The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Optimal Solutions to a Real-World Integrated Airline Scheduling Problem
Open accessAbstract
We study an integrated airline scheduling problem for a regional carrier. It integrates three stages of the planning process (i.e., fleet assignment, aircraft routing, and crew pairing) that are typically solved in sequence. Aircraft maintenance is also taken into account. The objective function aims at minimizing a weighted sum of the number of aircraft routes, the number of crew pairings, and the waiting times of crews between consecutive flights. In addition, it aims at maximizing the robustness of the solution by also minimizing the number of times that crews need to change aircraft. We present two mixed integer linear programming models for the integrated problem. The first formulation, called the path-path model, can be considered as the “natural model” in which both the crew pairings and the aircraft routes are represented by path-based variables. The other formulation, called the arc-path model, is a novel model in which the aircraft routes are represented by arc-based variables and the crew pairings by path-based variables. We propose two exact methods (called path-path method and arc-path method) for solving the integrated problem, each one based on one of the proposed models. Both methods consist of three phases. In the first phase, the linear programming relaxation of the corresponding model is solved to optimality by column generation on the path-based variables, thus providing a lower bound. The second phase computes a heuristic solution (upper bound) by using o…
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“More recently, increasing attention has been given to integrating sequential stages and improving the integration with predictive methods aimed at anticipating key inputs, such as demand at the tactical level and delays at the operational level, demonstrating enhanced capability to yield superior decisions ( Birolini et al., 2021; Cacchiani and Salazar-González, 2017 ).”
From Status quo and challenges in air transport management research (2024) · cites this paper as Cacchiani and Salazar-González, 2017
Citations
Cites
Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria
Magnanti, T. L., & Wong, R. T. (1981) · Operations Research · doi:10.1287/opre.29.3.464 · Cited by 725
Barnhart, C., Belobaba, P., & Odoni, A. (2009) · Wiley eBooks · doi:10.1002/9780470744734 · Cited by 560
Flight String Models for Aircraft Fleeting and Routing
Barnhart, C., Boland, N., Clarke, L. W., Johnson, E. L., Nemhauser, G. L., & Shenoi, R. G. (1998) · Transportation Science · doi:10.1287/trsc.32.3.208 · Cited by 360
(1998) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(98)90683-6 · Cited by 350
Lan, S., Clarke, J.-P., & Barnhart, C. (2006) · Transportation Science · doi:10.1287/trsc.1050.0134 · Cited by 308
Airline Schedule Planning: Integrated Models and Algorithms for Schedule Design and Fleet Assignment
Lohatepanont, M., & Barnhart, C. (2004) · Transportation Science · doi:10.1287/trsc.1030.0026 · Cited by 301
Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling
Cordeau, J., Stojković, G., Soumis, F., & Desrosiers, J. (2001) · Transportation Science · doi:10.1287/trsc.35.4.375.10432 · Cited by 301
Mercier, A., Cordeau, J., & Soumis, F. (2004) · Computers & Operations Research · doi:10.1016/j.cor.2003.11.013 · Cited by 214
Papadakos, N. (2007) · Computers & Operations Research · doi:10.1016/j.cor.2007.08.002 · Cited by 159
Operations Research in the Airline Industry
Yu, G. (1998) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-1-4615-5501-8 · Cited by 159
Cited by
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Airline schedule planning: a review and future directions
Eltoukhy, A. E. E., Chan, F. T. S., & Chung, S. (2017) · Industrial Management & Data Systems · doi:10.1108/imds-09-2016-0358 · Cited by 87
A multi-objective fuzzy optimization model for multi-type aircraft flight scheduling problem
Ming, W., Yang, S., Wu, W. Y., & Sun, B. (2024) · Transport · doi:10.3846/transport.2024.20536 · Cited by 69
Status quo and challenges in air transport management research
Wandelt, S., Antoniou, C., Birolini, S., Delahaye, D., Dresner, M., Fu, X., Gössling, S., Hong, S.-J., Odoni, A. R., Zanin, M., et al. (2024) · Journal of the Air Transport Research Society · doi:10.1016/j.jatrs.2024.100014 · Cited by 67
Airline integrated robust scheduling with a variable neighborhood search based heuristic
Xu, Y., Wandelt, S., & Sun, X. (2021) · Transportation Research Part B Methodological · doi:10.1016/j.trb.2021.05.005 · Cited by 66
Airline planning and scheduling: Models and solution methodologies
Zhou, L. S., Liang, Z., Chou, C.-A., & Chaovalitwongse, W. A. (2020) · Frontiers of Engineering Management · doi:10.1007/s42524-020-0093-5 · Cited by 65
Metadata
- Authors
- Cacchiani, V., & Salazar-González, J.-J.
- Affiliations
- University of Bologna (IT)
- DMEIO, Universidad de La Laguna, 38271 La Laguna, Tenerife, Spain
- Corresponding author
- Cacchiani, Valentina
- ORCID
- Cacchiani, Valentina
- Venue
- Transportation Science
- Published
- 2017-02
- Volume
- 51
- Issue
- 1
- Pages
- 250-268
- ISSN
- 0041-1655 (ISSN-L)
- 1526-5447
- OpenAlex
- W2331684445
- Cited by
- 64
- References
- 30
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 9 · 2023: 10 · 2022: 4 · 2021: 7 · 2020: 9 · 2019: 5 · 2018: 6 · 2017: 2
- FWCI
- 6.11
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc
- Locations
- Transportation Science (publishedVersion)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion, cc-by-nc)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Air Traffic Management and Optimization
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Vehicle Routing Optimization Methods
- Social Sciences › Decision Sciences › Management Science and Operations Research › Scheduling and Timetabling Solutions
- Keywords
- airline scheduling, integrated scheduling, fleet assignment, aircraft routing, crew pairing, aircraft maintenance, mixed-integer linear programming, column generation
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