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Pruning Rules for Optimal Runway Sequencing

De Maere, Geert; Atkin, Jason A. D.; Burke, Edmund K.

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Associate Professor

Edmund K. Burke


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.

Journal Article Type Article
Acceptance Date Sep 16, 2016
Online Publication Date Oct 5, 2017
Publication Date 2018-07
Deposit Date Oct 20, 2016
Publicly Available Date Oct 5, 2017
Journal Transportation Science
Print ISSN 0041-1655
Electronic ISSN 1526-5447
Publisher INFORMS
Peer Reviewed Peer Reviewed
Volume 52
Issue 4
Pages 739-1034
Keywords Dynamic programming, Runway Sequencing, Machine Scheduling, Sequence dependent setup times
Public URL
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