Journal of Jilin University(Engineering and Technology Edition) ›› 2026, Vol. 56 ›› Issue (3): 711-724.doi: 10.13229/j.cnki.jdxbgxb.20240908

Previous Articles    

Multi⁃objective optimization model for bus transfer station layouts around metro stations

Guo-zhu CHENG1(),Yan-feng LYU1,Tian-jun FENG2()   

  1. 1.School of Civil Engineering & Transportation，Northeast Forestry University，Harbin 150040，China
    2.School of Transportation Science & Engineering，Jilin University of Architecture，Changchun 130118，China
  • Received:2024-08-17 Online:2026-03-01 Published:2026-03-31
  • Contact: Tian-jun FENG E-mail:guozhucheng@126.com;fengtianjun@ jlju.edu.cn

RICH HTML

 0   

PDF (PC)

30

Abstract:

To enhance the efficiency of public transit transfers， a multi-objective collaborative optimization study on the layout of regular bus transfer stations around subway stations was conducted.A multi-objective collaborative optimization model considering three main objectives：passenger transfer convenience，travel time cost，and bus station load balance，was constructed.A solution method based on the social spider optimization algorithm was provided，and dynamic learning rate adjustment methods and Pareto optimal solution sets were introduced to optimize the algorithm.The case analysis results show that after optimization，the average shortest path is reduced by 28.98%，the average shortest path time is reduced by 34.22%，and the average station load balance is improved by 6.5%，indicating that the model has a good optimization effect on station layout.

Key words: urban traffic, metro stations, bus transfer station layout, multi-objective collaborative optimization, social spider optimization algorithm（SSOA）

CLC Number: 

  • U491

Fig.1

Calculation process of social spider optimization algorithm（SSOA）"

Fig.2

Case site location relationships"

Fig.3

Daily segmented inflow and outflow passenger flow at subway transfer station A in may 2023"

Fig.4

Daily segmented inflow and outflow passenger flow at bus stops around subway transfer station A in may 2023"

Table 1

Peak hours and card swiping numbers of bus stops around subway transfer station A"

公交站点刷卡高峰时段高峰时段刷卡数/（人次·h-1）
B18~9214
B216~171 695
B37~8648
B47~8964
B517~18184
B616~171 797
B77~81 400
B816~17916
B97~8546

Table2

Peak hours and maximum passenger flow of entry and exit at subway transfer station A"

时间进站高峰时段进站最大客流/（人次·h-1）出站高峰时段出站最大客流/（人次·h-1）
工作日16~171 4827~82 397
非工作日16~171 3467~82 301

Fig.5

Passenger flow distribution at bus stops around subway transfer station A"

Fig.6

Optimized bus stop locations"

Table 3

Shortest paths of each target node before and after optimization"

公交站点优化前最短路径/m优化后最短路径/m最短路径缩小比例/%
B12622398.70
B227520724.83
B335827822.40
B436220842.65
B5120143-18.78
B636518649.12
B736221141.62
B822012941.22
B930815749.05

Table 4

Shortest path times of each target node before and after optimization"

目标节点优化前最短路径时间/min优化后最短路径时间/min最短路径时间缩小比例/%
B15.194.856.49
B212.848.6232.82
B38.436.0827.92
B421.327.6963.93
B52.432.62-7.86
B69.184.0755.73
B711.885.9150.23
B84.613.4724.83
B96.733.1053.88

Table 5

Standard deviation and coefficient of variation of bus stop load before and after optimization"

时间

初始

标准差

初始

变异系数

优化后

标准差

优化后

变异系数

早高峰23.880.5222.240.49
晚高峰31.300.6624.370.51

Table 6

Shortest paths of each target node before and after optimization"

公交站点早高峰晚高峰
初始负荷/人

优化后

负荷/人

初始负荷/人

优化后

负荷/人

B11830916
B273698877
B344474042
B452553139
B59101521
B674719382
B772706060
B837336865
B943432628

Fig.7

Distribution of bus stop loads"

Fig.8

Comparison of bus stop location optimization by different algorithms"

Fig.9

Comparison of convergence curves of different algorithms"

