基于时空关联网络的机场机位运行过程建模

doi:10.12305/j.issn.1001-506X.2021.03.16

系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (3): 722-730.doi: 10.12305/j.issn.1001-506X.2021.03.16

基于时空关联网络的机场机位运行过程建模

邢志伟¹(), 刘洪恩¹(), 李彪^1,²(), 罗谦³(), 文涛³(), 陈肇欣³()

1. 中国民航大学电子信息与自动化学院, 天津 300300
2. 中国民航大学航空工程学院, 天津 300300
3. 中国民用航空局第二研究所, 四川成都 610041

收稿日期:2020-04-12 出版日期:2021-03-01 发布日期:2021-03-16
作者简介:邢志伟(1970-), 男, 教授, 硕士研究生导师, 博士, 主要研究方向为民航装备与系统、民航智能规划与调度、机场运行控制与信息。E-mail:cauc_xzw@163.com|刘洪恩(1995-), 男, 硕士研究生, 主要研究方向为机场交通信息与控制。E-mail:13700516512@163.com|李彪(1993-), 男, 博士研究生, 主要研究方向为机场运行安全保障技术。E-mail:18330227730@163.com|罗谦(1975-), 男, 研究员, 硕士研究生导师, 博士, 主要研究方向为机场运营管理、数据挖掘。E-mail:caacsri_luoqian@163.com|文涛(1993-), 男, 工程师，硕士, 主要研究方向为机场运营管理、数据挖掘。E-mail:wentao@caacsri.com|陈肇欣(1988-), 男, 中级工程师, 博士, 主要研究方向为机场运营管理、数据挖掘。E-mail:chenzhaoxin@caacsri.com
基金资助:
国家重点研发计划(2018YFB1601200);中央高校基本科研业务费项目中国民航大学专项(3122019094)

Modelling for airport gate operation process based on relational spatio-temporal network

Zhiwei XING¹(), Hong'en LIU¹(), Biao LI^1,²(), Qian LUO³(), Tao WEN³(), Zhaoxin CHEN³()

1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
2. College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
3. The Second Research Institute of Civil Aviation Administration of China, Chengdu 610041, China

Received:2020-04-12 Online:2021-03-01 Published:2021-03-16

摘要/Abstract

摘要：

为了提高机场机位运行效率, 对机位运行过程进行精确分析描述。在分析机场进出港航班机位运行流程的基础上, 将机位运行过程抽象为时空关联网络，定性描述航班与机位的逻辑关系, 使用航班时间窗、机位地理位置等特征参数定量描述机位运行信息, 由此构建一种基于时空关联网络的机场机位运行过程定量描述模型。利用国内某大型枢纽机场实际机位运行数据对所提模型进行分析验证, 结果显示，时空关联网络模型符合幂律分布, 58.62%的节点平均误差为0.172 4 h, 节点度分布均值为0.666 7, 聚集系数均值为0.807 5。节点度分布较高和聚类系数较高的节点为关键节点, 对应影响力较大的关键航班；较现有模型, 描述态势信息的宏观微观特征参数提升了场景描述精度并能有效适应数据规模的变化。

关键词: 航空运输, 机位运行过程, 网络模型, 信息关联, 数据驱动

Abstract:

In order to improve the efficiency of the airport gate operation, this paper analyzes and describes the gate operation process accurately. Based on the analysis of the operation process of the airport inbound and outbound flights, the gate operation process is abstracted as a relational spatio-temporal network, the logical relationship between the flight and the gate is described qualitatively. The gate operation information is discribed quantitatively by using the flight time window, gate location and other characteristic parameters. A quantitative description model of airport gate operation process based on relational spatio-temporal network is proposed. The proposed model is verified by the actual gate operation data of a large domestic airport hub. The results show that, the relational spatio-temporal network model conforms to the power-law distribution, 58.62% of the average node error is 0.172 4 h, the average node degree distribution is 0.666 7, and the average clustering coefficient is 0.807 5. The nodes with higher node degree distribution and clustering coefficient are the key nodes, corresponding to the key flights with greater influence. Compared with the existing models, the macro and micro feature parameters of the situation information can improve the accuracy of scene description and effectively adapt to the change of data scale.

Key words: air transportation, gate operation process, network model, information association, data driving

中图分类号:

V351

邢志伟, 刘洪恩, 李彪, 罗谦, 文涛, 陈肇欣. 基于时空关联网络的机场机位运行过程建模[J]. 系统工程与电子技术, 2021, 43(3): 722-730.

Zhiwei XING, Hong'en LIU, Biao LI, Qian LUO, Tao WEN, Zhaoxin CHEN. Modelling for airport gate operation process based on relational spatio-temporal network[J]. Systems Engineering and Electronics, 2021, 43(3): 722-730.

