Hierarchy location optimization of low-altitude flight service station based on risk constraints

doi:10.16265/j.cnki.issn1003-3033.2023.05.2258

Abstract

Abstract:

In order to ensure the scientific operation of low-altitude general navigation flight service work, the risk constraint mechanism of service response and economic cost was introduced and MOGA was improved to study the location optimization of low-altitude flight service station. Based on analysis of low-altitude flight service support system, the functions of three service coverage modes for two types of demand were determined. According to the hardware and software constraints of low-altitude flight service station location, a risk-constrained hierarchical location decision mechanism and evaluation index were established. Based on coverage decision theory, a multi-objective optimization model of safety risk and service cost was established. Based on Pareto ranking, fitness conversion function was designed, and a multi-objective genetic algorithm with minus-max evaluation method was constructed. It was verified by using 250 000 km² of Sichuan Basin. Compared with dynamic programming method, the results show that the multi-objective improved genetic method based on coverage decision can increase service efficiency by 14.5%, reduce duplicate coverage by 21.3%, reduce security risk by 13.4% and reduce total cost by 13.2%. The hierarchical mechanism of low-altitude flight service station location based on risk constraints balances the safety risk, service efficiency and location cost of low-altitude flight service station layout.

Key words: risk constraints, low-altitude flight service station, location optimization, coverage decision, multi-objective genetic algorithm (MOGA)

CHEN Huaqun, YANG Weichao. Hierarchy location optimization of low-altitude flight service station based on risk constraints[J]. China Safety Science Journal, 2023, 33(5): 57-65.

Figures/Tables 15

Fig.1

Fig.2

Tab.1

Constraints conditions and evaluation objectives

约束	服务要素	评价目标	权重占比
空域结构	管制服务/交通情报	E类空域	$ρ i U$ $(U = 1,2, 3)$
	管制/交通咨询/情报	F类空域
	飞行情报	G类空域
飞行种类	农/林/气象/测/油	作业类	$ρ i Q$ $(Q = 1,2, 3,4)$
	飞行培训/体育训练	飞行训练
	公务/调机/检验	其他公务
	专机/应急救援	重要飞行
决策准则	军/民/社会活动	安全性	$ρ j V$ $(V = 1,2, 3)$
	中心/服务站/用户	经济性
	供需弹性/不确定性	鲁棒性
优化目标	服务响应/协助应急	响应时间	$ρ j F$ $(F = 1,2, 3,4)$
	建设/运营/维护成本	服务成本
	信号中断/用户干扰	期望风险
	服务覆盖面积	服务覆盖

Tab.1

Fig.4

Fig.5

Fig.6

Tab.2

Tab.3

候选S_j	$C j 1$	$C j 2$	$C j 3$	$C j 4$	首年费用
S₁	436.5	299.5	188.1	83.2	1 070.8
S₂	402.8	270.3	169.8	74.3	950.9
S₃	320.3	249.4	156.7	68.6	877.5
S₄	398.9	220.8	138.7	58.9	738.6
S₅	316.2	247.0	155.2	67.9	869.0
S₆	329.5	209.3	131.5	56.5	713.5
S₇	385.7	230.4	144.8	61.2	765.9
S₈	392.1	242.7	152.5	66.4	847.3
S₉	313.6	243.6	153.0	66.9	855.6
S₁₀	306.3	206.8	129.9	55.8	706.2
S₁₁	357.8	203.5	127.9	54.8	692.5
S₁₂	482.2	221.5	139.2	60.9	779.5
S₁₃	383.5	291.2	183.0	80.7	1 037.0
S₁₄	343.9	249.0	156.4	67.5	856.4
S₁₅	317.2	223.9	140.7	60.7	769.2
S₁₆	336.5	214.2	134.6	57.5	723.4
S₁₇	312.6	218.5	137.3	59.3	751.5
S₁₈	300	204.4	128.4	55.3	700.8
S₁₉	324.6	200.5	126.0	53.9	680.4
S₂₀	318.2	217.1	136.4	58.4	736.5
S₂₁	375.9	216.4	135.9	57.9	728.5
S₂₂	436.5	234.2	147.1	64.3	821.5

