WANG Zheng-wu, CHEN Tao, SONG Ming-qun. Coordinated optimization of operation routes and schedules for responsive feeder transit under simultaneous pick-up and delivery mode[J]. Journal of Traffic and Transportation Engineering, 2019, 19(5): 139-149. doi: 10.19818/j.cnki.1671-1637.2019.05.014
Citation: WANG Zheng-wu, CHEN Tao, SONG Ming-qun. Coordinated optimization of operation routes and schedules for responsive feeder transit under simultaneous pick-up and delivery mode[J]. Journal of Traffic and Transportation Engineering, 2019, 19(5): 139-149. doi: 10.19818/j.cnki.1671-1637.2019.05.014

Coordinated optimization of operation routes and schedules for responsive feeder transit under simultaneous pick-up and delivery mode

doi: 10.19818/j.cnki.1671-1637.2019.05.014
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  • Author Bio:

    WANG Zheng-wu(1973-), male, professor, PhD, zhengwu.wang@csust.edu.cn

  • Received Date: 2019-04-14
  • Publish Date: 2019-10-25
  • The coordinated optimization problem of operation routes and vehicle schedules for responsive feeder transit under the simultaneous pick-up and delivery mode was studied. The vehicle route representation method based on passengers rather than demand points was devised by considering the personalization of passenger travel time window. The objective function that represents system benefit was constructed by combining the costs of vehicle departure and travel, penalty costs of vehicle early and late arrival, and ticket fares. The vehicle capacity, passenger time window, vehicle running time, vehicle holding quantity and departure time were all taken as constraints, and the integrated optimization model of departure interval, vehicle type and running route was constructed. The double genetic algorithm was designed to solve the integrated optimization model. In this algorithm, the chromosome was coded by multi-chain coding structure, and the chromosome chiasma included two ways of inter-individual and intra-individual. In order to validate the superiority of the simultaneous pick-up and delivery mode, and the effectiveness of the integrated optimization model and the algorithm, several examples were designed to compare the calculation results of the simultaneous pick-up and delivery mode and the separate pick-up and deliver mode. The effects of vehicle speed, single trip running time limit and vehicle composition on the operation efficiency of responsive feeder transit were analyzed. Calculation result shows that under the same passenger demand, compared with the separate pick-up and deliver mode, under the simultaneous pick-up and delivery mode, the departure times reduce by 1, the number of required vehicles reduce by 2, the average seat utilization rate increases by 8.3%, the average vehicle distance required to transport unit passenger reduces by 11.0%, and the operation cost reduces by 15.9%. Therefore, the simultaneous pick-up and delivery mode can effectively improve the operation efficiency. At the same time, under the simultaneous pick-up and delivery mode, when vehicle speed, single trip running time limit, and small vehicle ratio fluctuate by 15.0%, 15.0%, and 12.5% near the reference values, respectively, the maximum change rate of the departure times, the average seat utilization rate, and the objective value reach 20.0%, 15.7%, and 27.1%, respectively, therefore, these parameters have a significant impact on the system operating efficiency.

     

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  • [1]
    潘述亮, 俞洁, 卢小林, 等. 灵活型公交服务系统及其研究进展综述[J]. 城市交通, 2014, 12(2): 62-68, 58. doi: 10.3969/j.issn.1672-5328.2014.02.009

    PAN Shu-liang, YU Jie, LU Xiao-lin, et al. A review of flexible transit service[J]. Urban Transport of China, 2014, 12(2): 62-68, 58. (in Chinese). doi: 10.3969/j.issn.1672-5328.2014.02.009
    [2]
    CHANDRA S, QUADRIFOGLIO L. A new street connectivity indicator to predict performance for feeder transit services[J]. Transportation Research Part C: Emerging Technologies, 2013, 30: 67-80. doi: 10.1016/j.trc.2013.02.004
    [3]
    LI Xiu-gang, QUADRIFOGLIO L. Feeder transit services: choosing between fixed and demand responsive policy[J]. Transportation Research Part C: Emerging Technologies, 2010, 18(5): 770-780. doi: 10.1016/j.trc.2009.05.015
    [4]
    QUADRIFOGLIO L, LI Xiu-gang. A methodology to derive the critical demand density for designing and operating feeder transit services[J]. Transportation Research Part B: Methodological, 2009, 43(10): 922-935. doi: 10.1016/j.trb.2009.04.003
    [5]
    QUADRIFOGLIO L, DDESSOUKY M M, ORDÓÑEZ F. Asimulation study of demand responsive transit system design[J]. Transportation Research Part A: Policy and Practice, 2008, 42(4): 718-737. doi: 10.1016/j.tra.2008.01.018
    [6]
    EDWARDS D, WATKINS K. Comparing fixed-route and demand responsive feeder transit systems in real-world settings[J]. Transportation Research Record, 2013(2352): 128-135.
    [7]
    LI Xiu-gang, QUADRIFOGLIO L. Optimal zone design for feeder transit services[J]. Transportation Research Record, 2009(2111): 100-108.
    [8]
    苗一迪. 柔性路径公交车服务区域的决策模型研究[D]. 大连: 大连理工大学, 2011.

