A Method for Improved Air Luggage Check-in Service Based on Optimized Urban Mobile Stations

HU Xiaobing; ZHANG Xuemei; ZHOU Hang; MA Yiming

doi:10.3963/j.jssn.1674-4861.2022.03.014

Volume 40 Issue 3

Jun. 2022

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Article Navigation > Journal of Transport Information and Safety > 2022 > 40(3): 136-145

HU Xiaobing, ZHANG Xuemei, ZHOU Hang, MA Yiming. A Method for Improved Air Luggage Check-in Service Based on Optimized Urban Mobile Stations[J]. Journal of Transport Information and Safety, 2022, 40(3): 136-145. doi: 10.3963/j.jssn.1674-4861.2022.03.014

Citation:

HU Xiaobing, ZHANG Xuemei, ZHOU Hang, MA Yiming. A Method for Improved Air Luggage Check-in Service Based on Optimized Urban Mobile Stations[J]. Journal of Transport Information and Safety, 2022, 40(3): 136-145. doi: 10.3963/j.jssn.1674-4861.2022.03.014

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A Method for Improved Air Luggage Check-in Service Based on Optimized Urban Mobile Stations

doi: 10.3963/j.jssn.1674-4861.2022.03.014

HU Xiaobing^{1, 2
,},
ZHANG Xuemei^{1, 2},
ZHOU Hang^{1, 3
,
,},
MA Yiming^{1, 3}

1.
Laboratory of Complex System Safety and Intelligent Decisions, Civil Aviation University of China, Tianjin 300300, China
2.
College of Safety Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
3.
College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China

Received Date: 2021-10-21
Available Online: 2022-07-25

Abstract

Abstract

To enhance the quality and competitiveness of air transport service and overcome the limitations of low service coverage, high costs, and complex site selection of traditional air terminals, this paper proposes a novel method for improved air luggage check-in service based on Urban Mobile Stations (UMS). Specifically, the proposed UMS can adapt the check-in locations to the real-time passenger positions, which is formulated as a UMS dynamic siting optimization problem over the road network. The average distance and the maximal acceptable distance from passengers to UMS are considered, incorporating the constraints on the locations of service, time-varying distribution of passengers, and the service capacity of stations. Then, a hybrid optimization algorithm satisfying the requirement of real-time computation is developed, which combines the ripple spreading algorithm (RSA) and the adaptive genetic algorithm (AGA). The RSA is used to solve the many-to-many path optimization problem of passenger and UMS stations, and the AGA is employed to optimize the UMS locations. Case studies based on the road network of Tianjin City and simulated random road networks are used for the comparison between the proposed method and the traditional method. The results show that the average distances from passengers to stations are reduced by 30.9%, the number of scenarios exceeding the maximum acceptable distance is decreased by 43.7%, and the average running time of solving the UMS optimization problem is shortened by 41.2% when using the proposed method. These facts show the advantages of the proposed UMS method, meeting the real-time passengers' demands.
- intelligent transportation,
- city air terminal,
- urban mobile station,
- ripple spreading algorithm,
- adaptive genetic algorithm,
- luggage check-in service

