大连海事大学,交通运输工程学院;
【背景】公交跨线调度因其车辆运营成本低、利用率高等优势,已在国内外城市中开展实施,但在实际应用中仍面临跨线调度范围有限和行程时间波动等挑战,导致调度存在跨线班次少、准点率低等问题。【目标】针对行程时间波动环境下的公交车辆跨线调度问题,通过调整发车时刻表和融合各子场景下的公交行车计划,扩大公交车可跨线班次空间,达到最终行车计划具有跨线班次多、车辆利用率高、用车成本低和准点率高的效果。【方法】提出公交多线协同跨线调度两阶段鲁棒优化模型,引入时间控制点,建立发车时间偏移、班次衔接的时间以及首末站和空驶距离等约束,构建了异质行程时间场景集,针对模型的规模大、约束复杂等特性,将原模型分解为多个子模型,并构建基于场景融合的分支定价算法进行求解。【数据】基于重庆市五条公交线路真实行车数据,构建不同线路数量的算例验证模型与算法的有效性与高效性,并对时间控制点参数设计敏感性测试。【结果】相比于传统策略,所提出的基于发车时间偏移的多线协同跨线调度策略可降低成本12.92%,提高公交车的车均载客总时间16.62%,缩短待班时间29.55%。敏感性分析表明,合理分配时间控制点的数量和布局可减少公交车的到站时间偏差和用车总成本,提高车辆工作效率和准时性。
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下载次数 | 被引频次 | 阅读次数 |
[1]交通运输部. 2023年交通运输行业发展统计公报[N].中国交通报, 2024-06-18(002).
[2] WANG C, SONG Y, FAN G, et al. Optimizing cross-line dispatching for minimum electric bus fleet[J]. IEEE Transactions on Mobile Computing, 2023, 22(4):2307-2322.
[3] ZHAO X, SUN H, LU J, et al. DP-TABU:an algorithm to solve single-depot multi-line vehicle scheduling problem[J]. Complex&Intelligent Systems, 2022, 8(6):4441-4451.
[4] SHANG H, LIU Y, WU W, et al. Multi-depot vehicle scheduling with multiple vehicle types on overlapped bus routes[J]. Expert Systems with Applications, 2023, 228:120352.
[5]翁剑成,乔润童,王茂林,等.考虑场景差异性的混合车型公交调度优化方法[J].交通运输系统工程与信息,2024,24(4):176-187.WONG Jiancheng, QIAO Runtong, WANG Maolin, et al.Optimization method for mixed vehicle bus scheduling considering scenario differences[J]. Journal of Transportation Systems Engineering and Information Technology,2024,24(4):176-187.
[6]姜晓红,过秀成,沈涵瑕,等.片区城乡公交时刻表编制与车辆调度综合优化[J].交通运输系统工程与信息,2019, 19(3):141-148.JIANG Xiaohong, GUO Xiucheng, SHEN Hanxia, et al.Integrated optimization for timetabling and vehicle scheduling of zone urban and rural bus[J]. Journal of Transportation Systems Engineering and Information Technology,2019, 19(3):141-148.
[7] LIU T, JI W, GKIOTSALITIS K, et al. Optimizing public transport transfers by integrating timetable coordination and vehicle scheduling[J]. Computers&Industrial Engineering, 2023, 184:109577.
[8] KLUMPENHOUWER W, WIRASINGHE S C. Optimal time point configuration of a bus route—a Markovian approach[J]. Transportation Research Part B:Methodological, 2018, 117:209-227.
[9] DOU X, YAN Y, GUO X, et al. Time control point strategy coupled with transfer coordination in bus schedule design[J]. Journal of Advanced Transportation, 2016, 50(7):1336-1351.
[10]龙雲,周剑峰,方侃,等.旅行时间不确定的灵活线路公交调度优化[J].交通运输工程与信息学报, 2024, 22(2):48-62.LONG Yun, ZHOU Jianfeng, FANG Kan, et al. Robust flexible-route bus optimization model considering travel time uncertainty[J]. Journal of Transportation Engineering and Information, 2024, 22(2):48-62.