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参考文献 33

1	KIM S H, FERON E, CLARKE J P. Airport gate assignment that minimizes passenger flow in terminals and aircraft congestion on ramps[C]//Proc.of the AIAA Guidance, Navigation and Control Conference, 2012.
2	STOLLENWERK T , LOBE E , JUNG M . Flight gate assignment with a quantum annealer[M]. FELD S, LINNHOFF-POPIEN C. Quantum Technology and Optimization Problems. Gemany: Springer, 2019.
3	DELL O M , MARINELLI M , ALTIERI M G . Solving the gate assignment problem through the fuzzy bee colony optimization[J]. Transportation Research Part C: Emerging Technologies, 2017, 80 (1): 424- 438.
4	MOSCHOULA P , ALI H . An aircraft-to-gate reassignment framework for dealing with schedule disruptions[J]. Journal of Air Transport Management, 2019, 78, 116- 132. doi: 10.1016/j.jairtraman.2019.01.005
5	JIANG X J, WANG X D. A multi-objective airport gate assignment problem considering clustered reservations for airline companies[EB/OL].[2020-03-30]. http://kns.cnki.net/kcms/detail/32.1389.V.20180210.1232.002.html.
6	GHAZOUANI H, HAMMAMI M, KORBAA O. Solving airport gate assignment problem using genetic algorithms approach[C]//Proc.of the 4th International Conference on Advanced Logistics and Transport, 2015: 175-180.
7	DENG W , ZHAO H M , YANG X H , et al. Study on an improved adaptive PSO algorithm for solving multi-objective gate assignment[J]. Applied Soft Computing, 2017, 59, 288- 302. doi: 10.1016/j.asoc.2017.06.004
8	ZHAO J M , WU W J , LIU Z . Airport gate assignment problem with deep reinforcement learning[J]. High Technology Letters, 2020, 26 (1): 102- 107.
9	NARCISO M E , PIERA M A . Robust gate assignment procedures from an airport management perspective[J]. Omega, 2015, 50, 82- 95. doi: 10.1016/j.omega.2014.06.003
10	邢志伟, 魏志强, 罗谦, 等. 基于着色时间Petri网的航班保障服务建模方法[J]. 系统工程与电子技术, 2018, 40 (5): 1064- 1069. doi: 10.3969/j.issn.1001-506X.2018.05.16
	XING Z W , WEI Z Q , LUO Q , et al. Flight support service process modeling method based on colored time Petri net[J]. Systems Engineering and Electronics, 2018, 40 (5): 1064- 1069. doi: 10.3969/j.issn.1001-506X.2018.05.16
11	YAN S , CHANG C M . A network model for gate assignment[J]. Journal of Advanced Transportation, 1998, 32 (2): 176- 189. doi: 10.1002/atr.5670320204
12	YAN S Y , CHEN C Y , TANG C H . Airport gate reassignment following temporary airport closures[J]. Transportmetrica, 2009, 5 (1): 25- 41. doi: 10.1080/18128600802591814
13	朱星辉, 吴薇薇, 戚彦龙. 基于延误传播的飞机排班一体化鲁棒优化模型[J]. 西南交通大学学报, 2015, 50 (2): 375- 381. doi: 10.3969/j.issn.0258-2724.2015.02.026
	ZHU X H , WU W W , QI Y L . Robust optimization model for integrated aircraft scheduling based on delay propagation[J]. Journal of Southwest Jiaotong University, 2015, 50 (2): 375- 381. doi: 10.3969/j.issn.0258-2724.2015.02.026
14	YU C H , ZHANG D , LAU H Y K . MIP-based heuristics for solving robust gate assignment problems[J]. Computers & Industrial Engineering, 2016, 93 (3): 171- 191.
15	ZHANG D , KLABJAN D . Optimization for gate re-assignment[J]. Transportation Research Part B: Methodological, 2017, 95 (1): 260- 284.
16	罗荣武, 谢如鹤, 张得志. 停机位分配问题的顶点着色模型及算法[J]. 系统工程理论与实践, 2007, 27 (11): 148- 152. doi: 10.3321/j.issn:1000-6788.2007.11.021
	LUO R W , XIE R H , ZHANG D Z . Vertex coloring model and algorithm of gate assignment[J]. Systems Engineering-Theory & Practice, 2007, 27 (11): 148- 152. doi: 10.3321/j.issn:1000-6788.2007.11.021
17	DORNDORF U , JAEHN F , PESCH E . Flight gate assignment and recovery strategies with stochastic arrival and departure times[J]. Or Spectrum, 2017, 39 (1): 1- 29. doi: 10.1007/s00291-015-0429-4
18	乐美龙, 黄文秀. 基于时空网络的航班机型分配问题研究[J]. 交通运输系统工程与信息, 2014, 14 (1): 81- 87, 108. doi: 10.3969/j.issn.1009-6744.2014.01.014
	LE M L , HUANG W X . Airline fleet assignment model based on time-space network[J]. Journal of Transportation Systems Engineering and Information Technology, 2014, 14 (1): 81- 87, 108. doi: 10.3969/j.issn.1009-6744.2014.01.014
19	孙璐, 周伟, 姜佰辰, 等. 一种时空联合约束的多源航迹相似性度量模型[J]. 系统工程与电子技术, 2017, 39 (11): 2405- 2413. doi: 10.3969/j.issn.1001-506X.2017.11.03
	SUN L , ZHOU W , JIANG B C , et al. Multi-source trajectories similarity measure model with spatial and temporal constraints[J]. Systems Engineering and Electronics, 2017, 39 (11): 2405- 2413. doi: 10.3969/j.issn.1001-506X.2017.11.03
20	秦进, 谭宇超, 张威, 等. 基于时空网络的城际高速铁路列车开行方案优化方法[J]. 铁道学报, 2020, 42 (2): 1- 10.
	QIN J , TAN Y C , ZHANG W , et al. Train planning optimization for intercity railway based on space-time network[J]. Journal of the China Railway Society, 2020, 42 (2): 1- 10.
21	KEISUKE M . Time-space network model and MILP formulation of the conflict-free routing problem of a capacitated AGV system[J]. Computers & Industrial Engineering, 2020, 141 (3): 106270.
22	CHAWLA V K , CHANDA A K , ANGRA S , et al. Simultaneous dispatching and scheduling of multi-load AGVs in FMS-A simulation study[J]. Materials Today: Proceedings, 2018, 5 (11): 25358- 25367. doi: 10.1016/j.matpr.2018.10.339
23	YANG Y S , ZHONG M S , DESSOUKY Y , et al. An integrated scheduling method for AGV routing in automated container terminals[J]. Computers & Industrial Engineering, 2018, 126 (12): 482- 493.
24	SCHAIJK O R P , VISSER H G . Robust flight-to-gate assignment using flight presence probabilities[J]. Transportation Planning and Technology, 2017, 40 (8): 928- 945. doi: 10.1080/03081060.2017.1355887
25	DENG W , SUN M , ZHAO H M , et al. Study on an airport gate assignment method based on improved ACO algorithm[J]. Kybernetes, 2018, 47 (1): 20- 43. doi: 10.1108/K-08-2017-0279
26	ZOGRAFOS K G , MASAS M A , ANDROUTSOPOULOS K N . Increasing airport capacity utilisation through optimum slot scheduling: review of current developments and identification of future needs[J]. Journal of Scheduling, 2017, 20 (1): 3- 24. doi: 10.1007/s10951-016-0496-7
27	SENA D G . New multi-objective models for the gate assignment problem[J]. Computers & Industrial Engineering, 2017, 109 (7): 347- 356.
28	ABDULLAH A , BETUL Y , TUNCAY Ö , et al. The comparison of the metaheuristic algorithms performances on airport gate assignment problem[J]. Transportation Research Procedia, 2017, 22, 469- 478. doi: 10.1016/j.trpro.2017.03.061
29	MOSCHOULA P , ALI H . Mathematical models for flight-to-gate reassignment with passenger flows: state-of-the-art comparative analysis, formulation improvement, and a new multidimensional assignment model[J]. Computers & Amp; Industrial Engineering, 2018, 123 (9): 103- 118.
30	LIN Y K , NGUYEN T P . Reliability evaluation of a multistate flight network under time and stopover constraints[J]. Computers & Industrial Engineering, 2018, 115 (1): 620- 630.
31	YU C Y , ZHANG D , LAU H Y K . An adaptive large neighborhood search heuristic for solving a robust gate assignment problem[J]. Expert Systems with Applications, 2017, 84 (10): 143- 154.
32	YU C Y , ZHANG D , LAU H Y K . A heuristic approach for solving an integrated gate reassignment and taxi scheduling problem[J]. Journal of Air Transport Management, 2017, 62 (7): 189- 196.
33	XU L , ZHANG C , XIAO F , et al. A robust approach to airport gate assignment with a solution-dependent uncertainty budget[J]. Transportation Research Part B: Methodological, 2017, 105 (11): 458- 478.

