Airline Fleet Assignment Problems with Binary and Integer Programming models: Classical vs Quantum Annealing

TL;DR

This paper explores the use of quantum annealing for airline fleet assignment problems, comparing its performance with classical methods and discussing its potential and limitations for large-scale optimization.

Contribution

It provides a comparative analysis of classical and quantum annealing approaches for fleet assignment, highlighting the potential of quantum methods in aviation optimization.

Findings

Quantum annealing shows promise for large-scale problems.

Classical methods remain more reliable for certain problem sizes.

The study identifies current limitations of quantum annealing in this context.

Abstract

This research highlights the potential of quantum annealing in tackling large-scale optimization problems within the airline industry,demonstrating its efficiency for certain problem sizes while also acknowledging its current limitations. The comparative analysis provides valuable insights into the performance of advanced computational techniques, paving the way for further advancements in optimizing fleet assignments in the aviation sector.