Airline disruption management: dynamic aircraft scheduling with ant colony optimization

Abstract

Disruption management is one of the main concerns of any airline company, as it can influence its annual revenue by upwards of 3%. Most of medium to large airlines have specialized teams which focus on recovering disrupted schedules with very little automation. This paper presents a new automated approach to solve both the Aircraft Assignment Problem (AAP) and the Aircraft Recovering Problem (ARP), where the solutions are responsive to unforeseen events. The developed algorithm, based on Ant Colony Optimization, aims to minimize the operational costs involved and is designed to schedule and reschedule flights dynamically by using a sliding window. Test results tend to indicate that this approach is feasible, both in terms of time and quality of the proposed solutions.