Pruning rules for optimal runway sequencing
This paper investigates runway sequencing for real world scenarios at one of the world's busiest airports, London Heathrow. Several pruning principles are introduced that enable significant reductions of the problem's average complexity, without compromising the optimality of the resulting...
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| Format: | Article |
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INFORMS
2017
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| Online Access: | https://eprints.nottingham.ac.uk/37774/ |
| _version_ | 1848795531048910848 |
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| author | de Maere, Geert Atkin, Jason Burke, Edmund |
| author_facet | de Maere, Geert Atkin, Jason Burke, Edmund |
| author_sort | de Maere, Geert |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper investigates runway sequencing for real world scenarios at one of the world's busiest airports, London Heathrow. Several pruning principles are introduced that enable significant reductions of the problem's average complexity, without compromising the optimality of the resulting sequences, nor compromising the modelling of important real world constraints and objectives. The pruning principles are generic and can be applied in a variety of heuristic, meta-heuristic or exact algorithms. They could also be applied to different runway configurations, as well as to different variants of the machine scheduling problem with sequence dependent setup times, the generic variant of the runway sequencing problem in this paper. They have been integrated into a dynamic program for runway sequencing, which has been shown to be able to generate optimal sequences for large scale problems at an extremely low computational cost, whilst considering complex non-linear and non-convex objective functions that offer significant flexibility to model real world preferences and real world constraints. The results shown here counter the proliferation of papers that claim that runway sequencing problems are too complex to solve exactly and therefore attempt to solve them heuristically. |
| first_indexed | 2025-11-14T19:33:34Z |
| format | Article |
| id | nottingham-37774 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:33:34Z |
| publishDate | 2017 |
| publisher | INFORMS |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-377742020-05-04T19:10:46Z https://eprints.nottingham.ac.uk/37774/ Pruning rules for optimal runway sequencing de Maere, Geert Atkin, Jason Burke, Edmund This paper investigates runway sequencing for real world scenarios at one of the world's busiest airports, London Heathrow. Several pruning principles are introduced that enable significant reductions of the problem's average complexity, without compromising the optimality of the resulting sequences, nor compromising the modelling of important real world constraints and objectives. The pruning principles are generic and can be applied in a variety of heuristic, meta-heuristic or exact algorithms. They could also be applied to different runway configurations, as well as to different variants of the machine scheduling problem with sequence dependent setup times, the generic variant of the runway sequencing problem in this paper. They have been integrated into a dynamic program for runway sequencing, which has been shown to be able to generate optimal sequences for large scale problems at an extremely low computational cost, whilst considering complex non-linear and non-convex objective functions that offer significant flexibility to model real world preferences and real world constraints. The results shown here counter the proliferation of papers that claim that runway sequencing problems are too complex to solve exactly and therefore attempt to solve them heuristically. INFORMS 2017-10-05 Article PeerReviewed de Maere, Geert, Atkin, Jason and Burke, Edmund (2017) Pruning rules for optimal runway sequencing. Transportation Science . ISSN 1526-5447 Dynamic programming Runway Sequencing Machine Scheduling Sequence dependent setup times http://pubsonline.informs.org/doi/10.1287/trsc.2016.0733 doi:10.1287/trsc.2016.0733 doi:10.1287/trsc.2016.0733 |
| spellingShingle | Dynamic programming Runway Sequencing Machine Scheduling Sequence dependent setup times de Maere, Geert Atkin, Jason Burke, Edmund Pruning rules for optimal runway sequencing |
| title | Pruning rules for optimal runway sequencing |
| title_full | Pruning rules for optimal runway sequencing |
| title_fullStr | Pruning rules for optimal runway sequencing |
| title_full_unstemmed | Pruning rules for optimal runway sequencing |
| title_short | Pruning rules for optimal runway sequencing |
| title_sort | pruning rules for optimal runway sequencing |
| topic | Dynamic programming Runway Sequencing Machine Scheduling Sequence dependent setup times |
| url | https://eprints.nottingham.ac.uk/37774/ https://eprints.nottingham.ac.uk/37774/ https://eprints.nottingham.ac.uk/37774/ |