A survey of the literature on airline crew scheduling
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Cites
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
AI and ML algorithms can be used to optimize crew schedules, taking into account factors such as flight times, rest periods, and seniority.
“AI and ML algorithms can be used to optimize crew schedules, taking into account factors such as flight times, rest periods, and seniority.”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [121]
Cited by
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Artificial intelligence, machine learning and deep learning in advanced robotics, a review
Soori, M., Arezoo, B., & Dastres, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.001 · Cited by 1,131 · see citing works
- Authors
- Deveci, M., & Demirel, N. Ç.
- Affiliations
- Yıldız Technical University (TR)
- Corresponding author
- Deveci, Muhammet
- Venue
- Engineering Applications of Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 74
- Pages
- 54-69
- ISSN
- 0952-1976 (ISSN-L)
- OpenAlex
- W2809577870
- Cited by
- 71
- References
- 0
- Citations by year
- 2026: 10 · 2025: 11 · 2024: 4 · 2023: 17 · 2022: 6 · 2021: 10 · 2020: 8 · 2019: 5
- FWCI
- 4.34
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Engineering Applications of Artificial Intelligence (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Scheduling and Timetabling Solutions
- Physical Sciences › Engineering › Aerospace Engineering › Air Traffic Management and Optimization
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Vehicle Routing Optimization Methods
- Keywords
- airline crew scheduling, crew rostering, mathematical model, optimization algorithms, fleet size, airline operations planning, scheduling software
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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