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References

[1]	张亚玲, 龙熙华, 穆学文. 求解最大割问题的分枝定界算法[J]. 西安科技大学学报, 2006(4): 541-544. doi: 10.3969/j.issn.1672-9315.2006.04.025 ZHANG Y L, LONG X H, MU X W. The branch-and-bound algorithm for max-cut problem[J]. Journal of Xi'an University of Science and Technology, 2006(4): 541-544. (in Chinese) doi: 10.3969/j.issn.1672-9315.2006.04.025
[2]	张和君, 张跃. 基于模拟退火算法的布局问题研究[J]. 计算机工程与设计, 2006(11): 1985-1988. doi: 10.3969/j.issn.1000-7024.2006.11.023 ZHANG H J, ZHANG Y. Research on packing problem based on simulated annealing algorithm[J]. Computer Engineering and Design, 2006(11): 1985-1988. (in Chinese) doi: 10.3969/j.issn.1000-7024.2006.11.023
[3]	刘景发, 王大文, 颜学明. 面向动态设施布局的禁忌搜索算法[J]. 华中科技大学学报(自然科学版), 2021, 49(2): 44-50. https://www.cnki.com.cn/Article/CJFDTOTAL-HZLG202102006.htm LIU Y F, WANG D W, YAN X M. Tabu search algorithm for dynamic facility layout problem[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition), 2021, 49(2): 44-50. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HZLG202102006.htm
[4]	陈振, 王伟贤, 李卓群, 等. 基于多因子约束P中值模型的充电桩布局优化研究[J]. 北京交通大学学报, 2021, 45(3): 93-99. https://www.cnki.com.cn/Article/CJFDTOTAL-BFJT202103013.htm CHEN Z, WANG W X, LI Z Q, et al. Study on optimization of charging pile layout based on multi-factor constrained P-median model[J]. Journal of Beijing Jiaotong University, 2021, 45(3): 93-99. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-BFJT202103013.htm
[5]	HAKIMI S L. Optimum distribution of switching centers in a communi cation network and some related graph theoretic problems[J]. Operations Research, 1965, 13(3): 462-475. doi: 10.1287/opre.13.3.462
[6]	MLADENOVIĆ N, BRIMBERG J, HANSEN P, et al. The p-median problem: A survey of metaheuristic approaches[J]. European Journal of Operational Research, 2005, 179(3): 927-939.
[7]	李军, 解超, 王林, 等. 基于轨迹数据的道路客运班车停留站点位置提取方法[J]. 交通信息与安全, 2021, 39(4): 60-67. doi: 10.3963/j.jssn.1674-4861.2021.04.008 LI J, XIE C, WANG L, et al. A method for extracting regular bus parking stops of road passenger transport based on trajectory data[J]. Journal of Transport Information and safety, 2021, 39(4): 60-67. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2021.04.008
[8]	魏明, 陈学武, 孙博. 公交站场选址布局优化模型和算法[J]. 交通运输系统工程与信息, 2015, 15(4): 113-117. doi: 10.3969/j.issn.1009-6744.2015.04.017 WEI M, CHEN X W, Sun B. Model and algorithm for bus parking site layout optimization problem[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(4): 113-117. (in Chinese) doi: 10.3969/j.issn.1009-6744.2015.04.017
[9]	程一一, 郭建华, 蒋欢昕. 基于兴趣点数据的公交站点布局合理度物元分析评价[J]. 交通信息与安全, 2020, 38(6): 63-72. doi: 10.3963/j.jssn.1674-4861.2020.06.009 CHENG Y Y, GUO J H, JIANG H X. An evaluation of bus station layout rationality using matter element analysis based on points of interest data[J]. Journal of Transport Information and safety, 2020, 38(6): 63-72. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2020.06.009
[10]	鲍文仓, 田琼. 基于连续逼近的共享电动汽车站点布局研究[J]. 交通运输系统工程与信息, 2018, 18(增刊1): 21-29. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT2018S1005.htm BAO W C, TIAN Q. Depot location problem of electric vehicle sharing system: A continuum approximation method[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(S1): 21-29. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT2018S1005.htm
[11]	刘嘉文, 代颖, 杨斐, 等. 共享单车停放点联合覆盖选址及车辆配置模型[J]. 工业工程与管理, 2020, 25(1): 127-135. https://www.cnki.com.cn/Article/CJFDTOTAL-GYGC202001015.htm LIU J W, DAI Y, YANG F, et al. A cooperative covering model for location of bike sharing stations and its fleet deployment[J]. Industrial Engineering and Management, 2020, 25(1): 127-135. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GYGC202001015.htm
[12]	ERNST A T, KRISHNAMOORTHY M. Solution algorithms for the capacitated single allocation hub location problem[J]. Annals of perations Research, 1999(86): 141-159.
[13]	GONG D, GEN M, YAMAZAKI G, et al. Hybrid evolutionary method for capacitated location-allocation problem[J]. Computers & Industrial Engineering, 1997, 33(3/4): 577-580.
[14]	BRIMBERG J, HANSEN P, MLADENOVIC N, et al. Improvements and comparison of heuristics for solving the uncapacitated multisource Weber problem[J]. Operations Research. 2000, 48(3): 444-460. doi: 10.1287/opre.48.3.444.12431
[15]	SMED J, HAKONEN H. Algorithms and networking for computer games[M]. Hoboken: Wiley Online Library, 2006.
[16]	SNIEDOVICH M. Dijkstra's algorithm revisited: The dynamic programming connexion[J]. Control and Cybernetics, 2006, 35(3): 599-620.
[17]	HU X B, WANG M, LEESON M S, et al. Deterministic agent-based path optimization method by mimicking the spreading of ripples[J]. Evolutionary Computation, 2016, 24 (2): 319-346.
[18]	胡小兵, 陈树念, 张盈斐, 等. 求解多目标路径优化问题的涟漪扩散算法[J]. 计算机工程与应用, 2021, 57(23): 81-90. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG202123009.htm HU X B, CHEN S N, ZHANG Y F, et al. New ripple-spreading algorithm for multi-objective path optimization[J]. Computer Engineering and Applications, 2021, 57(23): 81-90. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG202123009.htm
[19]	顾鹏程. 基于自适应遗传算法的多目标优化研究[D]. 南京: 南京航空航天大学, 2016. GU P C. Research on multi-objective optimization based on adaptive genetic algorithm[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2016. (in Chinese)
[20]	China Aviation Ground Service Company. Project report of CAT construction in Tianjin[R]. Beijing: China Aviation Ground Service Company, 2013.

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