序号	进港航班号	出港航班号	计到	计飞	实到	实飞	进\|出港状态	进\|出港异常原因	机位号	机型
1	CZ3392	CZ3619	10:05	11:30	09:59	11:36	\|	—	12	B
2	CZ6478	CZ6478	20:40	21:35	20:07	21:51	+\|-	—	10	A
3	CZ3737	CZ3737	11:30	12:15	12:43	13:55	-\|-	飞机故障\|飞机故障	12	A
										
30	CZ3594	-	17:35	23:59	19:42	23:59	-\|**	对方机场天气\|-	01	A
31	CZ6010	-	22:00	23:59	22:21	23:59	-\|**	—	17	A

机型	对应参数
B738	A
B737	B
B733	C
A320	D

机位号	O_G	B_G	R_G	D_G	A_G(min/架次)
1	0.220 8	0	S2	1/1	127/1
2	0.150 7	0	S0	0/1	0/1
3	0.132 6	0	S0	0/1	0/1
					
19	0.159 7	1	S0	0/2	0/2
20	0.077 8	0	S0	0/1	0/1

N_A/个	H_A	ρ_A/(架次/h)	γ_A	R_A	D_A	A_A(min/架次)
20	20:41	49/24	22/49	5/49	16/49	696/49

网络参数	节点数	边数	最大度节点	网络密度	总路径长度	平均路径长度	网络聚类系数
参数值	29	147	24	0.362 1	902	2.073 6	0.807 5

基于时空关联网络的机场机位运行过程建模

Modelling for airport gate operation process based on relational spatio-temporal network

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