Optimization model of flight time and frequency under operation mode of multi-airports system
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摘要: 针对枢纽机场的拥堵问题, 提出了机场群航班时刻与频率优化策略。应用运输需求管理理论, 以旅客最小出行损失时间为目标函数, 以旅客流失率与航空公司客座率为约束条件, 建立了基于机场群运行方式的航班时刻与频率优化模型。根据机场群内5个机场的地面交通时间与枢纽机场的航班数量与平均延误的关系, 将机场群内各个机场的旅客需求进行分类, 采用k-means聚类算法, 计算了航班时刻与频率、旅客出行损失时间、机型与数量分配方式。计算结果表明: 在机场群运行方式下, 旅客需求分为7类, 满足全部旅客需求的航班数量为11个, 旅客出行损失时间为123 403min; 在独立运行方式下, 旅客需求分为8类, 满足全部旅客需求的航班数量为13个, 旅客出行损失时间为165 343min; 在机场群运行方式下, 采用遗传算法求得的满足全部旅客需求的航班数量为11个, 旅客出行损失时间为126 119min。Abstract: Aiming at congestion problem at hub airport, the optimization strategy of flight time and frequency for multi-airports system was put out.The transportation demand management theory was used, the minimum trip lost time of passenger was taken as objective function, the passenger wastage rate and the occupancy rate of airline were taken as constraint conditions, and the optimization model of flight time and frequency based on operation mode of multi-airports system was established.According to the ground traffic times of 5airports in multi-airports system and the relation between flight amount and average delay for hub airport, passenger demand in each airport was classified, and the flight time and frequency, the trip lost time of passenger and the distribution modes of aircraft type and amount were calculated by using k-means clustering algorithm.Calculation result shows that under the operatiom mode of multiairports system, passenger demand is classified into 7classes, the flight amount satisfied all passenger demands is 11, and the trip lost time of all passengers is 123 403 min.Under the independent operation mode, passenger demand is classified into 8classes, the flight amount satisfied all passenger demands is 13, and the trip lost time of all passengers is 165 343min.Under the operation mode of multi-airports system, the flight amount satisfied all passenger demands is 11, and the trip lost time of all passengers is 126 119min by using genetic algorithm.
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Key words:
- air transportation /
- multi-airports system /
- flight delay /
- flight time /
- flight frequency /
- clustering algorithm /
- genetic algorithm
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表 4 机场群运行方式下的航班时刻与频率
Table 4. Flight times and frequencies under operation mode of multi-airports system
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表 5 机场群运行方式下的分类结果
Table 5. Classification result under operation mode of multi-airports system
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表 6 独立运行方式下的航班时刻与频率
Table 6. Flight times and frequencies under independent operation mode
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[1] 李雄, 刘光才, 颜明池, 等. 航班延误引发的航空公司及旅客经济损失[J]. 系统工程, 2007, 25 (12): 20-23. doi: 10.3969/j.issn.1001-4098.2007.12.004LI Xiong, LIU Guang-cai, YAN Ming-chi, et al. The economic loss of airlines and passengers caused by flight delays[J]. Systems Engineering, 2007, 25 (12): 20-23. (in Chinese). doi: 10.3969/j.issn.1001-4098.2007.12.004 [2] ABEVRATNE R I R. Management of airport congestion through slot allocation[J]. Journal of Air Transport Management, 2000, 6 (1): 29-41. doi: 10.1016/S0969-6997(99)00019-8 [3] BRUECKNER J K. Airport congestion when carriers have market power[J]. American Economic Review, 2002, 92 (5): 1357-1375. doi: 10.1257/000282802762024548 [4] SENTANCE A. Airport slot auctions: desirableorfeasible?