Wei Ming, Sun Bo, Wu Wei, Jing Bin Bin
School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China.
CAAC Key Laboratory of General Aviation Operation, Civil Aviation Management Institute of China, Beijing 102202, China.
Math Biosci Eng. 2020 Aug 17;17(5):5545-5560. doi: 10.3934/mbe.2020298.
This study proposes a multi-objective mixed integer linear programming (MOMILP) model for assigning a set of flights to different runways and determining their actual arrival and departure times. The proposed model envisages unique operation model of each runway (i.e., takeoff, landing, or mixed takeoff and landing). Further, interference in two flights between adjacent runways are also fully considered in this model. The work aims at reveal the optimal relationship between traffic stream characteristics, operation mode of each runway and flight scheduling to simultaneously minimizing flight delays and maximizing runway utilization. Since the problem of interest has a non-deterministic polynomial (NP-hard) complexity, a heuristic-based non-dominated sorting genetic algorithm (NSGA-II) is also presented to find Pareto-optimal solutions in a reasonable amount of time, where coding structure and heuristic algorithm for producing initial population are defined. Finally, a real-world example is provided to compare the difference in quality between the proposed and traditional models, and reveal changes in trends between delay time of flights and idle time of the runways, which can verify the correctness of the model.
本研究提出了一种多目标混合整数线性规划（MOMILP）模型，用于将一组航班分配到不同跑道并确定其实际到达和出发时间。所提出的模型设想了每个跑道的独特运行模式（即起飞、降落或混合起飞和降落）。此外，该模型还充分考虑了相邻跑道之间两架航班的干扰。这项工作旨在揭示交通流特征、每个跑道的运行模式和航班时刻表之间的最优关系，以同时最小化航班延误并最大化跑道利用率。由于所关注的问题具有非确定性多项式（NP难）复杂度，还提出了一种基于启发式的非支配排序遗传算法（NSGA-II），以便在合理的时间内找到帕累托最优解，其中定义了编码结构和用于生成初始种群的启发式算法。最后，提供了一个实际例子，以比较所提出的模型与传统模型在质量上的差异，并揭示航班延误时间和跑道空闲时间之间趋势的变化，这可以验证模型的正确性。