[11] AVISHAN F, YAN?KO?LU?, ALWESABI Y. Electric bus fleet scheduling under travel time and energy consumption uncertainty[J]. Transportation Research Part C:Emerging Technologies, 2023, 156:104357.
[12]薛运强,郭军,钟蒙,等.基于不确定理论的常规公交车辆调度优化[J].交通运输系统工程与信息, 2021, 21(6):115-122, 130.XUE Yunqiang, GUO Jun, ZHONG Meng, et al. Optimization of regular bus scheduling based on uncertainty theory[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(6):115-122,130.
[13]姚恩建,王鑫,刘莎莎,等.考虑机会充电与行程时间可靠性的区域多车型电动公交调度优化[J].交通运输系统工程与信息, 2024,24(4):151-165,187.YAO Enjian, WANG Xin, LIU Shasha, et al. Regional electric bus scheduling optimization with multiple vehicle types considering opportunity charging and travel time reliability[J]. Journal of Transportation Systems Engineering and Information Technology, 2024,24(4):151-165,187.
[14] JIANG M, ZHANG Y, ZHANG Y. Optimal electric bus scheduling under travel time uncertainty:a robust model and solution method[J]. Journal of Advanced Transportation, 2021, 2021:1191443.
[15] SHEN Y, XIE W, LI J. A MultiObjective optimization approach for integrated timetabling and vehicle scheduling with uncertainty[J]. Journal of Advanced Transportation,2021, 2021(1):3529984.
[16] LI X, GUAN Y, HUANG J, et al. Robust service and charging plan for dynamic electric demand-responsive transit systems[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(12):15930-15947.
[17] BRUNI M E, GUERRIERO F, BERALDI P. Designing robust routes for demand-responsive transport systems[J]. Transportation Research Part E:Logistics and Transportation Review, 2014, 70:1-16.
[18] HUANG N, QIN H, XU G, et al. An enhanced exact algorithm for the multi-trip vehicle routing problem with time windows and capacitated unloading station[J].Computers&Operations Research, 2024, 168:106688.
[19]苏欣欣,伊廷刚,秦虎.分支定价割平面法求解带时间窗和人力分配的车辆路径问题[J].交通运输工程与信息学报, 2021, 19(4):75-86.SU Xinxin, YI Tinggang, QIN Hu. Branch-and-priceand-cut algorithm for the manpower allocation and vehicle routing problem with time windows[J]. Journal of Transportation Engineering and Information, 2021, 19(4):75-86.
[20]林海姣.纯电动公交时刻表与车辆排班计划整体优化方法研究[D].北京:北京交通大学, 2022.LIN Haijiao. Research on the overall optimization method of pure electric bus schedule and vehicle scheduling plan[D]. Beijing:Beijing Jiaotong University, 2022.
[21] GOEKE D, ROBERTI R, SCHNEIDER M. Exact and heuristic solution of the consistent vehicle-routing problem[J]. Transportation Science, 2019, 53(4):1023-1042.
[22]四兵锋,杨小宝,高亮.基于系统最优的城市公交专用道网络设计模型及算法[J].中国管理科学, 2016, 24(6):106-114.SI Bingfeng, YANG Xiaobao, GAO Liang. System optimization based bus-lane network design model and algorithm[J]. Chinese Journal of Management Science,2016, 24(6):106-114.
基本信息:
DOI:10.19961/j.cnki.1672-4747.2024.11.016
中图分类号:U491.17
引用信息:
[1]李欣,张赛,袁昀.时间波动环境下公交多线协同跨线调度优化[J].交通运输工程与信息学报,2025,23(01):119-134.DOI:10.19961/j.cnki.1672-4747.2024.11.016.
基金信息:
国家自然科学基金项目(52272317,52402381)