Optimal airline de-ice scheduling

TL;DR

This paper introduces a decision support framework using MILP for optimal flight rescheduling during winter weather to minimize delays and cancellations, demonstrated through a case study of Horizon Air.

Contribution

It develops a decomposable MILP model for airline rescheduling during de-icing events, enabling efficient solutions and practical application.

Findings

Model effectively reduces delays and cancellations.

Decomposition approach improves computational efficiency.

Case study validates practical utility of the framework.

Abstract

We present a decision support framework for optimal flight rescheduling on an airline's day of operations when de-icing becomes necessary due to snow and ice events. Winter weather, especially in areas where such weather is not commonplace, often causes cascading delays and cancellations throughout the system due to the unforeseen need to add de-ice time to each aircraft's turnaround time. Our model optimally reschedules remaining flights of the day to minimize system delays and cancellations. The model is formulated as a mixed integer linear program (MILP). Structural properties of the model allow it to be decomposed into a finite set of linear programs (LP) and a computationally tractable algorithm for its solution is described. Finally, numerical simulations are presented for a case study of Horizon Air, a regional airline based in the Pacific Northwest of the United States.