Title: A linear programming model for airline schedule recovery after disruption

Authors: Jakob Kotas

Addresses: Department of Mathematics, University of Portland, Portland, Oregon 97203, USA

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.

Keywords: decision support framework; disruption management; scheduling; airline scheduling; airline operations; linear programming; mixed integer linear programming; winter weather; snow; de-icing.

DOI: 10.1504/IJOR.2022.127146

International Journal of Operational Research, 2022 Vol.45 No.3, pp.378 - 396

Received: 30 Aug 2019
Accepted: 09 Jan 2020
Published online: 23 Nov 2022 *

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