A more realistic approach for airport ground movement optimisation with stand holding
In addition to having to handle constantly increasing numbers of aircraft, modern airports also have to address a wide range of environmental regulations and requirements. As airports work closer and closer to their maximal possible capacity, the operations problems that need to be solved become mor...
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| Format: | Article |
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Springer
2014
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| Online Access: | https://eprints.nottingham.ac.uk/34154/ |
| _version_ | 1848794786027274240 |
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| author | Ravizza, Stefan Atkin, Jason Burke, Edmund K. |
| author_facet | Ravizza, Stefan Atkin, Jason Burke, Edmund K. |
| author_sort | Ravizza, Stefan |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In addition to having to handle constantly increasing numbers of aircraft, modern airports also have to address a wide range of environmental regulations and requirements. As airports work closer and closer to their maximal possible capacity, the operations problems that need to be solved become more and more complex. This increasing level of complexity leads to a situation where the introduction of advanced decision support systems becomes more and more attractive. Such systems have the potential to improve efficient airside operations and to mitigate against the environmental impact of those operations. This paper addresses the problem of moving aircraft from one location within an airport to another as efficiently as possible in terms of time and fuel spent. The problem is often called the ground movement problem and the movements are usually from gate/stands to a runway or vice-versa. We introduce a new sequential graph based algorithm to address this problem. This approach has several advantages over previous approaches. It increases the realism of the modelling and it draws upon a recent methodology to more accurately estimate taxi times. The algorithm aims to absorb as much waiting time for delay as possible at the stand (with engines off) rather than out on the taxiways (with engines running). The impact of successfully achieving this aim is to reduce the environmental pollution. This approach has been tested using data from a European hub airport and it has demonstrated very promising results. We compare the performance of the algorithm against a lower bound on the taxi time and the limits to the amount of waiting time that can be absorbed at stand. |
| first_indexed | 2025-11-14T19:21:43Z |
| format | Article |
| id | nottingham-34154 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:21:43Z |
| publishDate | 2014 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-341542020-05-04T20:13:17Z https://eprints.nottingham.ac.uk/34154/ A more realistic approach for airport ground movement optimisation with stand holding Ravizza, Stefan Atkin, Jason Burke, Edmund K. In addition to having to handle constantly increasing numbers of aircraft, modern airports also have to address a wide range of environmental regulations and requirements. As airports work closer and closer to their maximal possible capacity, the operations problems that need to be solved become more and more complex. This increasing level of complexity leads to a situation where the introduction of advanced decision support systems becomes more and more attractive. Such systems have the potential to improve efficient airside operations and to mitigate against the environmental impact of those operations. This paper addresses the problem of moving aircraft from one location within an airport to another as efficiently as possible in terms of time and fuel spent. The problem is often called the ground movement problem and the movements are usually from gate/stands to a runway or vice-versa. We introduce a new sequential graph based algorithm to address this problem. This approach has several advantages over previous approaches. It increases the realism of the modelling and it draws upon a recent methodology to more accurately estimate taxi times. The algorithm aims to absorb as much waiting time for delay as possible at the stand (with engines off) rather than out on the taxiways (with engines running). The impact of successfully achieving this aim is to reduce the environmental pollution. This approach has been tested using data from a European hub airport and it has demonstrated very promising results. We compare the performance of the algorithm against a lower bound on the taxi time and the limits to the amount of waiting time that can be absorbed at stand. Springer 2014-10 Article PeerReviewed Ravizza, Stefan, Atkin, Jason and Burke, Edmund K. (2014) A more realistic approach for airport ground movement optimisation with stand holding. Journal of Scheduling, 17 (5). pp. 507-520. ISSN 1094-6136 Ground movement optimisation; Airport operations; Routing; Real world scheduling; Decision support system http://link.springer.com/article/10.1007%2Fs10951-013-0323-3 doi:10.1007/s10951-013-0323-3 doi:10.1007/s10951-013-0323-3 |
| spellingShingle | Ground movement optimisation; Airport operations; Routing; Real world scheduling; Decision support system Ravizza, Stefan Atkin, Jason Burke, Edmund K. A more realistic approach for airport ground movement optimisation with stand holding |
| title | A more realistic approach for airport ground movement optimisation with stand holding |
| title_full | A more realistic approach for airport ground movement optimisation with stand holding |
| title_fullStr | A more realistic approach for airport ground movement optimisation with stand holding |
| title_full_unstemmed | A more realistic approach for airport ground movement optimisation with stand holding |
| title_short | A more realistic approach for airport ground movement optimisation with stand holding |
| title_sort | more realistic approach for airport ground movement optimisation with stand holding |
| topic | Ground movement optimisation; Airport operations; Routing; Real world scheduling; Decision support system |
| url | https://eprints.nottingham.ac.uk/34154/ https://eprints.nottingham.ac.uk/34154/ https://eprints.nottingham.ac.uk/34154/ |