TY - JOUR
T1 - Overcoming computational challenges in air transportation
T2 - A quantum computing perspective of the status quo and future applicability
AU - Du, Zhuoming
AU - Wandelt, Sebastian
AU - Sun, Xiaoqian
N1 - Publisher Copyright:
© 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
PY - 2026/3
Y1 - 2026/3
N2 - Recent research breakthroughs in quantum computing, such as Microsoft’s topological qubits, hold the promise of revolutionizing complex optimization problems, particularly in the air transportation industry. This study aims to estimate the mid-term scalability of quantum computing in air transportation, focusing on prevalent optimization problems including network design, airline scheduling, and gate assignment. These problems are computationally intensive and often intractable for classical computers due to their highly combinatorial nature. We develop a framework to assess the potential scalability of quantum algorithms for these problems, considering factors such as qubit count and error rates. Our findings suggest that significant advancements in quantum hardware and algorithms are necessary before quantum computing can outperform classical methods in this domain. Therefore, while quantum computing offers a promising tool for solving complex optimization problems in air transportation, its real-world application remains a distant goal. We believe that our work helps guiding researchers and industry professionals in their pursuit of quantum-enhanced air transport solutions.
AB - Recent research breakthroughs in quantum computing, such as Microsoft’s topological qubits, hold the promise of revolutionizing complex optimization problems, particularly in the air transportation industry. This study aims to estimate the mid-term scalability of quantum computing in air transportation, focusing on prevalent optimization problems including network design, airline scheduling, and gate assignment. These problems are computationally intensive and often intractable for classical computers due to their highly combinatorial nature. We develop a framework to assess the potential scalability of quantum algorithms for these problems, considering factors such as qubit count and error rates. Our findings suggest that significant advancements in quantum hardware and algorithms are necessary before quantum computing can outperform classical methods in this domain. Therefore, while quantum computing offers a promising tool for solving complex optimization problems in air transportation, its real-world application remains a distant goal. We believe that our work helps guiding researchers and industry professionals in their pursuit of quantum-enhanced air transport solutions.
KW - Air transportation
KW - Challenges
KW - Computational complexity
KW - Quantum computing
KW - Review
UR - https://www.scopus.com/pages/publications/105029761429
U2 - 10.1016/j.trc.2025.105505
DO - 10.1016/j.trc.2025.105505
M3 - 文章
AN - SCOPUS:105029761429
SN - 0968-090X
VL - 184
JO - Transportation Research Part C: Emerging Technologies
JF - Transportation Research Part C: Emerging Technologies
M1 - 105505
ER -