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Optimal balanced chain decomposition of partially ordered sets with applications to operating cost minimization in aircraft routing problems

Optimal balanced chain decomposition of partially ordered sets with applications to operating... We consider the task of constructing a cost-effective daily flight schedule with a minimum number of required aircrafts and a maximum number of balanced flight routes, namely, routes with the same start and end spatial location. We suggest a solution strategy which is able to determine the problem’s hardness by estimating the number of all flight plans with a minimum number of required aircrafts. Provided that this number is not too large, the same algorithm is utilized for fully enumerating and detecting the set of solutions that have the maximum number of balanced routes. Our experimental study implies that the method is both effective and scalable in practice. For example, when applied to the Australian domestic flights timetable which is serviced by a total of eighty-eight aircrafts, our method manages to increase the number of balanced flight routes from nine to forty-two, while using only several minutes of computational time. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Public Transport Springer Journals

Optimal balanced chain decomposition of partially ordered sets with applications to operating cost minimization in aircraft routing problems

Public Transport , Volume OnlineFirst – Sep 5, 2022

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Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ISSN
1866-749X
eISSN
1613-7159
DOI
10.1007/s12469-022-00304-5
Publisher site
See Article on Publisher Site

Abstract

We consider the task of constructing a cost-effective daily flight schedule with a minimum number of required aircrafts and a maximum number of balanced flight routes, namely, routes with the same start and end spatial location. We suggest a solution strategy which is able to determine the problem’s hardness by estimating the number of all flight plans with a minimum number of required aircrafts. Provided that this number is not too large, the same algorithm is utilized for fully enumerating and detecting the set of solutions that have the maximum number of balanced routes. Our experimental study implies that the method is both effective and scalable in practice. For example, when applied to the Australian domestic flights timetable which is serviced by a total of eighty-eight aircrafts, our method manages to increase the number of balanced flight routes from nine to forty-two, while using only several minutes of computational time.

Journal

Public TransportSpringer Journals

Published: Sep 5, 2022

Keywords: Optimal flight scheduling; deadheading flights; approximate counting; optimization; heuristic

References