用精确模型同时优化飞机维修场布局与时间安排，大幅提速且效果更优。
An Efficient Continuous-Time MILP for Integrated Aircraft Hangar Scheduling and Layout
- 构建连续时间混合整数规划模型，联合优化飞机位置与调度时间。
- 80架飞机内问题一小时内解出近优解，160架问题提供强界，40架可证最优。
- 实测提升33%维修吞吐量，适合航空运维与工厂规划人员参考。
高效管理飞机维修与保养（MRO）机库需将空间布局与时间连续调度整合，以降低运营成本。本文提出一种连续时间混合整数线性规划模型，联合优化飞机布置与时间安排，突破了以往方法的可扩展性瓶颈。通过全面基准测试对比构造启发式算法，研究了大规模问题性能及时间拥堵敏感性。该模型在文献基准上实现数量级加速，可在0.11秒内求解长期未解的拥堵实例，并对最多40架飞机的问题找到证明最优解。在单小时时限内，可为最多80架飞机的问题获得小间隙近优解，并对最多160架飞机的问题提供强边界。优化方案显著提升机库吞吐量（如实例RND-N030-I03中服务飞机数增加33%），降低延误惩罚并提高资产利用率。结果表明，精确优化已具备解决大规模机库规划的能力，为战略与运营决策提供高质量、高效率的验证工具。
原文摘要 · Abstract (English)
Efficient management of aircraft MRO hangars requires the integration of spatial layout with time-continuous scheduling to minimize operational costs. We propose a continuous-time mixed-integer linear program that jointly optimizes aircraft placement and timing, overcoming the scalability limits of prior formulations. A comprehensive study benchmarks the model against a constructive heuristic, probes large-scale performance, and quantifies its sensitivity to temporal congestion. The model achieves orders-of-magnitude speedups on benchmarks from the literature, solving a long-standing congested instance in 0.11 seconds, and finds proven optimal solutions for instances with up to 40 aircraft. Within a one-hour limit for large-scale problems, the model finds solutions with small optimality gaps for instances up to 80 aircraft and provides strong bounds for problems with up to 160 aircraft. Optimized plans consistently increase hangar throughput (e.g., +33% serviced aircraft vs. a heuristic on instance RND-N030-I03), leading to lower delay penalties and higher asset utilization. These findings establish that exact optimization has become computationally viable for large-scale hangar planning, providing a validated tool that balances solution quality and computation time for strategic and operational decisions.
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