[J]. Utilities Policy, 2003, 11 (1): 53-57. doi: 10.1016/S0957-1787(02)00058-9 [5] PELS E, VERHOEF E T. The economics of airport congestion pricing[J]. Journal of Urban Economics, 2004, 55 (2): 257-277. doi: 10.1016/j.jue.2003.10.003 [6] VERHOEF E T. Congestion pricing, slot sales and slot trading in aviation[J]. Transportation Research Part B: Methodological, 2010, 44 (3): 320-329. doi: 10.1016/j.trb.2009.07.002 [7] 刘光才, 刘雷. 美国减少航班延误的有效途径及启示[J]. 技术经济与管理研究, 2010 (4): 92-96. doi: 10.3969/j.issn.1004-292X.2010.04.022LIU Guang-cai, LIU Lei. The effective ways to reduce flight delays in U. S. and their revelation to China[J]. Technoeconomics and Management Research, 2010 (4): 92-96. (in Chinese). doi: 10.3969/j.issn.1004-292X.2010.04.022 [8] 刘光才, 庄文武. 我国航班起降时刻分配和管理机制研究[J]. 经济问题探索, 2008 (4): 185-190. https://www.cnki.com.cn/Article/CJFDTOTAL-JJWS200804042.htmLIU Guang-cai, ZHUANG Wen-wu. Research on flights takeoff and landing time allocation and management mechanism in China[J]. Inquiry into Economic Issues, 2008 (4): 185-190. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JJWS200804042.htm [9] BRUECKNER J K. Price vs. quantity-based approaches to airport congestion management[J]. Journal of Public Economics, 2009, 93 (5): 681-690. [10] VAZE V, BARNHART C. Modeling airline frequency competition for airport congestion mitigation[J]. Transportation Science, 2012, 46 (4): 512-535. doi: 10.1287/trsc.1120.0412 [11] FLORES-FILLOL R. Congested hubs[J]. Transportation Research Part B: Methodological, 2010, 44 (3): 358-370. [12] WANG Yan-jun, HU Ming-hua, SUI Dong, et al. Departure scheduling in a multi-airport system[C]//IEEE. 8th USA/Europe Air Traffic Management Research and Development Seminar. Napa: IEEE, 2009: 126-135. [13] 朱承元, 王馨悦, 刁琳. 珠三角地区航班延误的仿真分析[J]. 常州工学院学报, 2011, 24 (5): 36-40. https://www.cnki.com.cn/Article/CJFDTOTAL-CZGB201105011.htmZHU Cheng-yuan, WANG Xin-yue, DIAO Lin. Simulation analysis of flight delays in Pearl River Delta Region[J]. Journal of Changzhou Institute of Technology, 2011, 24 (5): 36-40. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CZGB201105011.htm [14] WINDLE R, DRESNER M. Airport choice in multiple-airport regions[J]. Journal of Transportaion Engineering, 1995, 121 (4): 332-337. [15] TAM M L, LAM W H K, LO H P. Modeling air passenger travel behavior on airport ground access mode choices[J]. Transportmetrica, 2008, 4 (2): 135-153. [16] 杨广全, 朱昌明, 王向红, 等. 基于粒子群k均值聚类算法的电梯交通模式识别[J]. 控制与决策, 2007, 22 (10): 1139-1142. https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC200710013.htmYANG Guang-quan, ZHU Chang-ming, WANG Xianghong, et al. Elevator traffic pattern recognition based on particle swarm optimization k-means clustering algorithm[J]. Control and Decision, 2007, 22 (10): 1139-1142. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC200710013.htm [17] WEI Wen-bin, HANSEN M. Cost economics of aircraft size[J]. Journal of Transport Economics and Policy, 2003, 37 (2): 279-296. [18] MEYER M D. Demand management as an element of transportation policy: using carrots and sticks to influence travel behavior[J]. Transportation Research Part A: Policy and Practice, 1999, 33 (7/8): 575-599. [19] 王汝昕, 何秋钊, 曾灏. 基于TDM策略的支线机场资源需求分析与预测探讨[J]. 中国民航飞行学院学报, 2011, 22 (4): 16-19. https://www.cnki.com.cn/Article/CJFDTOTAL-MHFX201104005.htmWANG RU-xin, HE Qiu-zhao, ZENG Hao. Analysis on requirement and prediction of feeder airport resources based on TDM[J]. Journal of Civil Aviation Flight University of China, 2011, 22 (4): 16-19. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-MHFX201104005.htm -
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