[1] Codina E, Marin A, Lopez F.A model for setting services on auxiliary bus lines under congestion[J].TOP,2013,21(1):48-83.
[2] 方晓丽.城市轨道交通接驳公交线路布设及优化方法研究[D].成都: 西南交通大学交通运输与物流学院, 2013.
Fang Xiao-li.Research on the layout and optimization method of urban rail transit connection bus lines[D].Chengdu: School of Transportation and Logistics, Southwest Jiaotong University, 2013.
[3] 宋川. 轨道交通与常规公交衔接协调优化研究[D].西安: 长安大学汽车学院, 2015.
Song Chuan.Research on coordination optimization of rail transit and conventional bus connection[D].Xi'an: School of Automobile, Chang'an University, 2015.
[4] 李雨恒. 高峰期地铁客流网络协调控制研究[D]. 广州: 华南理工大学土木与交通学院, 2021.
Li Yu-heng.Research on coordinated control of subway passenger flow network during peak hours[D].Guangzhou: School of Civil Engineering and Transportation, South China University of Technology,2021.
[5] Gong C, Mao B, Wang M, et al.Equity-oriented train timetabling with collaborative passenger flow control:a spatial rebalance of service on an oversaturated urban rail transit line[J].Journal of Advanced Transportation,2020,2020: 1-17.
[6] 李佳杰, 柏赟, 周雨鹤, 等. 基于站外限流与时刻表调整的地铁换乘站大客流协同控制[J]. 铁道学报,2020, 42(5): 9-18.
Li Jia-jie, Bai Yun, Zhou Yu-he,et al.Coordinated control of large passenger flows at metro transfer stations based on external flow limitation and timetable adjustment[J]. Journal of the China Railway Society, 2020, 42(5): 9-18.
[7] Lovett A, Munden G, Saat M R,et al.High-speed rail network design and station location:model and sensitivity analysis[J].Transportation Research Record, 2013, 2374(1): 1-8.
[8] 苏瑞晔. 基于时空可达性的区域城际铁路线网规划方法研究[D]. 北京: 北京交通大学交通运输学院, 2017.
Su Rui-ye.Research on regional intercity railway network planning method based on spatio-temporal accessibility[D].Beijing:School of Traffic and Transportation, Beijing Jiaotong University, 2017.
[9] 马威. 基于规划紧迫度的京津冀城市群城际铁路网规划研究[D]. 石家庄: 石家庄铁道大学交通运输学院, 2020.
Ma Wei.Research on intercity railway network planning of beijing-tianjin-hebei urban agglomeration based on planning urgency[D].Shijiazhuang: School of Traffic and Transportation, Shijiazhuang Tiedao University, 2020.
[10] Kuan S N, Ong H L, Ng K M. Solving the feeder bus network design problem by genetic algorithms and ant colony optimization[J]. Advances in Engineering Software, 2005, 37(6): 351-359.
[11] Chew C H. Integrated bus/rail station[J].Applied Acoustics, 1999, 56(1): 57-66.
[12] Wang Chao, Ye Zhi-rui, Wang Wei. A multi-objective optimization and hybrid heuristic approach for urban bus route network design[J]. IEEE Access, 2020, 8: 12154-12167.
[13] Deng Lian-bo, He Yuan, Zeng Ning-xin, et al.Optimal design of feeder-bus network with split delivery[J].Journal of Transportation Engineering,Part A-Systems, 2020,146(3): No.4019078.
[14] 孙健, 宋茂星, 邱果, 等. 基于电动汽车大数据的多等级充电站选址与服务能力研究[J]. 中国公路学报, 2024, 37(4): 48-60.
Sun Jian, Song Mao-xing, Qiu Guo, et al. Research on site selection and service capacity of multi-level charging stations based on electric vehicle big data[J]. China Journal of Highway and Transport, 2024, 37(4): 48-60.
[15] Sun D, Ding X.Spatiotemporal evolution of ridesourcing markets under the new restriction policy:a case study in Shanghai[J].Transportation Research Part A: Policy and Practice, 2019, 130, 227-239.
[16] 刘倩, 李静, 路庆昌, 等. 考虑轨道交通换乘需求的公交发车时刻优化模型[J]. 小型微型计算机系统, 2022, 43(2): 430-437.
Liu Qian, Li Jing, Lu Qing-chang, et al.Bus departure time optimization model considering rail transit transfer demand[J].Mini-Micro Systems, 2022, 43(2): 430-437.
[17] 丁昱杰, 张凯, 张龄允, 等. 基于遗传灰狼算法的员工通勤合乘路径优化[J].现代信息科技, 2023, 7(2): 112-115.
Ding Yu-jie, Zhang Kai, Zhang Ling-yun, et al.Employee commute carpooling route optimization based on genetic grey wolf algorithm[J].Modern Information Technology,2023, 7(2): 112-115.
[18] 潘寒川, 戚博洋, 胡华, 等. 考虑司机偏好的城市轨道交通混合乘务轮转模型[J].交通运输系统工程与信息,2023, 23(5): 258-267.
Pan Han-chuan, Qi Bo-yang, Hu Hua,et al.Urban rail transit hybrid crew scheduling model considering driver preferences[J].Journal of Transportation Systems Engineering and Information Technology, 2023, 23(5): 258-267.
[19] 余欣鹏, 余子扬, 崔歡鑫, 等. 基于优化算法的新能源汽车充电站选址研究[J]. 汽车测试报告, 2024(6): 71-73.
Yu Xin-peng, Yu Zi-yang, Cui Huan-xin,et al.Research on charging station location for new energy vehicles based on optimization algorithm[J]. Auto Testing Report, 2024(6): 71-73.
[20] Cuevas E, Cienfuegos M, Zaldívar D,et al. A swarm optimization algorithm inspired in the behavior of the social-spider[J]. Expert Systems with Applications,2013, 40(16): 6374-6384.
[21] 王松波. 考虑帕累托最优解的多目标优化进化算法[J].数学的实践与认识, 2022, 52(9): 132-146.
