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Air traffic scheduling near airports is a complex task, particularly during landings where aircraft must maintain strict temporal separations at waypoints. Disruptions such as in-flight delays can lead to trajectory conflicts, which are typically mitigated by adjusting arrival times, which effectively issues speed advisories to pilots. This paper introduces a quantum optimization approach for this problem by encoding it as a Quadratic Unconstrained Binary Optimization (QUBO) instance. We further investigate how two variational algorithms, Quantum Approximate Optimization Algorithm (QAOA) and Variational Quantum Eigensolver (VQE), perform on this highly constrained problem compared to an unconstrained benchmark (MaxCut), highlighting the additional complexity introduced by constraints in quantum optimization.

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Constrained Quantum Optimization for Scheduling Aircraft Arrivals

  • 会议论文

  • 发表日期：

    2026年

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  • Gaspard Cassassolles,
  • Hian Lee Kwa,
  • Teck Yoong Chai,
  • Yung Sze Gan

摘要

Air traffic scheduling near airports is a complex task, particularly during landings where aircraft must maintain strict temporal separations at waypoints. Disruptions such as in-flight delays can lead to trajectory conflicts, which are typically mitigated by adjusting arrival times, which effectively issues speed advisories to pilots. This paper introduces a quantum optimization approach for this problem by encoding it as a Quadratic Unconstrained Binary Optimization (QUBO) instance. We further investigate how two variational algorithms, Quantum Approximate Optimization Algorithm (QAOA) and Variational Quantum Eigensolver (VQE), perform on this highly constrained problem compared to an unconstrained benchmark (MaxCut), highlighting the additional complexity introduced by constraints in quantum optimization.