Evaluating the Performance of Quantum Annealers and Classical Optimizers in the Aircraft Container Loading Problem: A Feasibility Study

The aircraft load balancing problem refers to arranging aircraft cargo such that the center of gravity (CoG) is in the optimal position. This problem is high impact in terms of safety and profitability, but is currently solved manually, leading to potentially suboptimal solutions and long lead times. In this study, we investigate the performance of quantum annealing in solving the problem, comparing performance with classical solvers. Our results indicate that for smaller problems, the classical solvers are faster and return higher-quality solutions, but the quantum annealers have more favourable time scaling, which indicates a potential quantum advantage for larger problems. However, for larger problem sizes the annealer fails to return any feasible solution, which indicates that the problem would need to be reformulated to reduce size in order to achieve quantum advantage.

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Published
2025-08-30
DOI
https://doi.org/10.1109/qce65121.2025.10376
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
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article

Evaluating the Performance of Quantum Annealers and Classical Optimizers in the Aircraft Container Loading Problem: A Feasibility Study

David Headley, Thomas Groß, Salvatore Sinno, Markus Bertl et al.
Quantum Computing Algorithms and Architecture
article

Evaluating the Performance of Quantum Annealers and Classical Optimizers in the Aircraft Container Loading Problem: A Feasibility Study

David Headley, Thomas Groß, Salvatore Sinno, Markus Bertl, Nicholas Chancellor, Κωνσταντίνος Γεωργόπουλος, Alan Mott, Manav Babel
article en

Abstract

The aircraft load balancing problem refers to arranging aircraft cargo such that the center of gravity (CoG) is in the optimal position. This problem is high impact in terms of safety and profitability, but is currently solved manually, leading to potentially suboptimal solutions and long lead times. In this study, we investigate the performance of quantum annealing in solving the problem, comparing performance with classical solvers. Our results indicate that for smaller problems, the classical solvers are faster and return higher-quality solutions, but the quantum annealers have more favourable time scaling, which indicates a potential quantum advantage for larger problems. However, for larger problem sizes the annealer fails to return any feasible solution, which indicates that the problem would need to be reformulated to reduce size in order to achieve quantum advantage.

National Society for the Prevention of Cruelty to Children (GB), Newcastle University (GB), Unisys (United States) (US)
Openalex Percentile: Top 80%
Quantum Computing Algorithms and Architecture
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Evaluating the Performance of Quantum Annealers and Classical Optimizers in the Aircraft Container Loading Problem: A Feasibility Study — David Headley, Thomas Groß, et al. · (2025) | TGRS Research Map | TGRS