Abstract
Disruptions in airline operations are not uncommon and can interrupt smooth and efficient passenger transportation, especially during extreme weather conditions and hurricanes. Airline operations can be severely affected and/or halted for the duration of these phenomena. In order to develop tools to implement proper recovery actions for different stakeholders during a disruption present in an air transportation system, prior hurricane data analysis is crucial. This work focuses on analyzing a large set of airline data during Hurricane Matthew in 2016 to obtain meaningful insights regarding the affected airports and airlines. Our analysis also predicts the number of affected airline passengers during the hurricane. The results of our study show that Orlando International Airport (MCO) and Southwest Airlines were the most affected airport and airline, respectively. Our findings further reveal that certain airline passengers were affected before and after the day of the hurricane.
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