考虑司乘人员工作时间窗的高铁快巴车辆调度与人员排班综合优化

doi:10.3976/j.issn.1002-4026.2020.02.011

山东科学 ›› 2020, Vol. 33 ›› Issue (2): 71-78.doi: 10.3976/j.issn.1002-4026.2020.02.011

考虑司乘人员工作时间窗的高铁快巴车辆调度与人员排班综合优化

李凯明，宋瑞^*，郭小乐

北京交通大学综合交通运输大数据应用技术交通运输行业重点实验室，北京 100044

收稿日期:2019-11-26 出版日期:2020-04-20 发布日期:2020-03-30
通信作者: 宋瑞（1971—），博士，教授，研究方向为城市交通运输规划与管理。 E-mail:rsong@bjtu.edu.cn
作者简介:李凯明（1995—），男，硕士研究生，研究方向为城市交通运输规划与管理。E-mail：17120829@bjtu.edu.cn
基金资助:
国家重点研发计划（2018YFB1201402）

Simultaneous vehicle and crew schedule optimization of express buses for high-speed railways considering work-time window

LI Kai-ming, SONG Rui^*, GUO Xiao-le

Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport，Ministry of Transport，Beijing Jiaotong University，Beijing 100044, China

Received:2019-11-26 Online:2020-04-20 Published:2020-03-30

摘要/Abstract

摘要： 针对新型公交服务产品如高铁快巴仍然缺少相应的运营方式的情况，对高铁快巴的车辆调度与人员排班的综合优化问题进行研究。为发挥高铁快巴灵活性的优势，引入了满足司乘人员工作时间要求的时间窗约束，建立了考虑司乘人员时间窗的高铁快巴车辆调度与人员排班综合优化模型。通过算例计算，得到了高铁快巴的最优调度与排班方案。结果表明，相比于传统的多线调度独立优化，在高铁快巴的优化问题上使用综合模型的效果更好，综合优化后运营成本比原运营方案降低约8.98%、比独立优化降低约4.73%，同时减少了司乘人员数量，验证了该模型在解决高铁快巴问题上的正确性与良好应用效果。

关键词: 城市交通, 高铁快巴, 车辆调度, 人员排班, 工作时间窗, 综合优化

Abstract: In this study, the integrated vehicle and crew scheduling problem of express buses on high-speed railways is studied owing to the lack of appropriate operational approaches for this new type of public transport service product. To benefit from the flexibility of express buses for high-speed railways, the work-time window constraint is introduced to meet the work-time requirements of the crew. An integrating optimization model for vehicle and crew scheduling is built. Then, the optimal vehicle and crew scheduling program is validated with real-time examples. Results show that this integrated optimization model is better than the traditional multiple route optimize independently. Operating costs are reduced by approximately 8.98% compared with the original operation schedule and approximately 4.73% compares with the independent optimization using this integrated optimization model, while the number of crew is also reduced. Furthermore, the accuracy and the satisfactory results of the model in solving the integrated vehicle and crew scheduling problem of express buses for high-speed railway are verified herein.

Key words: urban transportation, express bus for high-speed railways, vehicle scheduling, crew scheduling, work-time window for crew members, integrating optimization

中图分类号:

U491

李凯明, 宋瑞, 郭小乐. 考虑司乘人员工作时间窗的高铁快巴车辆调度与人员排班综合优化[J]. 山东科学, 2020, 33(2): 71-78.

LI Kai-ming, SONG Rui, GUO Xiao-le. Simultaneous vehicle and crew schedule optimization of express buses for high-speed railways considering work-time window[J]. Shandong Science, 2020, 33(2): 71-78.

