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基于多目标混合启发式算法的协同无冲突4D航迹规划

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  • 国家科技期刊平台
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为促进基于航迹运行的框架下未来空中交通管理系统的协同决策,本文提出了一种协同无冲突4D航迹规划方法.首先以提高航班效率和航空公司间的公平性为目标,以无冲突为约束构建了一个多目标整数线性优化模型.其次,提出了一种基于基尼系数的指标以量化航空公司间的成本分配公平性.为了提高问题求解效率,采用了基于网格的探测方法以加速冲突检测,并设计了一种多目标混合启发式算法(Multi-objective hybrid-meta-heuristic optimization algorithm,MHMOA),通过结合模拟退火(Simulated annealing,SA)和爬山局部搜索算法来近似最优的非支配解.最后,利用实际航班计划和航路网络数据比较和分析了MHMOA、SA和两种常规多目标优化算法的优化结果.结果表明,MHMOA所获得的非支配解的质量更高、延误更低且航空公司间公平性更优,在3个多目标优化性能指标方面表现优异,可为空中交通管理员提供更详细的决策支持.
Collaborative Conflict-Free 4D Trajectory Planning Based on Multi-objective Hybrid-Metaheuristic Optimization Algorithm
To facilitate collaborative decision making in future air traffic management systems under the trajectory based operation framework,a collaborative conflict-free four-dimensional(4D)trajectory planning method is proposed.Firstly,a multi-objective integer linear optimization model is developed to improve flight efficiency and inter-airline equity under conflict-free constraint.Secondly,a Gini coefficient-based metric is formulated to quantify the inter-airline equity of operation cost allocation.Thirdly,to improve the problem-solving efficiency,a grid-based conflict detection method is employed to accelerate conflict detection and a multi-objective hybrid-metaheuristic optimization algorithm(MHMOA)is designed to approximate the optimal non-dominated solutions by combining the simulated annealing(SA)and hill-climbing local search algorithms.Finally,the optimization results of the MHMOA,SA and two conventional multi-objective optimization algorithms are compared and analyzed using the actual flight plan and route network data.The results indicate that MHMOA can obtain higher-quality non-dominated solutions with lower delays,flight level shifts and better equity than other three algorithms,and outperform in terms of three multi-objective optimization performance metrics.The obtained solution can provide more detailed decision support for air traffic managers.

air traffic managementflight trajectory planninghybrid-metaheuristic optimization algorithmfour-dimensional(4D)trajectorymulti-objective optimization

周逸、胡明华、杨磊、张颖

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南京航空航天大学民航学院,南京 211106,中国

空中交通管理系统全国重点实验室,南京 211106,中国

南京航空航天大学通用航空与飞行学院,南京 211106,中国

空中交通管理 航迹规划 混合启发式算法 4D航迹 多目标优化

National Key R&D Program of ChinaNational Natural Science Foundation of ChinaNatural Science Foundation of Jiangsu Province

2022YFB430090561903187BK20190414

2024

10.16356/j.1005-1120.2024.03.009

南京航空航天大学学报(英文版)
南京航空航天大学

南京航空航天大学学报(英文版)

CSTPCD
影响因子：0.279
ISSN：1005-1120
年,卷(期)：2024.41(3)
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