考虑值乘能力差异的地铁跨线乘务轮班计划优化方法

doi:10.16097/j.cnki.1009-6744.2025.02.023

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (2): 253-260.DOI: 10.16097/j.cnki.1009-6744.2025.02.023

考虑值乘能力差异的地铁跨线乘务轮班计划优化方法

李昊^a,b，陈绍宽^a,b，徐彬^*a,b，石梦彤^a，肖迪^a，陈梓琦^a

北京交通大学，a.交通运输部综合交通运输大数据应用技术交通运输行业重点实验室； b. 中国综合交通研究中心，北京100044

收稿日期:2024-12-05 修回日期:2025-01-04 接受日期:2025-01-18 出版日期:2025-04-25 发布日期:2025-04-20
作者简介:李昊(1997—)，男，山西原平人，博士生。
基金资助:
北京市自然科学基金(L191023)。

Urban Rail Transit Crew Rostering Optimization Method Considering Cross-line Operation and Crews Capacity Difference

LI Hao^a,b,CHEN Shaokuan^a,b,XU Bin^*a,b,SHI Mengtong^a,XIAO Di^a,CHEN Ziqi^a

a. MOTKey Laboratory of Transport Industry of Big DataApplication Technologies for Comprehensive Transport; b. Integrated Transport Research Center of China, Beijing Jiaotong University, Beijing 100044, China

Received:2024-12-05 Revised:2025-01-04 Accepted:2025-01-18 Online:2025-04-25 Published:2025-04-20
Supported by:
Natural Science Foundation of Beijing, China (L191023)。

摘要/Abstract

摘要： 针对地铁列车跨线运营模式，本文研究跨线运营模式下乘务员值乘能力与值乘任务的匹配度问题，分析乘务员值乘能力差异对乘务轮班计划的影响。建立考虑值乘差异的数学模型，构造基于轮班路径和禁忌序列的网络图简化模型，设计网络图搜索和结合差分进化策略的粒子群算法对模型分阶段求解。结合某市地铁部分线网乘务数据开展案例研究。结果表明：相较跨线运营模式下仅值乘本线任务的乘务员，具备值乘跨线任务能力的乘务员轮班周期内值乘班次数降低了1.58％~6.79％，两类乘务员值乘能力与值乘任务的匹配度均不低于95.77%；相较所有乘务员仅值乘本线乘务区段的分线值乘模式，跨线值乘模式下乘务员平均工作强度降低了3.79％~4.78％，工作强度标准差降低了22.67％~26.16％，改善了乘务员值乘强度均衡性。

关键词: 城市交通, 值乘能力, 网络图模型, 乘务轮班计划, 跨线运营

Abstract: Aiming at the cross-line operation mode of metro trains, this paper investigated the matching problem between crew capacity and duty assignment in cross-line operation and analyzed the influence of crew heterogeneity on crew rostering. The mathematical model was proposed in consideration of the difference of crew capacity, and the network graph based on shift path and taboo sequence was described to simplify the model. The network search method and improved particle swarm optimization algorithm were designed to solve the proposed model in stages. A case study was performed based on some urban metro lines crew data. Compared with the crew who were only on duty of single line under the cross-line operation mode, the number of duties of the crew who were qualified to take cross-line tasks can be reduced by 1.58% to 6.79%. The matching degree between the two types of crew capacity and duty task is not less than 95.77%. Compared with the split duty mode, the average duty intensity of the crew in the cross-line duty mode is reduced by 3.79% to 4.78%, and the standard deviation of work intensity is reduced by 22.67% to 26.16%. The duty balance of the crew can be improved.

Key words: urban traffic, crew capacity, network model, crew rostering, cross-line operation

中图分类号:

U292.6

李昊, 陈绍宽, 徐彬, 石梦彤, 肖迪, 陈梓琦. 考虑值乘能力差异的地铁跨线乘务轮班计划优化方法[J]. 交通运输系统工程与信息, 2025, 25(2): 253-260.

LI Hao, CHEN Shaokuan, XU Bin, SHI Mengtong, XIAO Di, CHEN Ziqi. Urban Rail Transit Crew Rostering Optimization Method Considering Cross-line Operation and Crews Capacity Difference[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(2): 253-260.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2025.02.023

http://www.tseit.org.cn/CN/Y2025/V25/I2/253

参考文献

[1]茧敏,陈绍宽,王卓,等.城市轨道交通网络跨线列车开行方案优化模型研究[J].交通运输系统工程与信息,2024,24(5):116-127. [JIANM,CHENSK,WANG Z, et al. Cross-line train service plan optimization in urban rail transit network[J]. Journal of Transportation SystemsEngineeringandInformationTechnology, 2024, 24(5):116-127.]

[2]温芳,柏赟,陈垚.考虑快慢车的城轨跨线运营开行方案与时刻表优化[J].交通运输系统工程与信息, 2024,24(3):172-183. [WENF, BAIY,CHENY,etal. Optimization of operation scheme and timetable for interconnected lines in urban rail transit considering express-local train[J]. JournalofTransportationSystems Engineering and Information Technology, 2024, 24(3): 172-183.]

[3] HEIL J, HOFFMANNK, BUSCHERU. Railway crew scheduling: Models, methods and applications[J]. EuropeanJournalofOperationalResearch,2020,283(2): 405-425.

[4] THOMASB,THOMASS,CHRISTOFS, et al.Athree phaseheuristicfor the fairness-oriented crew rostering problem[J]. Computers &Operations Research, 2023, 154:106186.

