一种量子增强的启发式算法,用于优化低海拔智能运输系统中的飞机着陆问题
Yong Lu1, Shikang Chen2, Xukun Zhang3
1School of Information Engineering, Minzu University of China, Beijing, 100080, China. yong@muc.edu.cn.
Scientific reports
|July 2, 2025
概括
本研究介绍了一种量子增强的鱼优化算法 (QEWOA),以优化飞机降落时间表. QEWOA有效地解决了复杂的优化挑战,提高了低空载人飞行器的精度和速度.
科学领域:
- 航空航天工程 航空航天工程
- 量子计算是一种量子计算.
- 运营研究 运营研究
背景情况:
- 低空经济的扩张需要对载人飞行器进行高效的调度.
- 飞机着陆时间窗口的优化是一个复杂的,高维度的问题,易于局部优化.
- 现有的优化方法难以应对这些调度任务的复杂性和规模.
研究的目的:
- 为飞机着陆时间窗的问题开发一种新的优化算法.
- 在复杂的优化任务中增强全球搜索能力并逃避局部优化.
- 为了提高低空载人飞行器降落时间表优化的效率和精度.
主要方法:
- 开发一个量子增强的鱼优化算法 (QEWOA).
- 集成量子随机数发生器,以改善最初的人口多样性.
- 整合了一种增强的量子道机制,以逃避局部最佳.
- 与人工蜂群算法混合,以加强全球和本地搜索.
主要成果:
- QEWOA显著提高了全球搜索能力.
- 与传统方法相比,该算法实现了更高的优化精度.
- 在解决复杂的调度问题时,QEWOA 显示了增强的融合速度.
- 实验验证证证实了优化着陆时间窗口的卓越性能.
结论:
- 量子增强鱼优化算法 (QEWOA) 为优化飞机着陆时间表提供了一个强大的解决方案.
- QEWOA有效地克服了局部优化的局限性,并提高了搜索效率.
- 这种方法为管理低空载人飞行器操作提供了重大进展.
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