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@article{209558,
        author = {Kavya Jain and Arnav Bhandari and Samaira Walia and Shiven Shah and Zain Master},
        title = {From the Transportation Table to Column Generation: A Review of 50 Operations Research Studies in Airline Planning with Two Replications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {5},
        pages = {2433-2442},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=209558},
        abstract = {Most of the optimisation models that airlines use every day grow out of the transportation and assignment problems taught in a first course in Operations Research (OR), yet recent published applications of these classroom methods to aviation are small and seldom checked. This paper reviews 50 peer-reviewed studies, published between 1982 and 2023, that apply OR to nine airline planning stages, from network design to disruption recovery. Every reference was matched against the Crossref registry, and each study was classified by problem, model, objective, constraints, solution method, data, validation and region. The review finds three things. Methods moved from exact integer programming before 2000 to decomposition and integrated planning in the 2000s, and then to stochastic, multi-objective and machine-learning approaches after 2010. Nine studies report systems in daily use, with gains as large as US$1.4 billion over three years. Twenty-eight of the 50 studies come from North America and only one from India. We also re-solve the two recent classroom-method studies in the sample: a transportation model for route selection is confirmed apart from a US$492 rounding gap, while a crew-pairing assignment model is shown to rest on a cost matrix with 19 wrong cells, so that its true minimum layover is 52 hours rather than the 65.5 hours reported. The paper closes with a research agenda for carefully checked applications of classroom OR to Indian aviation.},
        keywords = {Airline planning, assignment problem, crew scheduling, fleet assignment, literature review, operations research, replication, transportation problem},
        month = {October},
        }