[5] DEAJ, CADARSOL, JUANAA, et al. Amulti-start randomizedheuristicforreal-lifecrewrosteringproblems in airlines with work-balancing goals[J]. Annals of OperationsResearch,2017,258(2):825-848.

[6] ZHOU J, XU XM, LONG J C, et al. Integrated optimization approach to metro crew scheduling and rostering[J]. TransportationResearchPart C: Emerging Technologies,2021,123:012975.

[7]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. [PANHC, QIBY, HUH, etal.Preference-orientedtask-type-mixedcrewrostering optimizationmodel forurbanrailwaytransit[J].Journalof Transportation Systems Engineering and Information Technology,2023,23(5):258-267.]

[8] QUESNELF,WUA, DESAULNIERSG, et al. Deep learning-based partial pricing in a branch-and-price algorithmfor personalized crew rostering[J]. Computers andOperationsResearch,2022,138:105554.

[9]金华,陈绍宽,冯旭杰,等.考虑乘务员值乘需求的地铁乘务轮班优化方法[J].铁道学报,2023,45(7):29 37. [JINH, CHENSK, FENGX J, et al. A crew rostering optimization method for urban rail transit considering crew preference[J]. Journal of the China RailwaySociety,2023,45(7):29-37.]

[10] QUESNELF,DESAULNIERSG, SOUMISF. Improving aircrewrosteringbyconsideringcrewpreferencesinthe crewpairing problem[J]. TransportationScience, 2019, 54(1):97-114.

[11] QUESNEL F, DESAULNIERS G, SOUMIS F. A branch and-price heuristic for the crew pairing problem with language constraints[J]. European Journal of Operational Research, 2020, 283(3): 1040-1054.

[12] ZHOU J, XU X M, LONG J C, et al. Metro crew planning with day-off pattern, duty type, and rostering scheme considerations[J]. Transportation Research Part C: Emerging Technologies, 2022, 143: 103832.

[13] LAI D S W, LEUMG J M Y, DULLAERT W, et al. A graph-based formulation for the shift rostering problem [J]. European Journal of Operational Research, 2020, 284 (1): 285-300.

[1]	晋泽倩, 俞诚成, 叶昕. 混合效用和后悔规则下的洪涝交通疏散决策行为研究[J]. 交通运输系统工程与信息, 2025, 25(2): 16-25.
[2]	周雨阳, 赵聪颖, 李京昆, 陈艳艳, 柳堤, 王书灵. 多类城市职住及通勤状态对出行方式选择影响比较[J]. 交通运输系统工程与信息, 2025, 25(2): 26-35.
[3]	彭其渊, 刘思源, 江山, 冯涛, 陈垚, 张永祥. 贯通运营下市域铁路与地铁列车开行方案协同优化[J]. 交通运输系统工程与信息, 2025, 25(2): 36-47.
[4]	蒋阳升, 叶肖甫, 徐尉耀, 刘洪汛, 胡路. 考虑转运与拼车的共享自动驾驶电动汽车动态运营[J]. 交通运输系统工程与信息, 2025, 25(2): 58-68.
[5]	赵雪亭, 胡立伟, 周君. 城市交通拥塞风险场级联失效及韧性评估研究[J]. 交通运输系统工程与信息, 2025, 25(2): 146-156.
[6]	武慧荣, 王玉莹, 盛椿婷. 考虑动态需求的城市货运公交线路规划模型研究[J]. 交通运输系统工程与信息, 2025, 25(2): 214-226.
[7]	徐伟汉, 李欣, 王天奇. 基于生态驾驶的常规和需求响应公交混合调度方法[J]. 交通运输系统工程与信息, 2025, 25(2): 227-240.
[8]	薛锋, 肖恩, 杨颖, 金成, 罗建. 基于多旅行商问题建模的地铁乘务排班计划优化[J]. 交通运输系统工程与信息, 2025, 25(2): 261-272.
[9]	张鹏, 吴照杰, 孙超, 李文权. 路口混合放行下的干线红波带宽最小优化模型[J]. 交通运输系统工程与信息, 2025, 25(2): 293-303.
[10]	许奇, 秦贝宁, 任澎, 陈越, 赖瑾璇. 建成环境对公交接驳地铁客流的异质性影响[J]. 交通运输系统工程与信息, 2025, 25(2): 352-363.
[11]	姚明, 王宇航, 曹淑超, 马露涵. 手机分心条件下行人运动特性研究[J]. 交通运输系统工程与信息, 2025, 25(2): 364-372.
[12]	翁剑成, 周慧缘, 张梦媛, 于江波. 考虑城市与群体异质的新能源车激励策略有效性研究[J]. 交通运输系统工程与信息, 2025, 25(1): 2-14.
[13]	李熙莹, 卢美燕, 何兆成, 苏淑妍, 庞淑敏. 基于车辆动态行为特征的交通状态识别研究[J]. 交通运输系统工程与信息, 2025, 25(1): 44-55.
[14]	王连震, 马志飞, 程国柱, 郑夫水. 城市道路智能网联汽车专用车道设置研究[J]. 交通运输系统工程与信息, 2025, 25(1): 56-66.
[15]	左忠义, 刘泽宇, 杨广川. 基于引力影响模型的轨道交通网络关键节点识别研究[J]. 交通运输系统工程与信息, 2025, 25(1): 102-112.

考虑值乘能力差异的地铁跨线乘务轮班计划优化方法

Urban Rail Transit Crew Rostering Optimization Method Considering Cross-line Operation and Crews Capacity Difference

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics