Quantum Optimization for Airline Fleet Assignment

Assigning aircraft to an airline’s flight schedule is a highly complex optimization problem. The process must simultaneously satisfy a large number of operational constraints, including airport time windows, aircraft rotations, maintenance requirements, and fleet availability. These constraints interact across the entire network, making the scheduling problem computationally challenging.

At Vueling, a European airline, parts of this process remain time-consuming and require significant manual intervention. This can lead to inefficiencies in aircraft utilization and increases the difficulty of adapting schedules when disruptions occur.

To explore new approaches to this challenge, Lighthouse Disruptive Innovation Group (LDIG)—a member company of the MIT Media Lab ecosystem—collaborated with the City Science group to investigate the potential of quantum-enabled optimization methods. The project evaluated the use of D-Wave’s hybrid quantum–classical computing framework to model and solve the aircraft assignment problem.

The initial objective was to explore whether hybrid quantum optimization techniques could improve aircraft utilization while minimizing schedule disruptions across the airline network. Early results demonstrate that hybrid quantum computing approaches can effectively address realistic instances of airline scheduling problems, providing promising evidence of their applicability to large-scale operational optimization.

This ongoing research aims to further expand the model to incorporate additional operational constraints and to investigate how emerging quantum computing technologies may support complex decision-making in large transportation networks. Optimizing Aircraft Utilization with Quantum Computing at Vueling Airlines