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Peer Review Status: Refereed
Title: A metaheuristic approach to aircraft departure scheduling at London Heathrow airport
Author(s): Atkin, Jason A D
Burke, Edmund
Greenwood, John S
Reeson, Dale
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Editor(s): Hickman, M
Mirchandani, P
Voss, S
Citation: Atkin JAD, Burke E, Greenwood JS & Reeson D (2008) A metaheuristic approach to aircraft departure scheduling at London Heathrow airport. In: Hickman M, Mirchandani P & Voss S (eds.) Computer-aided Systems in Public Transport, Part III. Lecture Notes in Economics and Mathematical Systems, 600. Berlin Heidelberg: Springer, pp. 235-252.;
Issue Date: 2008
Date Deposited: 3-Jul-2013
Series/Report no.: Lecture Notes in Economics and Mathematical Systems, 600
Abstract: London Heathrow airport is one of the busiest airports in the world. Moreover, it is unusual among the world's leading airports in that it only has two runways. At many airports the runway throughput is the bottleneck to the departure process and, as such, it is vital to schedule departures effectively and efficiently. For reasons of safety, separations need to be enforced between departing aircraft. The minimum separation between any pair of departing aircraft is determined not only by those aircraft but also by the flight paths and speeds of aircraft that have previously departed. Departures from London Heathrow are subject to physical constraints that are not usually addressed in departure runway scheduling models. There are many constraints which impact upon the orders of aircraft that are possible and we will show how these constraints either have already been included in the model we present or can be included in the future. The runway controllers are responsible for the sequencing of the aircraft for the departure runway. This is currently carried out manually. In this paper we propose a metaheuristic-based solution for determining good sequences of aircraft in order to aid the runway controller in this difficult and demanding task. Finally some results are given to show the effectiveness of this system and we evaluate those results against manually produced real world schedules.
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DOI Link: 10.1007/978-3-540-73312-6_12
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