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摘要:
为了提高区域航路网络结构的科学性、减轻飞行流量增长对网络运行带来的压力,提出了基于航路点布局的多目标网络结构优化方法。首先,考虑区域航路网络的组成要素,设计了反映网络综合性能的优化目标和约束条件以形成优化模型。然后,建立基于节点移动、融合、分解的航路点布局策略,进而给出优化模型的求解步骤,并利用NSGA-Ⅲ算法完成模型求解。最后,对北京飞行情报区部分区域航路网络进行仿真分析,结果表明,使用NSGA-Ⅲ算法得出的区域航路网络具有良好的综合性能。最优网络在满足约束条件的同时,保证了运行费用和非直线系数基本不变,并使得飞行冲突系数减少了10.8%。可见,所提优化方法能有效提升区域航路网络的经济性、安全性和可行性,符合中国现行空域环境和管理体制。
Abstract:In order to improve the scientific nature of regional air route network structure and reduce the network operation pressure made by flight flow growth, a multi-objective network optimization method based on waypoint layout was proposed. First, the constituent elements of regional air route network were considered, and the optimization model was made with the design of optimization targets and constraint conditions which reflected the network comprehensive performance. Then, a waypoint layout strategy was established based on node movement, fusion and decomposition, so the solution procedure of optimization method was provided and the method can be solved by NSGA-Ⅲ algorithm. Finally, a simulation of partial regional air route network belonging to Beijing flight information region was analyzed and the results demonstrate excellent comprehensive performance of air route networks made by NSGA-Ⅲ algorithm. While the optimal network satisfies the constraint conditions, the operating cost and non-linear coefficient are basically unchanged, and the flight conflict coefficient is reduced by 10.8%. So this optimization method can promote economic efficiency, safety and feasibility of air route network, which conforms to current airspace environment and management system in China.
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表 1 移动航路点信息
Table 1. Information of mobile waypoint
航路点 汇聚航段交叉角 航路点流量/
(架次·h-1)航路点容量/
(架次·h-1)P13 ∠P11P13P12 11.4 20.96 P14 ∠P13P14P12 12.5 32.31 P15 ∠P12P15P14 12.9 38.03 P16 ∠P15P16P18 16.6 34.77 P17 ∠P16P17P6 14.9 27.04 P18 ∠P9P18P14 14.9 26.92 表 2 航段信息
Table 2. Information of air leg
航路 航段 长度/km 流量/(架次·h-1) B548 P11P12 216.9 8.8 A575 P11P13 124.9 5.7 A575 P15P4 59.0 6.9 H13 P2P12 49.5 10.6 H13 P18P19 120.0 6.5 H6 P15P16 58.9 8.2 B339 P9P18 179.2 8.4 J201 P6P17 18.9 6.1 B548 P12P3 113.17 7.2 A575 P13P14 96.7 5.8 G218 P12P13 129.7 5.7 H13 P12P14 122.6 6.7 H13 P19P8 96.7 5.9 H6 P16P17 37.7 8.8 B339 P18P16 148.5 8.4 J201 P17P19 195.7 6.4 A575 P1P11 35.47 10.5 A575 P14P15 122.6 6 G218 P13P10 141.5 5.7 H13 P14P18 99.0 6.5 H6 P12P15 198.0 6.9 H6 P17P7 51.9 8.7 B339 P16P5 30.7 7.8 表 3 区域航路网络特性指标
Table 3. Property indexes of regional air route network
网络序号 运行费用 飞行冲突系数 非直线系数 角度改变量/(°) ① 5.409×103 1.092 1.244 266.5 ② 5.425×103 0.954 1.251 268.1 ③ 5.413×103 0.972 1.245 238.7 ④ 5.418×103 0.971 1.246 216.5 ⑤ 5.437×103 0.969 1.257 282.3 ⑥ 5.495×103 0.879 1.276 330.2 ⑦ 5.424×103 1.151 1.248 215.9 ⑧ 5.405×103 1.089 1.227 63.34 -
[1] 王世锦, 公言会, 郦晴云.航路网络规划技术研究综述[J].交通信息与安全, 2014, 32(6):8-14. doi: 10.3963/j.issn.1674-4861.2014.06.002WANG S J, GONG Y H, LI Q Y.A review of air transportation network planning methods[J].Transportation Information and Safety, 2014, 32(6):8-14(in Chinese). doi: 10.3963/j.issn.1674-4861.2014.06.002 [2] 公言会.航路网络规划技术研究[D].