    MIAO Yi-di. A decision-making model for determining the service area of a flexible-route bus[D]. Dalian: Dalian University of Technology, 2011. (in Chinese).
    [9]
    芒烈. 面向轨道交通站点的需求响应型接驳公交系统调度方法[D]. 长春: 吉林大学, 2017.

    MANG Lie. Scheduling method of railway transit station oriented demand responsive connector system[D]. Changchun: Jilin University, 2017. (in Chinese).
    [10]
    PAN Shu-liang, YU Jie, YANG Xian-feng, et al. Designing a flexible feeder transit system serving irregular shaped and gated communities: service area and feeder route planning[J]. Journal of Urban Planning and Development, 2015, 141(3): 04014028-1-9.
    [11]
    范文豪. 需求响应式接驳公交路径优化模型研究[D]. 南京: 东南大学, 2017.

    FAN Wen-hao. Research on routing optimization model of demand-responsive connector[D]. Nanjing: Southeast University, 2017. (in Chinese).
    [12]
    熊杰, 关伟, 黄爱玲. 社区公交接驳地铁路径优化研究[J]. 交通运输系统工程与信息, 2014, 14(1): 166-173. doi: 10.3969/j.issn.1009-6744.2014.01.026

    XIONG Jie, GUAN Wei, HUANG Ai-ling. Research on optimal routing of community shuttle connect rail transit line[J]. Journal of Transportation Systems Engineering and Information Technology, 2014, 14(1): 166-173. (in Chinese). doi: 10.3969/j.issn.1009-6744.2014.01.026
    [13]
    YU Yao, MACHEMEHL R B, XIE Chi. Demand-responsive transit circulator service network design[J]. Transportation Research Part E: Logistics and Transportation Review, 2015, 76: 160-175. doi: 10.1016/j.tre.2015.02.009
    [14]
    DESSOUKY M, RAHIMI M, WEIDNER M. Jointly optimizing cost, service, and environmental performance in demandresponsive transit scheduling[J]. Transportation Research Part D: Transport and Environment, 2003, 8(6): 433-465. doi: 10.1016/S1361-9209(03)00043-9
    [15]
    NOURBAKHSH S M, OUYANG Yan-feng. A structured flexible transit system for low demand areas[J]. Transportation Research Part B: Methodological, 2012, 46(1): 204-216. doi: 10.1016/j.trb.2011.07.014
    [16]
    NÚNEZ A, CORTÉSC E, SÁEZ D, et al. Multiobjective model predictive control for dynamic pickup and delivery problems[J]. Control Engineering Practice, 2014, 32: 73-86. doi: 10.1016/j.conengprac.2014.07.004
    [17]
    KIRCHLER D, CALVO R W. A granular tabu search algorithm for the dial-a-ride problem[J]. Transportation Research Part B: Methodological, 2013, 56: 120-135. doi: 10.1016/j.trb.2013.07.014
    [18]
    SCHILDE M, DOERNER K F, HARTL R F. Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem[J]. European Journal of Operational Research, 2014, 238(1): 18-30. doi: 10.1016/j.ejor.2014.03.005
    [19]
    潘述亮, 俞洁, 邹难, 等. 含特殊需求的灵活接驳公交服务区域与路径选择[J]. 东北大学学报(自然科学版), 2014, 35(11): 1650-1654. doi: 10.3969/j.issn.1005-3026.2014.11.029

    PAN Shu-liang, YU Jie, ZOU Nan, et al. Service area and route selection choice model for flexible feeder transit with special demands[J]. Journal of Northeastern University(Natural Science), 2014, 35(11): 1650-1654. (in Chinese). doi: 10.3969/j.issn.1005-3026.2014.11.029
    [20]
    SHEU J B. A fuzzy clustering approach to real-time demandresponsive bus dispatching control[J]. Fuzzy Sets and Systems, 2005, 150(3): 437-455. doi: 10.1016/j.fss.2004.05.006
    [21]
    邱丰, 李文权, 沈金星. 可变线路式公交的两阶段车辆调度模型[J]. 东南大学学报(自然科学版), 2014, 44(5): 1078-1084. https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX201405036.htm

    QIU Feng, LI Wen-quan, SHEN Jin-xing. Two-stage model for flex-route transit scheduling[J]. Journal of Southeast University(Natural Science Edition), 2014, 44(5): 1078-1084. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX201405036.htm
    [22]
    高煦明. 固定站点需求响应式接驳公交调度模型研究[D]. 南京: 东南大学, 2015.

