances of this problem, which is NP-hard in general, are computationally difficult to solve with direct application of the commercial solver, as well as existing state-of-the-art dynamic programming method. Using our data-splitting algorithm, various randomly generated instances of the problem can be solved optimally in near real-time, with time savings of over 90%. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Prakash, Rakesh Desai, Jitamitra Piplani, Rajesh |
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Article |
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Prakash, Rakesh Desai, Jitamitra Piplani, Rajesh |
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Prakash, Rakesh |
title |
An optimal data-splitting algorithm for aircraft sequencing on a single runway |
title_short |
An optimal data-splitting algorithm for aircraft sequencing on a single runway |
title_full |
An optimal data-splitting algorithm for aircraft sequencing on a single runway |
title_fullStr |
An optimal data-splitting algorithm for aircraft sequencing on a single runway |
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An optimal data-splitting algorithm for aircraft sequencing on a single runway |
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optimal data-splitting algorithm for aircraft sequencing on a single runway |
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2022 |
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https://hdl.handle.net/10356/160051 |
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