南京: 南京航空航天大学, 2016.GONG Y H.Research on air route network planning technology[D].Nanjing: Nanjing University of Aeronautics and Astronautics, 2016(in Chinese). [3] CHEN D, HU M H, ZHANG H H, et al.A network based dynamic air traffic flow model for en route airspace system traffic flow optimization[J].Transportation Research Part E:Logistics and Transportation Review, 2017, 106:1-19. doi: 10.1016/j.tre.2017.07.009 [4] WANG S J, GONG Y H.Research on air route network nodes optimization with avoiding the three areas[J].Safety Science, 2014, 66:9-18. doi: 10.1016/j.ssci.2014.01.008 [5] WANG S J, LI Q Y, CAO X, et al.Optimization of air route network nodes to avoid "three areas" based on an adaptive ant colony algorithm[J].Transactions of Nanjing University of Aeronautics and Astronautics, 2016, 33(4):469-478. http://cn.bing.com/academic/profile?id=9814f5ff4e11646f97412ab34e178858&encoded=0&v=paper_preview&mkt=zh-cn [6] WANG S J, CAO X, LI H Y, et al.Air route network optimization in fragmented airspace based on cellular automata[J].Chinese Journal of Aeronautics, 2017, 30(3):1184-1195. doi: 10.1016/j.cja.2017.04.002 [7] DUNN S, WILKINSON S M.Increasing the resilience of air traffic networks using a network graph theory approach[J].Transportation Research Part E:Logistics and Transportation Review, 2016, 90:39-50. doi: 10.1016/j.tre.2015.09.011 [8] 康金霞.航路网络特征及其抗毁性研究[D].南京: 南京航空航天大学, 2016. http://cdmd.cnki.com.cn/Article/CDMD-10287-1016791245.htmKANG J X.Research on the structure and its invulnerability of China air route network[D].Nanjing: Nanjing University of Aeronautics and Astronautics, 2016(in Chinese). http://cdmd.cnki.com.cn/Article/CDMD-10287-1016791245.htm [9] 严伟, 王瑛, 孟祥飞, 等.航空网络航路点布局的多目标优化设计[J].空军工程大学学报, 2017, 18(6):20-26. doi: 10.3969/j.issn.1009-3516.2017.06.004YAN W, WANG Y, MENG X F, et al.A multi-objective optimization design for crossing waypoint location in air route network[J].Journal of Air Force Engineering University, 2017, 18(6):20-26(in Chinese). doi: 10.3969/j.issn.1009-3516.2017.06.004 [10] 郦晴云.基于交通流特征的航路网络节点布局优化[D].南京: 南京航空航天大学, 2016. http://cdmd.cnki.com.cn/Article/CDMD-10287-1016791258.htmLI Q Y.Air route network node optimization based on traffic flow feature[D].Nanjing: Nanjing University of Aeronautics and Astronautics, 2016(in Chinese). http://cdmd.cnki.com.cn/Article/CDMD-10287-1016791258.htm [11] DU W B, LIANG B Y, YAN G, et al.Identifying vital edges in Chinese air route network via memetic algorithm[J].Chinese Journal of Aeronautics, 2017, 30(1):330-336. doi: 10.1016/j.cja.2016.12.001 [12] SAVURAN H, KARAKAYA M.Efficient route planning for an unmanned air vehicle deployed on a moving carrier[J].Soft Computing, 2016, 20(7):2905-2920. doi: 10.1007/s00500-015-1970-4 [13] ZHANG X G, MAHADEVAN S.Aircraft re-routing optimization and performance assessment under uncertainty[J].Decision Support Systems, 2017, 96:67-82. doi: 10.1016/j.dss.2017.02.005 [14] KALYANMOY D, HIMANSHU J.An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach.Part Ⅰ:Solving problems with box constraints[J].IEEE Transactions on Evolutionary Computation, 2014, 18(4):577-601. doi: 10.1109/TEVC.2013.2281535 [15] BI X J, WANG C.An improved NSGA-Ⅲ algorithm based on elimination operator for many-objective optimization[J].Meme-tic Computing, 2017, 9(4):361-383. doi: 10.1007/s12293-017-0240-7 [16] 中国民用航空局.从统计看民航2017[M].北京:中国民航出版社, 2018.CAAC.From the statistical view of civil aviation 2017[M].Beijing:China Civil Aviation Press, 2018(in Chinese). [17] 李明娟.杰普逊航图及应用[M].北京:北京航空航天大学出版社, 2016.LI M J.Jeppesen charts and applications[M].Beijing:Beihang University Press, 2016(in Chinese).