OPERATIONS RESEARCH IN AIRLINE SCHEDULING: A BIBLIOMETRIC ANALYSIS OF CURRENT TRENDS AND FUTURE DIRECTIONS (2020–2026)
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Dr Richa Kalpesh Saxena
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Marketing & Operations, NMIMS, Anil Surendra Modi School of Commerce, Mumbai Campus, India
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Abstract
This bibliometric analysis offers a comprehensive overview of the evolving landscape of Airline Scheduling research from an Operations Research (OR) perspective. The set of 500 records used in the study includes works published in 2020 through 2026, with 297 i.e. 59.4%, of them originating in 2024-2026. This suggests active ongoing research into the topic, though 2026 is obviously an incomplete year for publication. Authors have identified the breadth and fragmentation of research that is related to airline scheduling which is the origin of the motivation of the current study. The literature has been developed into several specialized problems including the three key areas of crew scheduling, fleet assignment and aircraft routing, as well as related topics such as aircraft maintenance, disruption management and delay propagation. Existing reviews as demonstrated display the depth of individual streams, (Xu et al., 2024) reviews airline scheduling optimization and modelling methodologies, while (S. Wu et al., 2025) reviews airline recovery problems under disruptions. The literature continues to rely on established OR techniques such as column generation and mathematical programming, while also incorporating newer approaches such as machine learning and reinforcement learning (Wandelt, Wang, et al., 2025; Zhang et al., 2024). The future research agenda identifies integrated multi-resource disruption recovery as the largest growing theme, followed by uncertainty-aware scheduling and predictive AI integrated with prescriptive operations research.
Keywords
crew scheduling fleet assignment and aircraft routing column generation scheduling optimization airline operations and disruption management.
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Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 10
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Oct 10 2026
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Tater, M., Shah, K., Sharma, M., Divate, K. & Sharma, K. (2026). Operations Research in Airline Scheduling: A Bibliometric Analysis of Current Trends and Future Directions (2020–2026). International Journal of Science, Strategic Management and Technology, 02(10), 1-9. https://doi.org/10.55041/ijsmt.v2i10.039
Tater, Mahi, et al.. "Operations Research in Airline Scheduling: A Bibliometric Analysis of Current Trends and Future Directions (2020–2026)." International Journal of Science, Strategic Management and Technology, vol. 02, no. 10, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijsmt.v2i10.039.
Tater, Mahi,Krit Shah,Mehar Sharma,Krushna Divate, and Kunaal Sharma. "Operations Research in Airline Scheduling: A Bibliometric Analysis of Current Trends and Future Directions (2020–2026)." International Journal of Science, Strategic Management and Technology 02, no. 10 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijsmt.v2i10.039.
References
Abdelghany, A., & Abdelghany, K. (2026). Addressing the systemic complexity of airline irregular operations: Toward integrated schedule recovery. Journal of Air Transport Management, 131, 102925. https://doi.org/https://doi.org/10.1016/j.jairtraman.2025.102925
Akıncılar, A., & Güner, E. (2025). A new tool for robust aircraft routing: Superior Robust Aircraft Routing (sup-RAR). Journal of Air Transport Management, 124, 102744. https://doi.org/https://doi.org/10.1016/j.jairtraman.2025.102744
Barry, N., & Stuart, C. (2026). Developing Discrete Optimisation Methods for a Holistic Airline Scheduling Algorithm With Sustainability as an Objective Function. AIAA SCITECH 2026 Forum. https://doi.org/10.2514/6.2026-0451
Bartulović, D., & Grgić, A. (2025). Implementing fatigue risk management system in an airline: A case study. Transportation Research Procedia, 91, 13–20. https://doi.org/https://doi.org/10.1016/j.trpro.2025.10.003
Beltman, M., Ribeiro, M., de Wilde, J., & Sun, J. (2025). Dynamically forecasting airline departure delay probability distributions for individual flights using supervised learning. Journal of Air Transport Management, 126, 102788. https://doi.org/https://doi.org/10.1016/j.jairtraman.2025.102788
Ben Ahmed, M., Hryhoryeva, M., Hvattum, L. M., & Haouari, M. (2022). A matheuristic for the robust integrated airline fleet assignment, aircraft routing, and crew pairing problem. Computers & Operations Research, 137, 105551. https://doi.org/https://doi.org/10.1016/j.cor.2021.105551
Benson, T. Y. (2020). An investigation of the practices used in airline crew scheduling and their impact on the physical and mental health of airline crew. repositories.lib.utexas.edu. https://repositories.lib.utexas.edu/items/deb7bc51-c40b-4be1-8306-23249377d9ad
Birolini, S., Antunes, A. P., Cattaneo, M., Malighetti, P., & Paleari, S. (2021). Integrated flight scheduling and fleet assignment with improved supply-demand interactions. Transportation Research Part B: Methodological, 149, 162–180. https://doi.org/https://doi.org/10.1016/j.trb.2021.05.001
Akıncılar, A., & Güner, E. (2025). A new tool for robust aircraft routing: Superior Robust Aircraft Routing (sup-RAR). Journal of Air Transport Management, 124, 102744. https://doi.org/https://doi.org/10.1016/j.jairtraman.2025.102744
Barry, N., & Stuart, C. (2026). Developing Discrete Optimisation Methods for a Holistic Airline Scheduling Algorithm With Sustainability as an Objective Function. AIAA SCITECH 2026 Forum. https://doi.org/10.2514/6.2026-0451
Bartulović, D., & Grgić, A. (2025). Implementing fatigue risk management system in an airline: A case study. Transportation Research Procedia, 91, 13–20. https://doi.org/https://doi.org/10.1016/j.trpro.2025.10.003
Beltman, M., Ribeiro, M., de Wilde, J., & Sun, J. (2025). Dynamically forecasting airline departure delay probability distributions for individual flights using supervised learning. Journal of Air Transport Management, 126, 102788. https://doi.org/https://doi.org/10.1016/j.jairtraman.2025.102788
Ben Ahmed, M., Hryhoryeva, M., Hvattum, L. M., & Haouari, M. (2022). A matheuristic for the robust integrated airline fleet assignment, aircraft routing, and crew pairing problem. Computers & Operations Research, 137, 105551. https://doi.org/https://doi.org/10.1016/j.cor.2021.105551
Benson, T. Y. (2020). An investigation of the practices used in airline crew scheduling and their impact on the physical and mental health of airline crew. repositories.lib.utexas.edu. https://repositories.lib.utexas.edu/items/deb7bc51-c40b-4be1-8306-23249377d9ad
Birolini, S., Antunes, A. P., Cattaneo, M., Malighetti, P., & Paleari, S. (2021). Integrated flight scheduling and fleet assignment with improved supply-demand interactions. Transportation Research Part B: Methodological, 149, 162–180. https://doi.org/https://doi.org/10.1016/j.trb.2021.05.001
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