|Table of Contents|

Dynamic multi-objective optimization model of arrival anddeparture flights on multiple runways based on RHC-GA(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2015年02期
Page:
70-
Research Field:
交通运输规划与管理
Publishing date:

Info

Title:
Dynamic multi-objective optimization model of arrival anddeparture flights on multiple runways based on RHC-GA
Author(s):
ZHANG Qi-qian HU Ming-hua ZHANG Hong-hai
School of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China
Keywords:
air transportation flight management flight schedule multiple runways receding horizon control genetic algorithm
PACS:
V355
DOI:
-
Abstract:
The minimum control workload and flight delay were taken as objective functions, wake turbulence separation, runway restriction and the maximum position limit were taken as constraint conditions, and the dynamic multi-objective optimization model of arrival and departure flights on multiple runways based on RHC-GA was set up by considering the latest operation standards of Civil Aviation Administration of China. For the large solution scale of the proposed model, genetic algorithm was designed to solve the proposed model with the dynamic characteristics of receding horizon control strategy, and the 48 flights data in the peak period of a large Chinese busy airport were selected to verify the model. Simulation result shows that when the unit flight costs of heavy, medium and light aircrafts are 25, 16, 10 yuan·s-1 respectively, the total delay cost is 36 098 yuan and the control workload is 32 sorties by using the first come first served(FCFS)strategy. The total delay cost is 28 900 yuan and the control workload is 31 sorties by using the receding horizon control strategy with 5 receding horizons, the total delay cost is 27 375 yuan and the control workload is 32 sorties by using the receding horizon control strategy with 4 receding horizons, and the total delay cost is 27 194 yuan and the control workload is 33 sorties by using the receding horizon control strategy with 3 receding horizons. Compared with the existing FCFS strategy, the proposed model is able to optimize the multi-runway sequencing problem of arrival and departure flights more dynamically, and the total delay cost reduces more efficiently and the runway resource could be utilized more evenly. 3 tabs, 14 figs, 25 refs.

References:

[1] LAMBRECHT M, SLATER G L. Departure trajectory modeling for air traffic control automation tools[C]∥AIAA. Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit. Reston: AIAA, 1999: 1507-1520.
[2] BOLENDER M A, SLATER G L. Cost analysis of the departure-en route merge problem[J]. Journal of Aircraft, 2000, 37(1): 23-29.
[3] TRIVIZAS D A. Optimal scheduling with maximum position shift(MPS)constraints: a runway scheduling application[J]. Journal of Navigation, 1998, 51(2): 250-266.
[4] KARI A, HALL W, ATKINS S, et al. Optimization-based analysis of collaborative airport arrival planning[J]. Transportation Science, 2003, 37(4): 422-433.
[5] BEASLEY J E, KRISHNAMOORTHY M, SHARAIHA Y M, et al. Scheduling aircraft landings—the static case[J]. Transportation Science, 2000, 34(2): 180-197.
[6] SOOMER M J, FRANX G J. Scheduling aircraft landings using airlines’ preferences[J]. European Journal of Operational Research, 2008, 190(1): 277-291.
[7] BEASLEY J E, KRISHNAMOORTHY M, SHARAIHA Y M, et al. Displacement problem and dynamically scheduling aircraft landings[J]. Journal of the Operational Research Society, 2004, 55(1): 54-64.
[8] HANSEN J V. Genetic search methods in air traffic control[J]. Computers and Operations Research, 2004, 31(3): 445-459.
[9] HU Xiao-bing, PAOLO E D. An efficient genetic algorithm with uniform crossover for air traffic control[J]. Computers and Operations Research, 2009, 36(1): 245-259.
[10] 程晓航,薛惠锋,洪鼎松,等.进港飞机调度的精华自适应遗传算法设计[J].交通与计算机,2006,24(6):91-94.CHENG Xiao-hang, XUE Hui-feng, HONG Ding-song, et al. Design of elitist adaptive genetic algorithm in arrival aircrafts scheduling[J]. Computer and Communications, 2006, 24(6): 91-94.(in Chinese)
[11] 孙 宏,张 翔,徐 杰.应用模拟退火算法求解飞机调度问题[J].飞行力学,2006,24(4):84-87. SUN Hong, ZHANG Xiang, XU Jie. Applying the simulated annealing algorithm to solve airliner aircraft dispatching problem[J]. Flight Dynamics, 2006, 24(4): 84-87.(in Chinese)
[12] 王海东,孙淑光,华克强.模糊Petri网在飞机进近排序中的应用[J].系统仿真学报,2007,19(18):4298-4301.WANG Hai-dong, SUN Shu-guang, HUA Ke-qiang. Applications of fuzzy Petri net method in aircraft approach sequencing[J]. Journal of System Simulation, 2007, 19(18): 4298-4301.(in Chinese)
[13] 李志荣,张兆宁.基于蚁群算法的航班着陆排序[J].交通运输工程与信息学报,2006,4(2):66-69.LI Zhi-rong, ZHANG Zhao-ning. Prioritizing landing flights based on ACS[J]. Journal of Transportation Engineering and Information, 2006, 4(2): 66-69.(in Chinese)
[14] ERNST A T, KRISHNAMOORTHY M, STORER R H. Heuristic and exact algorithms for scheduling aircraft landings[J]. Networks, 1999, 34(3): 229-241.
[15] 应圣钢,孙富春,胡来红,等.基于多目标动态规划的多跑道进港排序[J].控制理论与应用,2010,27(7):827-835.YING Sheng-gang, SUN Fu-chun, HU Lai-hong, et al. Multi-objective dynamic programming algorithm for aircraft arrival sequencing and runway scheduling[J]. Control Theory and Applications, 2010, 27(7): 827-835.(in Chinese)
[16] 周 茜,张学军,柳重堪.CDM GDP程序中混合使用跑道时隙分配问题研究[J].空中交通管理,2005(5):23-26.ZHOU Qian, ZHANG Xue-jun, LIU Zhong-kan. Study on time slot allocation for mixed runway application in CDM GDP program[J]. Air Traffic Management, 2005(5): 23-26.(in Chinese)
[17] CAPRI S, IGNACCOLO M. Genetic algorithms for solving the aircraft-sequencing problem: the introduction of departures into the dynamic model[J]. Journal of Air Transport Management, 2004, 10(5): 345-351.
[18] EUN Y, HWANG I, BANG H. Optimal arrival flight sequencing and scheduling using discrete airborne delays[J]. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(2): 359-373.
[19] MALAEK S M B, NADERI E. A new scheduling strategy for aircraft landings under dynamic position shifting[C]∥IEEE. 2008 IEEE Aerospace Conference. New York: IEEE, 2008: 1-8.
[20] LEE H, BALAKRISHNAN H. Fuel cost, delay and throughput tradeoffs in runway scheduling[C]∥IEEE. Proceedings of American Control Conference. New York: IEEE, 2008: 2449-2454.
[21] 张洪海,胡明华.多跑道着陆飞机协同调度多目标优化[J].西南交通大学学报,2009,44(3):402-409.ZHANG Hong-hai, HU Ming-hua. Multi-objection optimization for collaborative scheduling aircraft landing on multi-runways[J]. Journal of Southwest Jiaotong University, 2009, 44(3): 402-409.(in Chinese)
[22] 张启钱,胡明华,施赛锋,等.多跑道航班起降调度优化算法[J].交通运输工程学报,2012,12(6):63-68.ZHANG Qi-qian, HU Ming-hua, SHI Sai-feng, et al. Optimization algorithm of flight takeoff and landing on multirunways[J]. Journal of Traffic and Transportation Engineering, 2012, 12(6): 63-68.(in Chinese)
[23] 陈炜炜,耿 睿,崔德光.进近区域到达航班排序和调度的优化[J].清华大学学报:自然科学版,2006,46(1):157-160. CHEN Wei-wei, GENG Rui, CUI De-guang. Optimization of sequencing and scheduling for arrival aircrafts in approach area[J]. Journal of Tsinghua University: Science andTechnology, 2006, 46(1): 157-160.(in Chinese)
[24] 杨晶妹.终端区进场航班排序方法研究[D].南京:南京航空航天大学,2010.YANG Jing-mei. Research on algorithms for scheduling arrival aircrafts in terminal area[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2010.(in Chinese)
[25] 游进军,纪昌明,付 湘.基于遗传算法的多目标问题求解方法[J].水利学报,2003,7(7):64-69.YOU Jin-jun, JI Chang-ming, FU Xiang. New method for solving multi-objective problem based on genetic algorithm[J]. Journal of Hydraulic Engineering, 2003, 7(7): 64-69.(in Chinese)

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Last Update: 2015-04-30