参考文献 18

1	OUGHALIME A, ISMAIL W R, LIONG C Y, et al. Vehicle and driver scheduling modelling: a case study in UKM[C]//2009 2nd Conference on Data Mining and Optimization,Kajand, Malaysia：IEEE, 2009: 53-59. doi: 10.1109/dmo.2009.5341911
2	RODRIGUES MM, DE SOUZA C C, MOURA A V. Vehicle and crew scheduling for urban bus lines[J]. European Journal of Operational Research, 2006, 170(3): 844-862. doi: 10.1016/j.ejor.2004.06.035
3	HUISMAN D, WAGELMANS A P M. A solution approach for dynamic vehicle and crewscheduling[J]. European Journal of Operational Research, 2006, 172(2): 453-471. doi: 10.1016/j.ejor.2004.10.009
4	IBARRA-ROJAS O J, DELGADO F, GIESEN R, et al. Planning, operation, and control of bus transport systems: a literaturereview[J]. Transportation Research Part B: Methodological, 2015, 77: 38-75. doi: 10.1016/j.trb.2015.03.002
5	PRILESZKY I, HORV-TH B. New ways in vehicle and crew scheduling[J]. Acta Technica Jaurinensis, 2011, 4(2): 297-304.
6	LAM E, VAN HENTENRYCK P, KILBY P. Joint vehicle and crew routing andscheduling[M]//Lecture Notes in Computer Science. Cham: Springer International Publishing, 2015: 654-670. doi: 10.1007/978-3-319-23219-5_45
7	DOM-NGUEZ-MART-N B, RODR-GUEZ-MART-N I, SALAZAR-GONZ-LEZ JJ. An exact algorithm for a vehicle-and-driver scheduling problem[J]. Computers & Operations Research, 2017, 81: 247-256. doi: 10.1016/j.cor.2016.12.022
8	DE ATHAYDE PRATA B. Amultiobjective metaheuristic approach for the integrated vehicle and crew scheduling[J]. Journal of Transport Literature, 2016, 10(2): 10-14. doi: 10.1590/2238-1031.jtl.v10n2a2
9	HUISMAN D, FRELING R, WAGELMANS A P M. Multiple-depot integrated vehicle and crewscheduling[J]. Transportation Science, 2005, 39(4): 491-502. doi: 10.1287/trsc.1040.0104
10	FRELING R, HUISMAN D, WAGELMANS A. Models and algorithms for integration of vehicle and crew scheduling[J]. Journal of Scheduling, 2003, 6(1): 63-85. doi: 10.1023/A:1022287504028
11	MESQUITA M, PAIAS A, RESP-CIO A. Branching approaches for integrated vehicle and crewscheduling[J]. Public Transport, 2009, 1(1): 21-37. doi: 10.1007/s12469-008-0005-2
12	MESQUITA M, PAIAS A. Set partitioning/covering-based approaches for the integrated vehicle and crew schedulingproblem[J]. Computers & Operations Research, 2008, 35(5): 1562-1575. doi: 10.1016/j.cor.2006.09.001
13	DE GROOT S W, HUISMAN D. Vehicle and crew scheduling: solving large real-world instances with an integrated approach[M]//Lecture Notes in Economics and Mathematical Systems. Berlin, Heidelberg: Springer, 2008: 43-56. doi: 10.1007/978-3-540-73312-6_3
14	HAASE K, DESAULNIERS G, DESROSIERS J. Simultaneous vehicle and crew scheduling in urban mass transitsystems[J]. Transportation Science, 2001, 35(3): 286-303. doi: 10.1287/trsc.35.3.286.10153
15	陈明明, 牛惠民. 带时间窗的多车场公交乘务排班优化[J]. 兰州交通大学学报, 2015, 34(4): 100-106. doi: 10.3969/j.issn.1001-4373.2015.04.019
16	陈明明, 牛惠民. 多车场公交乘务排班问题优化[J]. 交通运输系统工程与信息, 2013, 13(5): 159-166. doi: 10.3969/j.issn.1009-6744.2013.05.024
17	张宇石, 陈旭梅, 于雷, 等. 基于换乘站点的轨道交通与常规公交运营协调模型研究[J]. 铁道学报, 2009, 31(3): 11-19. doi: 10.3969/j.issn.1001-8360.2009.03.003
18	MESQUITA M, MOZ M, PAIAS A, et al. A new model for the integrated vehicle-crew-rostering problem and a computational study onrosters[J]. Journal of Scheduling, 2011, 14(4): 319-334. doi: 10.1007/s10951-010-0195-8

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考虑司乘人员工作时间窗的高铁快巴车辆调度与人员排班综合优化

Simultaneous vehicle and crew schedule optimization of express buses for high-speed railways considering work-time window

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