Wang Song-bo.Multi-objective optimization evolutionary algorithm considering pareto optimal solutions[J]. Mathematics in Practice and Theory, 2022, 52(9):132-146.
[22] 王敏, 毛保华, 杨彦强, 等. 虑均衡性的城市轨道交通线路负荷水平评估研究[J].交通运输系统工程与信息, 2021, 21(2): 98-104, 118.
Wang Min, Mao Bao-hua, Yang Yan-qiang, et al.Research on the load level assessment of urban rail transit lines considering balance[J].Journal of Transportation Systems Engineering and Information Technology, 2021, 21(2): 98-104, 118.
[23] 舒文, 汤银英, 胡广红. 考虑碳排放的车流径路与列车编组计划综合优化[J].铁道运输与经济, 2025, 47(2):1-12.
Shu Wen, Tang Yin-ying, Hu Guang-hong. Integrated optimization of traffic routing and train formation plan considering carbon emissions[J].Railway Transport and Economy, 2025, 47(2): 1-12.
[24] 黄君泽, 吴文渊, 李轶,等.面向动态公交的离散分层记忆粒子群优化算法[J].计算机工程, 2024, 50(4): 20-30.
Huang Jun-ze, Wu Wen-yuan, Li Yi,et al.Discrete layered memory particle swarm optimization algorithm for dynamic bus systems[J].Computer Engineering, 2024, 50(4): 20-30.
[25] 杭佳宇, 王嘉文, 葛淼彦.基于模拟退火算法的事件影响交叉口可靠性优化方法[J].常州大学学报: 自然科学版, 2023, 35(5): 83-92.
Hang Jia-yu, Wang Jia-wen, Ge Miao-yan.Reliability optimization method for intersection impacted by events based on simulated annealing algorithm[J].Journal of Changzhou University(Natural Science Edition), 2023, 35(5): 83-92.
[1] Yuan-wen LAI,Yan-sheng CHEN,Shu-yi WANG,Yu-long ZHANG,Xin-yun ZHU. Bus schedule optimization considering bus and metro interchange needs [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(6): 2030-2037.
[2] Cheng-dong ZHOU,Fei SONG,Xiao-mei ZHAO,Jun-jie YAO. Congestion pricing model in multi-modal network based on doubly dynamical evolution [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(4): 1319-1327.
[3] Yao SUN,Bao-zhen YAO,Zi-jian BAI. Evaluate the validity of traffic congestion dispersion based on random forest method [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(2): 512-519.
[4] Guang-yue NIAN,Hai-xiao PAN,Jian SUN. Exploring relationship between urban built environment and road traffic performance [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(1): 141-149.
[5] Chun-jiao DONG,Yu-xiao LU,She-qiang MA,Peng-hui LI. Identification of E⁃bike violation behaviors by considering waiting tolerance time [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(9): 2540-2546.
[6] Xiao-yue WEN,Guo-min QIAN,Hua-hua KONG,Yue-jie MIU,Dian-hai WANG. TrafficPro： a framework to predict link speeds on signalized urban traffic network [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(8): 2214-2222.
[7] Shu-hong MA,Guo-mei LIAO,Yan HUANG,Jun-jie ZHANG. Heterogeneity of built environment on commuter passenger flow of subway in traffic analysis zones [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(7): 1913-1922.
[8] Zhi-hua XIONG,Dai-yue DONG,Chun-jiao DONG,Yan ZHENG,Chao XIE. Combined decision-choice behavior of spectators considering personal preferences [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(4): 979-986.
[9] Jiao-rong WU,Qing-kai LIN,Yong-qi DENG. Identification method of potential public transportation lane demand based on bus line operation stability [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(3): 692-699.
[10] Wen-hui ZHANG,Jing YI. Optimization of bus stop system considering capacity and queuing delays [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(1): 146-154.
[11] Xian-yan KUANG,Zi-ru CHEN. Dynamic game comity behavior at pedestrians′ crossing on unsignal-controlled roads based on cellular automata [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(4): 837-846.
[12] Hong-fei JIA,Zi-han SHAO,Li-li YANG. Ride⁃sharing matching model and algorithm of online car⁃hailing under condition of uncertain destination [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(3): 564-571.
[13] Chun-jiao DONG,Dai-yue DONG,Cheng-xiang ZHU-GE,Li ZHEN. Trip characteristics and decision⁃making behaviors modeling of electric bicycles riding [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(11): 2618-2625.
[14] Shi-jun YANG,Yu-long PEI,Heng-yan PAN,Guo-zhu CHENG,Wen-hui ZHANG. Characteristics analysising and prediction of dwelling time of urban bus [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(6): 2031-2039.
[15] Lei CHEN,Jiang⁃feng WANG,Yuan⁃li GU,Xue⁃dong YAN. Multi⁃source traffic data fusion algorithm based onmind evolutionary algorithm optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 705-713.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd