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A linear programming model for airline schedule recovery after disruption

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  • Jakob Kotas

Abstract

We present a decision support framework for optimal flight rescheduling on an airline's day of operations under unanticipated system disruption. We consider disruptions which add an unforeseen need to extend each aircraft's turnaround time on the ground, not necessarily uniformly across all flights or airports in the system. Our model optimally reschedules remaining flights of the day to minimise system delays and cancellations. The model is formulated as a mixed integer linear program. We prove that structural properties of the model allow it to be decomposed into a finite set of linear programs, and a computationally tractable algorithm for its solution is described. The model is solvable exactly and quickly, even for large airlines. Numerical simulations are presented for a case study of a winter weather event impacting Horizon Air, a regional airline based in the Pacific Northwest of the USA.

Suggested Citation

  • Jakob Kotas, 2022. "A linear programming model for airline schedule recovery after disruption," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 45(3), pages 378-396.
    • Handle: RePEc:ids:ijores:v:45:y:2022:i:3:p:378-396
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