Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.580568
Title: Airport runway optimization
Author: Mesgarpour, Mohammad
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2012
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Abstract:
This thesis considers the scheduling of aircraft landing and take-off problems on a single runway where aircraft must respect various operational constraints. The aim is to introduce generic models and solution approaches that can be implemented in practice. Existing solution methods and techniques of airport runway optimization have been reviewed. Several solution methods such as mixed integer programming, dynamic programming, iterated descent local search and simulated annealing are proposed for the scheduling of aircraft landings in the static and dynamic environment. A multi-objective formulation is used for taking into account runway throughput, earliness and lateness, and the cost of fuel arising from aircraft manoeuvres and additional flight time incurred to achieve the landing schedule. Moreover, computational results are presented using real data from Heathrow airport as well as randomly generated problem instances which are generated based on characteristics of the real data. Later, dynamic programming, descent local search and beam search algorithms are proposed for the scheduling of aircraft take-offs in the departure holding area. Scheduling aircraft take-off is formulated as a hierarchical multi-objective problem which includes maximizing departure runway throughput and minimizing total waiting time in the holding area. Performance of the algorithms have been evaluated for three common layouts of holding area. Computational results are presented on randomly generated test data.
Supervisor: Potts, Christopher Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.580568  DOI: Not available
Keywords: HE Transportation and Communications ; QA Mathematics ; HD28 Management. Industrial Management
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