    GAO Xu-ming. Resaerch on dispatching system of demandresponsive connector with on-demand stations[D]. Nanjing: Southeast University, 2015. (in Chinese).
    [23]
    赵伟忠. 随机用户需求下实时定制公交线路生成模型研究[D]. 西安: 长安大学, 2017.

    ZHAO Wei-zhong. The research on route generation model of real-time custom bus based on random user's demand[D]. Xi'an: Chang'an University, 2017. (in Chinese).
    [24]
    陈坚, 李武, 吴丹, 等. 基于MAST的智慧公交系统调度优化模型[J]. 重庆交通大学学报(自然科学版), 2016, 35(5): 140-145. https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201605027.htm

    CHEN Jian, LI Wu, WU Dan, et al. Scheduling optimization model of intelligent public transport system based on MAST[J]. Journal of Chongqing Jiaotong University(Natural Science), 2016, 35(5): 140-145. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201605027.htm
    [25]
    GHANNADPOUR S F, NOORI S, TAVAKKOLI-MOGHADDAM R, et al. A multi-objective dynamic vehicle routing problem with fuzzy time windows: model, solution and application[J]. Applied Soft Computing Journal, 2014, 14(Part C): 504-527.
    [26]
    易星. 基于用户需求的城市公交调度算法研究[J]. 智能计算机与应用, 2018, 8(4): 129-131, 135. doi: 10.3969/j.issn.2095-2163.2018.04.027

    YI Xing. Research on urban public transport scheduling algorithm based on user needs[J]. Intelligent Computer and Applications, 2018, 8(4): 129-131, 135. (in Chinese). doi: 10.3969/j.issn.2095-2163.2018.04.027
    [27]
    张鹏浩. 接驳高铁站的区域灵活型公交调度模型研究[D]. 北京: 北京交通大学, 2018.

    ZHANG Peng-hao. Research on scheduling model of regional flexible feeder bus for high-speed railway stations[D]. Beijing: Beijing Jiaotong University, 2018. (in Chinese).
    [28]
    王正武, 易童翔, 高志波. 响应型接驳公交运行路径与车辆调度的协调优化[J]. 交通科学与工程, 2018, 34(1): 68-73. https://www.cnki.com.cn/Article/CJFDTOTAL-CSJX201801012.htm

    WANG Zheng-wu, YI Tong-xiang, GAO Zhi-bo. Coordinated optimization of running route and vehicle scheduling for responsive feeder transit[J]. Journal of Transport Science and Engineering, 2018, 34(1): 68-73. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CSJX201801012.htm
    [29]
    王正武, 袁媛, 高志波. 高自由度响应公交分区路径与调度的协调优化[J]. 长沙理工大学学报(自然科学版), 2018, 15(1): 41-48. https://www.cnki.com.cn/Article/CJFDTOTAL-HNQG201801007.htm

    WANG Zheng-wu, YUAN Yuan, GAO Zhi-bo. Coordination optimization for partition path and scheduling with high degree of freedom demand response transit[J]. Journal of Changsha University of Science and Technology(Natural Science), 2018, 15(1): 41-48. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HNQG201801007.htm
    [30]
    王正武, 刘安琪, 谭康康. 考虑乘客需求特性的DRC公交运行周期优化[J]. 长沙理工大学学报(自然科学版), 2016, 13(2): 19-25. https://www.cnki.com.cn/Article/CJFDTOTAL-HNQG201602005.htm

    WANG Zheng-wu, LIU An-qi, TAN Kang-kang. DRC bus operation cycle optimization corresponding to passenger demand characters[J]. Journal of Changsha University of Science and Technology(Natural Science), 2016, 13(2): 19-25. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HNQG201602005.htm
    [31]
    DENG Lian-bo, GAO Wei, ZHOU Wen-liang, et al. Optimal design of feeder-bus network related to urban rail line based on transfer system[J]. Procedia-Social and Behavioral Sciences, 2013, 96: 2383-2394.
    [32]
    陈呈频, 韩胜军, 鲁建厦, 等. 多车场与多车型车辆路径问题的多染色体遗传算法[J]. 中国机械工程, 2018, 29(2): 218-223. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGJX201802014.htm

    CHEN Cheng-pin, HAN Sheng-jun, LU Jian-sha, et al. A multi-chromosome genetic algorithm for multi-depot and multi-type vehicle routing problems[J]. China Mechanical Engineering, 2018, 29(2): 218-223. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGJX201802014.htm
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