Tab.3

Tab.4

Value of parameters

参数	取值	参数	取值
M	31	$ρ i u$	0.1/0.42/0.48
N	22	$ρ i q$	0.07/0.89/0.03/0.01
β	2 380万	$ρ j v$	0.75/0.15/0.10
$β'$	800万	$ρ j f$	0.2/0.5/0.15/0.15
γ	11 s	φ	30 %
γ'	6 s	σ	0~0.5
r₁	200 km	r₂	150 km
r₃	100 km	ρ_d	3.33 %

Tab.4

Fig.9

Fig.10

Fig.11

Fig.12

Fig.13

Tab.5

References 17

[1]	FEDERAL A. Reduction of remote communications outlets used by flight service stations in the conterminous united states[J]. Federal Register / Find, 2017, 82(8):41304-41 306.
[2]	FEDERAL A. Flight service station operators market: benchmarks & performance review-profiles of 18 emerging operators[J]. M2 Presswire, 2016, 70(5):2031-2036.
[3]	张翔. 低空飞行服务系统助力路空协同立体交通体系建设[J]. 交通建设与管理, 2020(3):100-101.
[4]	黄涛, 金姜韬. 通航区域飞行服务中心的功能与应用研究[C]. 2019世界交通运输大会论文集(上), 2019:1363-1373.
	HUANG Tao,JIN Jiangtao. Research on funetion and application of navigation service center in navigation area[C]. Proceedings of the 2019 World Transportation Conference (Part I), 2019:1363-1 373.
[5]	方勇, 朱丹彤, 武文杰, 等. 基于ARENA的通航飞行服务流程仿真与优化[J]. 系统管理学报, 2018, 27(6):1205-1211.
	FANG Yong, ZHU Dantong, WU Wenjie, et al. Simulation and optimization of general aviation flight service process based on arena[J]. Journal of System Management, 2018, 27 (6): 1205-1211.
[6]	文昌辞, 徐国艳, 曹亚聪. 低空飞行服务系统软件需求分析[C]. 第一届空中交通管理系统技术学术年会论文集, 2018:189-192.
	WEN Changci, XU Guoyan, CAO Yacong. Software requirement analysis of low flight service system[C]. Proceedings of the First Annual Conference on Air Traffic Management System Technology, 2018:189-192.
[7]	王晓亮, 马宇超, 王鹏, 等. 通航飞行计划申请受理系统的设计与实现[J]. 计算机工程与设计, 2015, 36(10):2838-2842,2 848.
	WANG Xiaoliang, MA Yuchao, WANG Peng. et al. Design and implementation of flight plan acceptance system for general aviation[J]. Computer Engineering and Design, 2015, 36(10):2838-2 842,2 848.
[8]	SALDANHA-DA-GAMA F. Facility location in logistics and transportation: an enduring relationship[J]. Transportation Research Part E, 2022, 166(10):1069-1073.
[9]	MIAO Runjie, Yuan Jinjiang. A note on LP-based approximation algorithms for capacitated facility location problem[J]. Theoretical Computer Science, 2022, 932(6):31-40. doi: 10.1016/j.tcs.2022.08.002
[10]	MALIKI F, SOUIER M, DAHANE M, et al. A multi-objective optimization model for a multi-period mobile facility location problem with environmental and disruption considerations[J]. Annals of Operations Research, 2022, 316 (9):21-26.
[11]	霍非舟, 董格力, 李墨潇, 等. 考虑需求等级与距离损失联动消防站选址研究[J]. 中国安全科学学报, 2022, 32(3):183-193. doi: 10.16265/j.cnki.issn1003-3033.2022.03.025
	HUO Feizhou, DONG Geli, LI Moxiao, et al. Study on location selection of linkage fire stations based on demand level and distance loss[J]. China Safety Science Journal, 2022, 32(3):183-193. doi: 10.16265/j.cnki.issn1003-3033.2022.03.025
[12]	胡立伟, 何越人, 佘天毅, 等. 高速公路应急救援中心选址优化模型[J]. 中国安全科学学报, 2019, 29(5):145-150. doi: 10.16265/j.cnki.issn1003-3033.2019.05.024
	HU Liwei, HE Yueren, SHE Tianyi, et al., Research on optimization model of expressway emergency rescue center location[J]. China Safety Science Journal, 2019, 29(5):145-150. doi: 10.16265/j.cnki.issn1003-3033.2019.05.024
[13]	ZAMANI S, ARKAT J, NIAKI S. Service interruption and customer withdrawal in the congested facility location problem[J]. Transportation Research Part E, 2022, 165(9):2866-2873.
[14]	陈华群, 熊静, 黄炬凯. 基于多目标规划的低空飞行服务站选址[J]. 科学技术与工程, 2021, 21(11):4717-4723.
	CHEN Huaqun, XIONG Jing, HUANG Jukai. Location of low altitude flight service station based on multi-objective programming[J]. Science Technology and Engineering, 2021, 21(11):4717-4723.
[15]	ROY A. Solution of cluster traveling salesman problem using heuristic based genetic algorithm with risk constraint[J]. International Journal of Innovative Technology and Exploring Engineering, 2019, 9(2):2523-2526.
[16]	ZHENG Yuqiao, ZHANG Lu, DONG Fugang, et al. Multi-objective structural optimization of wind turbine tower using nondominated sorting genetic algorithm[J]. Journal of Beijing Institute of Technology, 2020, 29(3):417-424. doi: 10.15918/j.jbit1004-0579.20050
[17]	SEDDAOUI A, SAAJ C M. Collision-free optimal trajectory generation for a space robot using genetic algorithm[J]. Acta Astronautica, 2022, 316(9):311-321.

需求	本场区域/架次	通道1/ 架次	通道2/ 架次	通道3/ 架次	ρ₂/ %	D
w₂	9946	22	220	125	3.6	1/2
w₄	8911	20	192	107	3.5	1/2
w₆	8691	29	142	114	3.2	1/2
w₂₁	6705	15	122	103	3.0	1/2
w₁₀	4283	1	82	51	3.4	1/2
w₂₀	8996	20	132	154	3.0	1/2
w₁₂	8136	18	127	102	3.4	1/2
w₁₈	9042	19	140	116	2.9	1/2
w₁₄	6886	6	165	100	3.3	1/2
w₂₄	9389	23	153	169	3.5	1/2
w₂₂	10726	21	220	131	3.1	1/2
w₃₃	9675	10	153	143	3.3	1/2
w₂₇	3202	1	76	34	3.6	1/2
w₁₇	6708	11	151	86	3.8	1/2
w₃₇	2011	5	48	24	3.7	1/2

序号	需求分配(w_i,s_j)	动态规划	改进MOGA
序号	风险R(s_j,x_i)	动态规划	改进MOGA
1	G₀=(Ω⁰,S⁰)	w₉,w₁₀,w₁₁,w₁₂,w₁₈,w₂₀
1	R⁰	0.64	0.30
2	S₃	w₁,w₂	w₁,w₃
2	R³	0.48	0.27
3	S₁₆	w₃₁,w₂₂	w₂₂,w_29,w₃₁
3	R¹⁶	0.47	0.20
4	S₁₄	w₂₅,w₂₇
4	R³	0.49	0.11
5	S₁₇	w₃₃,w₃₅
5	R¹⁷	0.45	0.10
6	S₁₁	w₁₈,w₃₃	w₁₉,w₃₃
6	R¹¹	0.44	0.09
7	S₂₀	w₂₄,w₃₇
7	R²⁰	0.42	0.14
8	S₉	w₁₃,w₁₄
8	R⁹	0.53	0.24
9	S₂₁	无	w₇,w_6,w_21,w₈
9	R²¹	无	0.21
10	S₁₀	无	w₁₅,w_16,w₁₇
10	R¹⁰	无	0.08
11	T(N)/s	58	36
12	Z₁/s	108.74	105.04
13	Z₂/万元	12 815.8	11 125.4
14	Z₃/km²	525 327	482 927
15	Z₄/%	31.9	18.5
16	ε	1.25	1.09